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World Aviation Festival growth and significance

Since its inception 21 years ago, the World Aviation Festival has grown from a modest gathering to a major industry event. This year’s festival highlighted this transition, with post-pandemic recovery driving significant attendance and engagement. The rapid growth of the event underscores the relevance and importance of the topics discussed, especially with the aviation industry experiencing a vibrant resurgence, growing 24% to a market worth $1.5 trillion.¹

As a supporter of the event, Microsoft met with industry leaders, customers, and partners to discuss the impact of growth, technological advancements, and a secure future for the industry. Our industry executives participated in three panels covering the topics of:

• Understanding how CEOs are approaching structural industry shifts, potential for growth, sustainability implications, and AI business transformation.
• How will generative AI impact the aviation sector, and what strategies can be employed to harness its potential.
• How can the aviation industry accurately identify risks and develop robust cybersecurity strategies to address global threats.

These panels inspired deeper follow-up conversations with conference attendees who we hosted in our meeting room suite and at our evening customer engagement event along with our industry partners. This provided an excellent opportunity to hear about the challenges and opportunities our customers face in an evolving industry and share success stories from industry peers who are leading change and delivering business results. Attendees were encouraged by this evidence and wanted to learn more about our cloud, AI, and data capabilities, including where we can support:

• Enhancing the employee experience—leveraging AI for communication and collaboration platform and digital tools that create connection and inspire collaboration with more insights.
• Innovating the traveler journey—by unlocking data intelligence to create frictionless, multi-modal travel solutions for customers.
• Creating efficient operations—that improve asset utilization, planning, and management of real-time operational impacts.
• Delivering a more engaging customer experience—to improve customer value, drive growth, and brand affinity.

Addressing aviation industry challenges and opportunities

With the many attendees at the event absorbing information across more than 600 speakers and 327 sessions, the following themes resonated as key to addressing the challenges and opportunities facing the industry.

Importance of information sharing

A recurring theme at the festival was the critical need for enhanced information sharing among airlines and airports. By integrating customer data from the moment a traveler leaves home through their entire travel experience, the industry has a significant opportunity to create personalized offers and services within their own, and extended ecosystems. This seamless customer journey was emphasized as crucial for enhancing the travel experience and operational efficiency. Another impact on information sharing is the operational differences between European and US airports that can impact data sharing and efficiency. European airports often have more integrated operations, which can enhance data sharing and streamline processes.

Focus on technology

The festival also placed a strong emphasis on leveraging new technologies, particularly AI, generative AI, and data analytics. These technologies were viewed as pivotal for the aviation industry’s growth, enabling better customer insights, personalized services, and operational efficiencies. Discussions also covered security and sustainability, highlighting their growing importance in today’s aviation landscape along with the increasing concerns over data privacy.

Legacy systems and new equilibrium

The aviation industry is at a crossroads, balancing legacy systems with the adoption of new technologies. While legacy systems still play a significant role, there is a strong push towards new distribution capabilities (NDC) and standards, such as those set by the International Air Transport Association (IATA). This shift is driven by the need to move away from outdated technologies and embrace solutions that utilize data effectively to enhance customer experience, operational efficiency, and to attract a new and more engaged workforce.

Startups leading the way

Startups are at the forefront of this technological revolution, unburdened by legacy systems and able to implement modern architectures and processes at speed. These innovative and agile companies are leading the charge in adopting new technologies and driving the industry forward. This enables a healthy and needed expansion of the industry ecosystem, and while it might pose some challenges for incumbents to compete, it also provides great opportunities to innovate and partner, further stressing the importance of re-thinking how the industry conducts its business to meet the demands of their customers.

Sustainability

Sustainability is a significant challenge, with the aviation industry aiming to be carbon neutral by 2050.² One area discussed is the introduction of sustainable aviation fuel (SAF). However, shortages of supply make the exploration of alternative fuels and sustainable practices beyond SAF important. For example, some industry scenarios are exploring electrification and hydrogen as a potential for specific use cases that can improve sustainable travel.

Technology enablers

Several key discussions at the festival highlighted the industry’s challenges and opportunities. Conversations with airlines like Alaska Airlines and Emirates provided insights into how AI and personalization technologies are being used to enhance customer experiences.

Agentic AI

While the focus on generative AI was pervasive, we also discussed the interest in AI agents, or agentic agents. Agentic agents are autonomous software programs that perform specific tasks on behalf of and alongside users, making decisions based on data, predefined rules and learning from experience. The benefits include a streamlined and user-friendly booking process, faster bookings, higher conversion rates, around-the-clock availability, personalized recommendations and potential upselling. We found companies were very interested in learning more about successful use cases where agentic AI has delivered results.

Reference architectures

In an environment where technology creates positive disruption that drives transformation, many different paths to an outcome may be explored. Rather than create a “one size fits all” approach to achieving those outcomes, we have created a composable base that partners and customers can leverage to develop their innovations using the Microsoft cloud, Azure, and industry focused reference architectures. This enables development of value-creating solutions on top of the Microsoft Cloud technology stack, helping airlines and airports manage data, break down silos, and improve operations. Customers like Adami and Fraport are leveraging these architectures to integrate data from various sources and enhance operational efficiency. Watch here to learn about our reference architecture for airlines and airports.

One major challenge is unbundling legacy systems that have been in place for decades. These systems need to be updated to utilize data effectively and implement new technologies that can help airlines operate more like e-commerce businesses.

Next steps for aviation industry innovation

The 2024 World Aviation Festival was a testament to the resilience and innovation of the aviation industry. With a focus on new technologies, information sharing, and sustainability, the festival showcased the industry’s commitment to enhancing customer experiences and operational efficiency. We were encouraged by participants’ interest in emerging cloud, data, and AI capabilities which are now seen as driving key competitive differentiation among airlines and a key opportunity to improve airport operations and services.

Moving forward from the event, we now look ahead to our key industry programs including Microsoft Ignite, and the global Microsoft AI Tour series underway, as well as the focus on the overall mobility landscape at CES 2025. We look forward to continue to working closely with our customers, ecosystem and industry to contribute and innovate for an even brighter and exciting future.

To learn more about Microsoft solutions for travel and hospitality, visit Microsoft for travel and transportation.

¹ Travel Professional News, Global travel industry roars back, reaching $1.5 trillion in 2023, August 2024.

² IATA, Net Zero Roadmaps.

The post Transforming the travel industry through innovation and collaboration: World Aviation Festival 2024 appeared first on Microsoft Industry Blogs.

AI transformation offers you a phenomenal chance to innovate and compete with new vigor—offering previously unimaginable opportunities. It is a term you are likely to hear more over the coming years, and Microsoft aims to place a copilot on every desk, every device and across every role in support of Microsoft’s mission to empower every person and every organization on the planet to achieve more.

As part of this, Microsoft has identified four areas of opportunity for organizations to drive their AI transformation¹:

• Enrich employee experiences.
• Reinvent customer engagement.
• Reshape business processes.
• Bend the curve on innovation.

The value of AI transformation and copilots

While it may feel instinctive that the value of AI transformation lies in its ability to save time, this is only part of the story. Early studies are already showing significant value from AI transformation being derived from not only reducing costs, but also increasing revenue and reducing risk through improved quality of decision making.

Highlights from key studies include benefits of:

• Delivered 25% increase revenue through enhanced efficiency.²
• Increased customer satisfaction by 12%.³
• Increased revenue growth by 4% through improved strategy and engagement.⁴
• Reduced costs of 10%.⁵
• Completed tasks 25% faster.⁶
• Reduced total expenditure by 0.7%.⁷
• Reduced risk through a 40% improvement in quality of decisions.⁸

The supply chain context

In an era of rapid global change, macroeconomic shifts, and geopolitical disruptions, the global supply chain faces unprecedented challenges. Simultaneously, technology is undergoing a transformation fueled by data and AI. These powerful tools and capabilities empower organizations to enhance efficiency, mitigate risk, and discover hidden opportunities.

As the world becomes increasingly complex, leading organizations are gravitating towards technology to accelerate supply chain optimization with greater speed and precision to shift the paradigm from a reactive mode of operating to one that is proactively getting ahead.

It is a foundational concept that supply chain excellence is achieved by consistently and efficiently getting the right products to the right place, in the right quantities, at the right time and at the desired quality, the first time. Doing this while respecting constraints and balancing inventory, waste, and transportation costs is what makes the work of a supply chain practitioner so difficult.

Integral to this challenge is optimized data management, real-time visibility combined with integration and interoperation across supply chain elements—such as production, logistics, procurement, partners, and customer service.

Yet so often, organizations struggle with siloed business processes, communications challenges, disconnected systems, complex planning workflows, transportation disruption, warehouse capacity issues and multiple other challenges leading to high inventory, increased costs, waste, and a lack of overall business resilience.

For a supply chain practitioner there are simply too many information sources to assimilate and consider when making better-informed decisions in real time. The practitioner can get started with a copilot to overcome fragmented data and integrate it into usable insights. Read about how Altana began overcoming fragmented knowledge—establishing a uniform understanding of the data/knowledge gap combining enterprise resource planning (ERP) systems, factory data, enriched with market and external risk factors.

The application of AI across the supply chain

With all the focus on generative AI, it can be easy to perceive that generative AI is the answer to all your problems. This would be incorrect—as ever there are no silver bullets. AI and generative AI are distinct, yet complementary technologies used for supply chain optimization that provide the analytical horsepower to process vast amounts of data that can deliver significant impact.

Non-generative AI techniques can be used for multiple different tasks in a supply chain context, for example:

• Clustering: Route planning for customer shipments and Warehouse slotting optimization.
• Classification: Inventory management approaches (for example, fresh, frozen) and resource allocation.
• Rules and heuristics: Inventory planning and distribution planning.
• Optimization: Inventory optimization, and route optimization and network design.
• Regression: Demand forecasting and supplier performance analysis.

Likewise, generative AI offers some incredible opportunities across the supply chain, which can be broadly placed into three groups:

• Content generation: For example, summarizing multiple contracts and agreements associated with a given supplier.
• Insight generation: For example summarizing multiple sources of external data to provide a perspective of events that could influence your demand forecast.
• User Interaction: Provision of a universal interface with which supply chain practitioners interact and spans multiple systems and allows for both understanding and interaction with systems that control the supply chain.

The control tower concept

You can think of your supply chain function as a central brain orchestrating data and physical movements across your organization. This is critical work, influencing all the key metrics that drive business performance.

The concept of a supply chain control tower appeared a few years ago as a centralized system providing real-time visibility and insights across the entire supply chain. It leverages a unified data platform to deliver next-generation supply chain capabilities, beginning with end-to-end visibility and performance management.

The concept looks to incorporate data from various sources to help you monitor, manage, and optimize your supply chain operations, enabling better decision-making and more rapid responses to disruptions.

Adding AI into this mix offers tantalizing possibilities—the ability to dramatically reduce the quantity of direct decision-making that supply chain practitioners need to be directly engaged in.

Enrich employee experiences

Generative AI is fundamentally changing how we, as individuals, relate to, and benefit from technology. While both generative AI and traditional AI contribute to supply chain optimization, generative AI emphasizes employee productivity and can work with a broader set of data, revolutionizing the types of insights you can glean with better explainability. The gamechanger here is the ability to use a conversational “agent” or copilot to navigate any task and turn data into knowledge through a conversational user interface using natural language. A copilot can enhance supply chain teams by providing real-time insights, automating routine tasks and workflows, and facilitating collaboration. For instance, it can analyze data to identify bottlenecks, suggest optimal routes for shipments, and streamline inventory management. It provides the ability to move beyond static dashboard reporting by extracting actionable insights to empower users.

A copilot for supply chain can help empower teams during their workday by converting predictive insights into specific actions while powering collaboration within a connected ecosystem.

This means organizations are better able to manage the cascading impact of their supply chain with more transparent and collaborative data sharing. Visibility improves because, where once it was restricted by the network it is now enhanced through a wider global context.

Internal data is augmented with real-time connections to partners and external signals—like geopolitical tensions, logistics challenges, and commercial factors like promotional activity or weather events. Data is continuously available and interoperable across the supply chain, giving users simultaneous access to current information, with the ability to pass on insights into the wider organization. Microsoft Teams and Microsoft 365 become engines in the connected ecosystem for greater connectivity and collaboration—empowering team members who may not be using supply chain systems—like a store manager or sales representatives—to be consumers of supply chain insights and information. This improves access to insights that are actionable at the optimal point in the value chain.

Copilots can dramatically improve productivity while accelerating decision-making. For example, take this common scenario where Hillary—an inventory analyst—needs to understand why projected cost and freight (CFR) of a key product has dropped and determine what to do to reduce impact on customer service level agreement (SLA).

Instead of compiling spreadsheets from different data sources and spending hours doing manual analysis, Hillary uses a combination of copilots and a CFR prediction algorithm to quickly identify the root cause, assess alternatives, and share the recommended approach with her manager.

Next steps to apply generative AI across your supply chain

We’ve explored some strategies for applying AI and generative AI across your supply chain, and how a supply chain copilot can support supply chain practitioners. Stay tuned for part two, where we delve into data considerations and how to get started on AI ideation for your organization.

Learn more

• Microsoft Copilot Studio
• Azure AI Studio
• Microsoft Cloud for Retail website
• Microsoft for Consumer Goods website
• Supply chain AI for the new era of value realization
• Unlock the full potential of your next-generation supply chain with Microsoft and Blue Yonder
• Empowering responsible AI practices

¹Embracing AI Transformation: How customers and partners are driving pragmatic innovation to achieve business outcomes with the Microsoft Cloud, Official Microsoft Blog.

²How Netlogic Computer Consulting is Boosting its Sales Performance with Microsoft Copilot for Sales, Tech Community.

³Microsoft: Copilot for Service Boosts Customer Satisfaction by 12 Percent, CX Today.

⁴What Can Copilot’s Earliest Users Teach Us About Generative AI at Work?, WorkLab.

⁵Is Microsoft Copilot Worth the Investment?, Varonis.

⁶Navigating the Jagged Technological Frontier.

⁷Is Microsoft Copilot Worth the Investment?, Varonis.

⁸Navigating the Jagged Technological Frontier.

The post Delivering your supply chain copilot: Prioritizing areas of ROI appeared first on Microsoft Industry Blogs.

The aviation industry is entering a new era: airlines and airports worldwide are on the brink of transformation, driven by the power of generative AI. This powerful technology is creating new value at every stage of the aviation ecosystem, revolutionizing the way we fly and operate. From personalized travel offers to instant responses for customer service requests, AI is enhancing every step of your journey, making travel smoother and more personalized than ever before.

Generative AI is also transforming the core operations of airlines and airports. Research shows that up to 35% of flight delays can be reduced through AI-powered decision-making—saving time, reducing stress, and increasing safety for both travelers and staff.¹

AI is also reshaping the workforce. With streamlined tasks and smarter tools, staff can dedicate more time to enhancing the passenger experience—both on the ground and in the air. AI-powered personalization can increase revenue per passenger by 10 to 15%. At the same time, intelligent AI chatbots can reduce customer service costs by up to 30%, creating significant value for both airlines and airports.²

This is the future of aviation. AI is not just a tool—it’s a revolution, creating value across the entire industry. Microsoft has developed a new industry reference architecture enabling AI for a seamless traveler journey, efficient airline operations, and enhanced airport operations. 

Seamless traveler journey

The experience begins the moment a traveler considers a trip. They can interact with an AI-powered mobile app to explore options, book flights, and receive personalized recommendations. Throughout their journey, the app serves as a digital assistant, providing real-time updates on flight status, gate changes, and the weather at the destination. At the airport, travelers can navigate through a touchless experience, from check-in to security, using biometric identification and e-boarding passes on their mobile devices. The app continues to assist by guiding them to their gate, offering lounge access, and updating any travel alerts.

Once on board, the digital assistant ensures a comfortable experience by allowing travelers to control in-flight entertainment, order food and items from the onboard shop, and adjust seating preferences through their mobile device. The journey concludes with the app facilitating a smooth arrival process, including customs and baggage claim guidance, and arranging for ground transportation. Throughout this journey, AI and machine learning algorithms work behind the scenes to anticipate needs, offer timely assistance, and personalize the travel experience.

Air India passengers, for example, now get answers to all their questions from planning to arrival at their fingertips. Their AI.g virtual assistant, powered by Microsoft AI services, quickly proposes a travel itinerary for passengers, finds answers about check-in options and flight status, recommends the best food options, finds the next business lounge or helps with lost luggage. Another example is Saudia Airlines. The flag carrier of Saudi Arabia developed an AI-powered travel companion for their passengers using Microsoft technology to enable travel-related services like: planning and booking, refund management, and exploring new destinations.

Efficient airline operations

AI working on data platforms enhances efficiency and customer experience across various segments of the airline value chain.

• In aircraft handling, AI-powered predictive maintenance can forecast potential issues before they occur, minimizing downtime and ensuring timely operations. Ground support equipment can be optimized using AI algorithms to streamline processes and reduce delays.
• In ground operations, AI can manage complex logistics, from baggage handling to fuel management, by analyzing vast amounts of data to optimize workflows and resource allocation. This leads to smoother operations and can significantly reduce turnaround times for aircraft.
• Flight operations benefit from AI through advanced analytics that can assist in route planning, weather forecasting, and fuel consumption optimization. By leveraging historical data and real-time inputs, AI can provide pilots and flight planners with insights that lead to safer and more cost-effective flights.
• For marketing and sales, AI enables personalized customer experiences by analyzing customer data to tailor offerings and promotions. This can lead to increased customer loyalty and revenue as airlines can offer the right product to the right customer at the right time.
• In customer support, AI-powered chatbots and virtual assistants provide around the clock support, handling inquiries and resolving issues promptly. This not only improves customer satisfaction but also frees up human agents to deal with more complex queries, enhancing overall service quality.

Lufthansa, for example, developed the one data platform built on Microsoft Azure to provide self-service applications and leverage cognitive AI services like image and speech recognition.

“Leveraging Microsoft Azure’s robust cloud capabilities, we’ve transformed Lufthansa’s operations with a unified data platform. This innovation empowers us to optimize every aspect of our service, from ground operations to in-flight experiences, ensuring punctuality and safety across our global network—continuing to use AI will help us advance to the level.”

Ganesh Swaminathan, Head of Platforms, Lufthansa Group Digital Hangar

American Airlines, the world’s largest airline, is using Azure as its preferred cloud platform. Their team members now use the ConnectMe app for the latest crew information while the airline is using AI to reduce taxi time and turn times at gates.

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Enhanced airport operations

Generative AI and data platforms also play a pivotal role in enhancing airport operations, catering to the needs of tens of thousands of passengers daily. Airports can optimize their critical infrastructure management, such as energy, water, and climate control. The integration of AI into security and emergency services significantly enhances their capabilities, providing a safer and more secure environment for travelers. Connected transportation systems such as buses and trains benefit from predictive analytics and real-time data processing capabilities, leading to improved scheduling and passenger flow management.

In the realm of commerce, which encompasses retail stores and restaurants within the airport, generative AI and data platforms offer valuable insights into consumer behavior, enabling businesses to tailor their services and inventory to meet the dynamic needs of passengers.

The logistics and supply chains for cargo, fuel, and baggage are also transformed by these technologies, with AI-powered systems facilitating better tracking, forecasting, and management of resources. This results in a more streamlined and cost-effective operation, reducing delays and enhancing the overall passenger experience. Fraport has introduced FraportGPT, an example of an employee-facing app powered by Microsoft Azure OpenAI Service to streamline internal processes.

“Fraport’s company GPT app, powered by Generative AI, has been a resounding success, swiftly adopted by our team. It’s not just streamlined our processes; it’s accelerated skill acquisition, empowering our employees to master new competencies with unprecedented speed.”

Christian Wrobel, Chief Data Architect, Fraport AG

Together with Microsoft, Miami International Airport (MIA) has developed a centralized data hub environment, known as the Common Data Environment (CDE), to store, manage, and share business data, apps, and business process flows. This is crucial for breaking down data silos and ensuring data accessibility for analysis and helps unlocking additional value from generative AI.

“By integrating various data sources, including on-premises, cloud, and edge environments, we provide a unified and scalable platform for data management. This is the basis, and together with our partner Microsoft we will now be able to leverage advanced technologies such as AI, machine learning, and IoT to gain insights, make data-driven decisions, and drive innovation.”

Maurice Jenkins, Chief Innovation Officer, Miami International Airport

The overarching reference architecture and partners

Our common architecture for airports and airlines is built among core elements with the ultimate goal to create AI-enhanced experiences for everyone, from passengers to ground personnel: the creation of user-facing applications, data storage and analytics, and data ingestion and integration of existing data systems.

The AI-enhanced experiences are tailored to each user group.

• For passengers, it is all about a smooth journey from origin to destination, with plenty of time to enjoy travel with retail, entertainment, and restaurant offers.
• Ground staff and customer service focus on making the passenger experience smooth, even when something goes wrong.
• Pilots and crew members require support for coordination, communication, and the reduction of their management overload.
• For technicians, it is about knowing where to go next, reducing cognitive workload for maintenance and repair tasks, and automating documentation.
• Terminal managers require support to manage traffic, ensure security, and provide travel comfort.
• For airside operators, it is about managing baggage, refueling, and safety.

Different user groups require different backend applications and data sources. The user-facing applications layer describes some of the common front-end experiences that can be built using Microsoft services.

• End users require mobile and web applications built using services such as Azure API Management, Azure App Service and Azure Functions. Developers create AI-powered user experiences leveraging services such as Azure OpenAI Service. These applications can be deployed in Azure tenants and can scale to millions of users.
• Business users leverage Dynamics 365 (Customer Service, Finance, Project Operations, and Customer Insights) to manage business operations, such as claims, promotions, and ticketing. Dynamics 365 has built-in custom agents for many common business use cases such as customer service, sales, finance, field service, and customer insights.
• Front line workers are fully integrated in the business with customized workflows and automated operations with custom AI, tailored to their needs and the ergonomics of their workplaces—wherever fixed terminals, mobile devices, or augmented reality. Microsoft Copilot Studio facilitates the creation of custom AI agents to support their work. Power Apps enables the creation of custom user interfaces, while Power Automate enables the creation of business workflows.
• With Microsoft 365 Copilot, employees can collaborate and communicate using Microsoft products such as Microsoft Teams, SharePoint, and Outlook.

The operation of airports and airlines generates large amounts of data. The data storage and analytics layer describes how to securely store business data to support operations and create insights.

• Microsoft Dataverse is a scalable data platform that securely stores and manage business data. The data model is a structure framework that organizes data in tables with relationships. It is possible to use industry models to harmonize and integrate business data across multiple applications.
• Microsoft Fabric is an end-to-end data and analytics platform that includes real-time analytics capabilities. OneLake is a unified logical data lake that centralizes and simplifies data management, with multiple analytical engines and workspaces. Fabric enables organizations to process and analyze data for timely insights and decision making.

Airports and airlines are established businesses. It is important to integrate existing data systems, such as connected assets as well as existing systems. Messaging services on Azure enables connectivity to assets and devices using standardized communication protocols such as Message Queuing Telemetry Transport (MQTT) with Azure Event Grid, or data streams like Apache Kafka using Azure Event Hubs. Serverless solutions like Azure Functions provide compute to process messages.

We’re also proud to collaborate with leading partners driving innovation in aviation.

• Amadeus and Microsoft have formed a global strategic partnership that harnesses cloud technology to innovate and explore new products and solutions and create smoother travel experiences.
• SAP deployments on Azure provide robust cloud solutions tailored to customer needs.
• Our partnership with SITA, and their SITA Mission Control solution, helps duty personnel anticipate and respond to real-time changes during flight operations.
• We also integrate independent software vendors (ISVs), such as SmartKargo, PROS, and Satavia, to contribute to a smarter, more connected aviation ecosystem.

Creating frontline worker experiences

Frontline worker experiences are highly customized to the task and require constant adaptation. The power of low-code platforms like Power Apps and Copilot Studio significantly reduce the time to value, allowing for rapid development and deployment of tailored solutions. These platforms enable the integration of multiple data sources, such as location-based services, logistical information from Dynamics 365, and documentation search. Additionally, task support is enhanced through the use of knowledge graphs and manuals, while collaboration and information regarding connected assets are seamlessly incorporated.

Overcoming the challenges of using AI in aviation

While the potential of AI in aviation is immense, there are key challenges: defining the most valuable AI use cases, setting up cloud infrastructure, organizing the data estate, and minimizing costs during development, testing, and deployment phases.

Microsoft addresses the challenges of AI in aviation by working closely with partners, establishing a framework for responsible and trusted AI principles, and leveraging its comprehensive suite of tools and services. It helps define valuable AI use cases through collaborative workshops and industry-specific solutions. Azure provides scalable cloud infrastructure, while Microsoft Dataverse and OneLake streamline data management. Cost efficiency is achieved through optimized development, testing, and deployment processes. Additionally, Microsoft provides extensive training programs to equip employees with necessary AI skills and collaborates with regulatory bodies to ensure compliance with legal frameworks governing AI usage.

Moving forward with generative AI in aviation

Taking advantage of generative AI requires a pragmatic approach, where existing solutions are combined with new capabilities and partner solutions. Correctly identifying the use cases with the highest priority and impact is critical for success.

Visit Microsoft for travel and transportation or contact our team to learn more and take the next step in your AI journey.

“We’re excited to introduce our new reference architecture for the aviation industry, built on Azure’s cloud capabilities and advanced AI tools. What truly makes this effort stand out is our collaboration with leading aviation partners. Together with our partners, we’re shaping the future of the aviation industry.”

Julie Shainock, Managing Director Travel & Transportation Industry, Microsoft

“Microsoft’s Industry Solutions team is ready to help you deliver and implement AI-driven solutions across your organization: From a first [proof of concept] POC to full-scale rollouts, we are dedicated to providing the expertise you need to ensure a smooth and successful deployment.”

Eric Chaniot, General Manager of AI Industry Solutions, Microsoft

“At Microsoft Cloud for Industries, we are committed to empowering our partners with proven patterns and comprehensive enablement resources. By leveraging our industry-specific solutions and collaborative approach, we help partners accelerate innovation, streamline operations, and deliver exceptional value so that their customers can achieve more.”

Monica Ugwi, General Manager Cloud for Industries, Manufacturing & Mobility, Microsoft

¹Worldmetrics: AI in the Airline Industry, 2024.

²The economic potential of generative AI, McKinsey & Co., 2023.

The post AI solutions and data platforms for the aviation industry appeared first on Microsoft Industry Blogs.

At Microsoft, our mission has always been one of empowerment. AI furthers this mission. When harnessed together with modern compute and infrastructure, Microsoft AI offers unprecedented access to information that can help solve complex manufacturing problems faster. To showcase this innovation, we recently attended the International Manufacturing Technology Show (IMTS) 2024 in Chicago, Illinois, and demonstrated how Microsoft and its partners are accelerating industrial transformation outcomes with AI. Read on to experience IMTS for yourself, with our highlights and the 3 areas we believe the Microsoft Cloud for Manufacturing and AI are driving real industry impact.

• Design better products with AI-powered insights
• Build products smarter with AI-optimized manufacturing
• Modernize frontline operations with AI-assisted workers

Design better products with AI-powered insights

Design is the cornerstone of manufacturing, shaping not only product functionality, aesthetics, and performance but influencing production efficiency, material use, and long-term sustainability. This critical stage presents significant opportunities to optimize manufacturing processes and reduce costs that are often locked in early. With generative design and AI-enabled solutions like predictive modeling and digital twins, we can analyze real-time performance data and simulate alternatives rapidly to minimize material waste, reduce errors, and improve time-to-market.

Moreover, for many modern connected products, software is an increasingly significant component—driving functionality, value, and the transformation of traditional dynamics. Generative AI streamlines software development by accelerating code generation with tools like Github Copilot, allowing engineers to iterate faster, improve overall quality, and design more sustainably. The combined impact is a more agile, efficient development process that reduces time-to-market, enhances product performance, and fosters sustainable innovation. As software continues to integrate deeper into connected products, generative AI empowers engineers to push the boundaries of what’s possible within design and manufacturing.

Harnessing data for streamlined product development with PTC

In the Microsoft booth, our partner PTC demonstrated the impact AI can have on product lifecycle with a well-managed digital thread. Their demo showed how Vestas, a wind turbine manufacturer, leverages PTC’s design, Application Lifecycle Management (ALM), and Product Lifecycle Management (PLM) solutions to develop products. PTC’s new digital thread solution uses Azure and Microsoft AI to bring these tools together to enable real-time data synchronicity, traceability, and version control across Vestas’ product lifecycle. This single source of truth simplified the development process and enabled Vestas to continue reusing valuable data throughout the product’s lifecycle.

Build products smarter with AI-optimized manufacturing

Manufacturing success today requires a seamless integration of materials, technology, and resources. With these complex environments, AI is changing how we think about industrial operations. The merging of physical assets with AI, IoT, and automation solutions is enabling manufacturers to optimize production, reduce downtime, and improve real-time decision making for greater competitiveness.

Microsoft Cloud for Manufacturing centralizes data in the cloud, unifying its structure. Once organized, AI solutions can extract data’s hidden value analyzing it for insights, including predictive maintenance by identifying shop floor patterns and anomalies that may indicate potential equipment failures. AI-enabled factories allow manufacturers to better manage supply chains, anticipate these production shifts, and optimize their resource allocation.

For mission-critical operations, Azure IoT Operations ensures your data is processed on-premises for immediate action, before being sent to the cloud for further analysis. Azure IoT Operations takes an adaptive cloud approach, supported by Azure Arc, which enables manufacturers to unify data across their hybrid, multi-cloud, and edge environments. An adaptive cloud approach simplifies infrastructure management and security while maximizing resource utilization and ensuring AI-powered solutions scale across production lines and multiple sites. By adopting this approach, manufacturers can streamline operations, improve scalability, and establish a standardized architecture, ensuring resiliency and continuous improvement across the enterprise.

Enabling OT intelligence for autonomous operations with Rockwell

AI has already demonstrated its ability to digest information and offer accurate recommendations. How does this translate to manufacturing factories? Rockwell demonstrated how IoT solutions can enlighten older OT assets and processes. Rockwell enables organizations to transform their factory equipment into IoT-enabled assets. This live operational data is then centralized in the cloud through Azure IoT Operations, where predictive AI can automatically identify and address maintenance needs, enhance workflows, and perform tasks that once needed onsite staff.

Modernize frontline operations with AI-assisted workers

Frontline workers and service teams are the backbone of manufacturing operations. Their expertise, adaptability, and problem-solving skills are critical for maintaining production efficiency—ensuring quality control and driving continuous improvement in environments where the digital world meets the physical world. When empowered by AI, these workers become decision-makers freed from repetitive tasks. AI allows frontline workers from the factory floor to the field to focus on higher-value activities, improves their productivity, and enables them to adapt to the evolving demands of modern manufacturing.

Generative AI enables service teams to seamlessly create work orders from unstructured data like emails, efficiently schedule resources, and provide timely support—particularly during high-demand periods. For frontline workers, AI offers fast and intuitive access to essential information, eliminating the need to manually sift through long standard operating procedures, equipment manuals or contact expert support. By delivering the right information at the right moment with natural language prompting, generative AI not only improves first-time fix rates but also accelerates worker upskilling, preparing them for more complex responsibilities and driving long-term productivity gains.

Delivering exceptional customer service with Dynamics 365 Field Service

At IMTS 2024 we showcased how Microsoft Copilot in Dynamics 365 Field Service is enabling workers to solve problems more efficiently and deliver exceptional customer experiences. Delivering exceptional service is key for building customer preference and loyalty. Copilot in Dynamics 365 Field Service can help service managers and technicians efficiently create workorders, schedule workers and find the information they need to resolve issues right the first time while keeping customers updated at every step of the process. With the added capabilities of Microsoft Dynamics 365 Remote Assist capabilities in Microsoft Teams, frontline workers can call for expert help and utilize augmented reality features such as spatial annotations reducing asset downtimes and efficient service experience for customers.

Continuing AI conversations beyond IMTS 2024

Manufacturing is undergoing a profound transformation. It is clear, AI will be at the heart of this change. From revolutionizing product design with AI-driven insights and optimizing manufacturing processes with predictive analytics to empowering frontline workers with easy access to information, AI is fundamentally reshaping how industries operate. IMTS 2024 underscored our vision for manufacturing and the impact AI will have on industrial operations. From PTC to Rockwell to Microsoft Copilot in Dynamics 365 Field Service, AI is driving innovation and enabling manufacturers to overcome operational bottlenecks.

As AI adoption accelerates, organizations will face challenges such as inadequate data, expertise gaps, and governance. Microsoft is committed to helping manufacturers overcome these obstacles and realize the full potential of AI. By combining modern cloud infrastructure and compute with powerful AI tools, Microsoft can enable every organization to scale their AI initiatives across multiple sites and functions, moving them beyond “pilot purgatory” to achieve long-term, sustainable transformation.

Explore Microsoft solutions

Now is the time. Along with its partners, Microsoft can help every manufacturer unlock the value in their data, streamline operations, and drive greater value chain efficiency. Whether you’re just beginning your journey or looking to scale, Microsoft can support you at every stage.

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• Learn how Microsoft can help you overcome barriers to AI adoption and drive real impact in your manufacturing value chain by reading this report we created in collaboration with MIT Technology Review Insights.
• Explore how Microsoft is helping other organizations accelerate their transformation on our industrial transformation webpage.

The post 3 practical ways industrial AI is reshaping manufacturing appeared first on Microsoft Industry Blogs.

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Organizations are looking for intelligent supply chain solutions

The COVID-19 pandemic didn’t necessarily create new challenges for supply chains. Instead, it magnified problems that already existed. Lockdowns, for example, brought into stark relief the fragility of many supply chains, leading to evident shortages of raw materials and finished goods. These events underscored a crucial point in 2020: to efficiently handle disruptions and meet customer needs, organizations need real-time visibility into their supply chain. Businesses need to go a step further. Not only do companies need to monitor every supplier, process, and system supporting operations, but they also must be able to contextualize this information to proactively mitigate risks and prepare for future possibilities. That alone requires serious coordination and a lot of brainpower.

This is where AI enters the scene. Enterprises that have relied on traditional paper-based systems, legacy tools, and on-premises databases to manage supply chains, are looking for intelligent solutions to address the long-standing issues of disruption, visibility, and risk. AI—particularly generative AI—stands out as a viable solution to query across data silos and provide meaningful insights to enhance the efficiency and effectiveness of supply chain operations.

Customizing generative AI for your supply chain operations

AI has been a part of supply chain management for decades, with its roots in traditional AI applications like computer algorithms and data analysis in logistics and inventory management. However, the recent shift to generative AI is transforming the landscape by leveraging powerful data infrastructures and cloud platforms. Unlike traditional AI, generative AI democratizes insights through natural language processing, making critical information accessible to everyone across an organization.

For example, tools like Microsoft Copilot highlight the disruptive potential of generative AI when seamlessly integrated with enterprise resource planning (ERP), supply chain planning, warehouse, transportation, customer relationship management (CRM), and many other business systems. Copilot’s integration with Dynamics 365 shows how AI-powered, interactive assistance can revolutionize supply chain management (SCM), driving efficiency, reducing costs, and enhancing customer satisfaction. Nevertheless, it’s important to recognize that generative AI alone cannot solve long-standing challenges like supply chain disruption and risk.

To truly harness AI’s potential, organizations must adopt a comprehensive approach, combining intelligent solutions to break down data silos and foster supply chain resilience. Generative AI tools such as Copilot deliver optimal outcomes when paired with platforms like Microsoft Fabric and Azure Open AI Service that contextualizes the data from many sources. This synergy boosts operational effectiveness with seamless orchestration to drive productivity and profitability. However, it’s essential to choose business applications that operate on centralized, cloud-based platforms with integrated AI and machine learning, connected workflows, and a unified database to fully unlock AI’s value for your supply chain.

Redefining business value through AI and data integration

AI is not just about improving productivity for specific roles—it’s a powerful tool for driving business value and enhancing outcomes across the entire organization. Take, for instance, the case of Cemex, a global concrete manufacturer that took up to an hour to respond to confirm their customer orders. Time taken to analyze the fulfillment option is necessary to avoid revenue loss, customer dissatisfaction, and environmental risks from waste. Traditionally, customer representatives would spend about an hour to validate ingredient supply, equipment readiness, labor availability, and delivery logistics. However, by integrating AI into their daily job, these tasks could be handled in seconds, dramatically improving business performance.

This manufacturer aimed to enhance more than just speed—they wanted to transform the entire process with AI-powered insights. Leveraging Azure, Azure OpenAI Service, and Microsoft Teams, they achieved impressive results. Azure OpenAI Service utilized vast amounts of historical data stored in Microsoft’s secure cloud to analyze and contextualize information in real time. This contextualization was crucial in quickly assessing whether a new order could be fulfilled, driving faster, more informed decision making.

The time to fulfill customer orders dropped from an hour to just nine seconds, showcasing how integrating AI and data can drive substantial business outcomes—far beyond mere productivity gains. This transformation not only enhanced operational efficiency but also elevated customer satisfaction and overall business agility.

This demonstrates how AI innovation is not only feasible but also highly accessible, empowering organizations to embed intelligence into their operations and realize greater business value across the board.

Microsoft’s commitment to responsible, accurate, and trustworthy AI

When generative AI and machine learning are applied to centralized data models, they create opportunities to enhance supply chain efficiency and profitability. However, success lies in adopting the right technology and infrastructure that unify processes and data while prioritizing security, accessibility, and reliability.

Microsoft is uniquely equipped to drive AI advancements in supply chain management by promoting responsible AI practices. Their platforms are secure, extendable, and interoperable, ensuring seamless data and supply chain orchestration. Microsoft delivers AI-powered innovations such as Copilot across its entire platform, as well as a range of applications from data summarization to more critical, high-stakes decisions that directly impact supply chain operations.

Understanding that supply chain management demands precision and accountability, Microsoft enables organizations to refine use cases and add structure to Copilot models, allowing Supply Chain Management users to inquire about data points and track shifts in customer demand within defined timeframes, such as year-over-year or period-over-period. This level of specificity delivers granular insights, saving organizations substantial time otherwise spent on manual research.

Integrating AI into supply chain operations

Microsoft’s approach to integrating AI into supply chain operations focuses on grounding data within a relevant, secure framework, to make sure that insights are reliable and credible. Their AI models are designed to not only analyze past actions but to also forecast what can be achieved next. With the combination of different AI techniques and Microsoft’s secure cloud platforms, organizations can build on this innovation using low-code and no-code tools, unlocking new use cases, and driving trustworthy AI adoption across their operations.

Explore Microsoft Cloud for Manufacturing to see how you can accelerate your transformation.

The post Optimize supply chain resiliency by integrating diverse AI-powered solutions appeared first on Microsoft Industry Blogs.

Generative AI is revolutionizing the way that people interact with their applications. Microsoft is at the forefront of this change by integrating Microsoft Copilot into its products and empowering customers and partners to build their own copilot experiences. Today, copilots have been developed to enhance the productivity of industry functions and roles. These copilots synthesize data from multiple systems, providing information workers with streamlined access to data that can lead to faster, better decision-making and empowers the workforce.  

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The power of mobility copilots 

In the automotive industry, information workers are found across many business functions: research and development, manufacturing, sales, digital experiences, after-sales, and commercial operations. Information workers have different roles and tasks, for example: 

• Requirement engineers: Define functions of the vehicle based on market requirements.
• Software developers: Create new software defined vehicle functions.
• Fleet operators: Operate mobility services and fleet operations for commercial operations using fleet management solutions.
• Repair and maintenance technicians: Provide repair and maintenance services in the workshop. 

A function-based copilot can leverage multiple systems to provide a unified user experience for increasing productivity. To be more effective, the copilot user experience can be optimized for each type of end-user depending on the nature of their tasks and work environments. For example, the copilots run in different types of applications, devices, and uses, such as, end-user programs, desktop computers, mobile applications, or as voice only assistants—requiring different types of user interactions. Application and data integration in automotive can be complex as the ecosystem of software vendors create specialized data and applications that address industry-specific needs, such as functional safety and compliance during development, and right-to-repair regulation for after sale. 

For connecting, ingesting, and analyzing mobility and industrial data, organizations can use Microsoft Azure data analytics and messaging services such as Microsoft Fabric,  Real-Time Intelligence, and Event Grid, to process streaming data from different kinds of devices, from vehicles to robots. Furthermore, Copilot, available across the Microsoft stack in trusted products such as Dynamics 365, Microsoft 365, and Microsoft Teams, can promote additional collaboration, and increase productivity. 

The latest mobility partner copilots 

Microsoft Industry Clouds is redefining the way industries operate, with tools and guidance to support partners in the creation of industry copilots. Mobility-specific reference architectures are available to help to plan and build complete solutions. As part of the Microsoft commitment to empowering a global partner ecosystem of industry experts, we work closely with partners to build solutions based on customer pain points. Microsoft recently collaborated with industry partners, Netstar and KPIT, to create copilots that address concrete needs in the automotive industry. These solutions will soon be available in Azure Marketplace:

• Netstar has created a fleet operations copilot that simplifies the work of the fleet manager by interacting with vehicle, driver, and task management subsystems.
• KPIT has created a repair and maintenance copilot that enables repair and maintenance workers to fix vehicles faster, at first visit, thus increasing customer satisfaction. 

Fleet operations copilot from Netstar 

Fleet operators need to focus on operational efficiency to maintain and increase business profits—this means making quick decisions on vehicles, driver allocations, schedules, and tasks to optimize cost. Furthermore, to obtain a comprehensive view of the operation while in the office and on the move, a fleet manager relies on information from multiple systems. 

Netstar has created a copilot that integrates different systems to provide a unified experience that enables fleet managers to extract relevant information quickly and make decisions grounded on data insights in a short amount of time.  

The copilot integrates fleet information and telemetry data from the Real-Time Intelligence component from Fabric using two techniques: 

• A predefined query set that executes common queries on vehicles, trips, and health.
• A Kusto Query Language (KQL) query generation approach that creates dynamic queries on a scoped data set. 

To simplify interaction, Netstar has integrated custom cards that provide location information and maps to visually represent the position of vehicles and trips.

Repair and maintenance copilot from KPIT  

Modern vehicles are complex from the mechatronic and software point of view. This leads to longer repair times, dissatisfied customers, and unnecessarily replaced part warranty cases, known as “no-fault found”, incurring costs for the automotive manufacturer. Customer satisfaction is deeply affected if vehicles cannot be fixed correctly at a fair price, on the first try. Hence, repair and maintenance is critical to the profitability of the automotive OEMs and their relationship with customers. 

A repair and maintenance technician uses multiple systems to fix a car. These systems range from specialized tools for vehicle diagnostics to digital repair and maintenance manuals, repair procedures, and schematics. Additionally, they need to track all labor and cost times. 

To address these challenges, KPIT has created Trace2Fix, a repair and maintenance copilot that interacts with the following elements: 

• Vehicle diagnostics tooling to communicate with the car and read vehicle health, measurements, actuator control, and software lifecycle management.
• AI-powered reasoning engine to diagnose issues by analyzing symptoms, evidence, and fault codes to identify the most probable root cause. The copilot then directs technicians through optimal test steps, providing access to relevant repair procedures and schematics.
• Sample connections to the dealer management system and customer relationships management that leverages Dynamics 365 to handle appointments, scheduling, customer information, and inventory management. 

KPIT addressed interaction with the technician using both voice-only interfaces to facilitate hands free operations as well as custom cards to quickly display relevant repair information on different device types. With this solution, a repair and maintenance technician can access multiple systems to have information at their fingertips, leverage the Trace2Fix’s dynamic root-cause analysis and reasoning engine, and perform all necessary business actions to perform their tasks quicker. 

Tools for building your own copilot 

There are several options for creating industry specific copilots to address a variety of function and role-based needs.

For pro-code developers, copilots can also be created as services that leverage Semantic Kernel and connect to data sources and systems that are relevant for the customer scenario. The copilots are deployed as services in the cloud and integrated into front-end solutions. 

This high-level diagram shows a common approach for the creation of a function-based copilot backend: 

• API Management provides managed access to the copilot API, simplifying integration with multiple device front ends (such as mobile apps, desktop applications, augmented reality, and more.)
• Usage statistics to improve the operation of copilots are stored in Fabric. They are used to improve the response of the copilots based on feedback from the users.
• Memory along with user and vehicle profiles are stored using Azure Cosmos DB.
• Plugins implement the required data and capabilities for copilot—such as integration of vehicle telematics data using Fabric with Real-Time Intelligence, retrieval-augmented generation using AI search for vehicle documentation, and integration of business data from the dataverse.

For businesses looking to get started building copilots right away, Microsoft Copilot Studio offers an accelerated approach to creating copilots with minimal development expertise. Businesses can create function-based copilots to meet specific user needs. Organizations can also leverage the Copilot Studio Gallery, which offers industry-specific copilot templates that incorporate tailored business logic and custom prompts, streamlining operations and decision-making processes.    

Learn more about how you can create your own copilots using Microsoft Copilot Studio. 

Explore mobility solutions

• Discover how Microsoft is powering the future of mobility. 
• Learn more about the featured partners: Netstar and KPIT.   

The post Accelerating the automotive sector with mobility copilots appeared first on Microsoft Industry Blogs.

At the heart of this initiative are industry prompts in Copilot Lab and industry templates in Microsoft Copilot Studio—two platforms tailored to meet the unique demands of various businesses. These platforms are not just about providing tools; they’re about delivering a seamless experience that aligns with our customers’ operational workflows, enhancing productivity and fostering creativity.

Copilot Lab serves as a portal for innovation, offering diverse industry prompts that cater to the specific needs of job functions and industries. Getting up to speed on AI prompts can be challenging from both a technical and practical standpoint. If AI prompts are vague or lack necessary details, AI models can produce off-target responses. Copilot Lab provides a repository of prompts that resonate with industry professionals, enabling them to generate meaningful outcomes with Microsoft Copilot’s assistance.

Copilot Studio includes industry copilot templates that can simplify the adoption process for businesses. These templates incorporate industry-specific business logic and custom prompts that streamline operations and decision-making processes. These templates, available in the Copilot Studio Gallery, represent fully working copilots that often only require configuration or integration for an organization to adopt them.

As we continue to build and co-create, our vision is to not only enhance the capabilities of Microsoft Industry Clouds but also to help redefine the way industries operate. By providing accelerators that drive mainstream adoption and co-building with industry partners, we’re setting a new standard for industry solutions.

Industry AI prompts in Copilot Lab

In our continuous pursuit of empowering organizations across various industries, Microsoft has introduced a suite of industry-specific prompts within Copilot Lab. These prompts are a culmination of our efforts to provide a more context-aware AI experience that leverages users’ domain expertise to drive better outcomes. Our new industry prompts help customers quickly get started using Copilot for sector, job, and role-specific scenarios and can be customized with domain-specific details, best practices, and industry context to reduce trial and error and ensure high-quality output. These prompts can create an interactive experience for sector-, job-, and role-specific users, which can enhance prompts and deliver tailored responses, continually improving based on user interactions.

The genesis of these prompts was a collaborative effort, drawing on insights from industry professionals to ensure quality and relevance. The initiative begins with the financial services, retail, and manufacturing industries, introducing 24 industry-specific prompts within Copilot Lab, marking the start of a broader vision to integrate industry-specific intelligence into business operations.

These prompts are readily accessible in Copilot Lab, where users can select prompts that resonate with their professional needs. They are designed to help users ask relevant and specific questions, enabling Copilot to generate insights from data that are finely tuned to their industry’s nuances.

The introduction of these prompts is part of our broader vision to bring industry-specific intelligence to the forefront of business operations. By providing these tailored tools, we aim to enhance productivity and foster innovation within the Microsoft 365 environment.

Accessing these prompts is simple. Within Copilot Lab, a collection of pre-built prompts categorized by industry. Users can select the one that fits their role, and let Copilot do the rest. Users can further customize the prompts with domain-specific details and best practices.

Figure 1: User selects the retail prompt category and picks the outlet visit preparation prompt.

Figure 2: The prompt is copy/pasted into Word and a document is generated for editing and use.

Industry copilot templates in Copilot Studio

Industry copilot templates in Copilot Studio help users streamline the adoption of AI solutions across various sectors, providing pre-built dialogs, intents, entities, prompts, and actions that can be easily customized and extended according to the user’s needs using a low-code/no-code experience.

The templates offer a quick and efficient way to get started with AI, with configurations and rollout typically taking only a few hours. They include publicly accessible and customizable data sources, allowing customers to change the default data source with their own to get the copilot ready for business. This feature is particularly beneficial for industries that require rapid deployment and flexibility, such as retail and sustainability.

For instance, the Sustainability Insights Copilot template empowers users with easy access to data and insights regarding a company’s sustainability goals and progress, while the copilot template for store operations is designed to enhance the efficiency of retail frontline workers by providing easy access to store procedures and policies. These templates were part of the Copilot template Gallery unveiled at Microsoft Build 2024 and represent Microsoft’s commitment to empowering users with AI tools that are both powerful and adaptable to their specific industry needs.

Figure 3: Copilot Studio Sustainability Insights Copilot template.

Copilot Studio is available worldwide, across 22 datacenters, and supports multi-lingual experiences, making it a versatile tool for global enterprises. The studio’s capabilities are continually expanding, with support for 23 languages and growing, helping to ensure that users can build solutions and respond in their preferred language.

For more detailed information on how to utilize these new features and to stay updated on future releases, users can refer to the resources provided by Microsoft Copilot Studio.

Learn more about industry-specific AI tools

Microsoft remains dedicated to empowering customers through innovation. Our latest offerings in Copilot Lab and Copilot Studio reflect our commitment to providing industry-specific AI tools that are not only powerful but also intuitive and accessible. By continually investing in these technologies, we aim to help ensure that organizations, regardless of size or sector, can harness the full potential of AI to drive efficiency, creativity, and growth.

Get started by exploring detailed guides and information on our industry prompts and templates at Copilot Lab and Copilot Studio. Learn more and stay informed about Microsoft’s advancements in AI by exploring Copilot for Microsoft 365 Tech Community Blog and the Microsoft Industry Blog for insig

The post Innovating at the speed of AI: Microsoft’s industry Copilot solutions appeared first on Microsoft Industry Blogs.

Microsoft, in partnership with IoT Analytics market research firm, conducted a global survey of manufacturers to gain insight into how they are seizing the AI opportunity while navigating key industry challenges. We asked manufacturers about their current priorities and future visions, their adoption of modern technologies and paradigms, and the benefits they expect from those technologies 

In this report, we share the key findings from the survey, to show how manufacturing enterprises are preparing their shopfloors for AI to make them secure, scalable, and automated and how they are adopting advanced technologies such as centralized device management, software containerization at the edge, and unified industrial data operations to accelerate that process.

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Read on to discover the six key lessons learned from manufacturers rethinking their operations for AI and how Microsoft is supporting the factory of the future with Microsoft Azure’s adaptive cloud approach.

Six findings from manufacturers preparing their shop floor for AI

1. Scale matters the most in the era of AI

Scalability was the main concern for 72% of survey respondents, who highlighted this paradigm as crucial for their factory’s future. Scalability came first, followed by automation and serviceability. These paradigms ensure that factories can efficiently expand with demand, optimize with minimal manual decision making, and maintain high uptime through easy troubleshooting and maintenance. 

What does scale look like for industrial environments? 

Manufacturers face the challenges of keeping up with the changing demands of the market, the regulations, and the competition. They also recognize the potential of AI to transform their operations, optimize their processes, and enhance their products. But they don’t have the luxury of spending months or years on deploying and scaling solutions across their plants. Manufacturers need a faster way to move, a smarter way to manage, and a more flexible way to adapt. That’s why we have introduced a new approach—the adaptive cloud approach. 

To learn more, see how the adaptive cloud approach is designed to help manufacturers unify their teams, sites, and systems with cloud-native and AI technologies that work seamlessly across hybrid, multicloud, edge, distributed computing, and the Internet of Things (IoT). The adaptive cloud approach empowers manufacturers to deliver value faster, manage devices more efficiently, and run applications more securely to prepares them for the AI-powered factory of the future.  

2. Cybersecurity and data management are top of mind right now 

Security risks and data handling difficulties pose serious problems, with 58% of respondents seeing cybersecurity as a severe issue and 49% seeing data management as a severe issue. These concerns are motivating customers to improve network security and ensure data is reliable and accessible for decision-making. 

What does security look like for industrial environments? 

Security and data protection are critical for the manufacturing sector, as the sector faces increasing regulatory standards and cyber threats. Manufacturers need to secure existing devices, and plan during device refresh to choose devices that meet industry security standards, will enable them to more easily comply with regulatory standards, and provide security to defend from the latest security threats.  

To learn more, see Microsoft’s comprehensive approach to security, from device to cloud, that helps customers meet their compliance needs and defend against attacks. For existing devices, Microsoft provides firmware and network scanning with Microsoft Defender for IoT, which allows customers to inventory their devices and monitor for vulnerabilities and threats. For new devices, customers can choose from leading industry original equipment manufacturers (OEMs) devices labeled Secured-core, which meet the latest security requirements. Both existing and new devices can be monitored and remediated using Microsoft Defender and Microsoft Sentinel.

3. Device management is critical for security and data handling 

Device management’s value is evolving beyond updates and device health monitoring to also address security risks and data flow management. The survey data supported this trend, with 68% of respondents noting that the security monitoring aspect of device management was very or extremely important to their organization and 59% of respondents highlighting data management as the second most important aspect of device management. 

Why is centralized device management important? 

Centralized device management is vital for ensuring the performance and security of operations in a factory setting. It helps to keep devices secure and functioning optimally, which contributes to the overall efficiency and productivity of a manufacturing environment. Effective management also enables better oversight and control over the factory processes, improving operational reliability and supporting scalability and adaptability in a dynamic industrial landscape.

To learn more, see how Azure Arc delivered centralized management for IT and OT environments. Manufacturers can define resources, such as hybrid, multi-cloud, edge, and IoT, to Azure Resource Manager so services such as system health monitoring, security, and many others can be easily applied across a globally distributed digital estate.

4. Containerized workloads are coming to the shop floor 

The adoption of containerized software on the shop floor is rising, with 85% of survey respondents already utilizing this technology. This shift towards containerization at the edge signifies a move to improve operational efficiency, system stability, and security. 55% of respondents indicated that containerized software could significantly or extremely mitigate reliability and uptime challenges, while 53% indicated it could do the same for cybersecurity challenges.

What is containerized software? 

Software containerization enables consistent and repeatable development and deployment of solutions across different environments, in the cloud and in factory. Containerization of OT software is essential for the AI-powered factory of the future, as it enables seamless technology deployment in scalable, serviceable, and automated factories. Kubernetes automates the scaling and management of containerized applications, saving time and resources for manufacturers.

To learn more, see how Azure Kubernetes Service helps to securely modernize and optimize Kubernetes environments with unified management, governance, and monitoring. Azure Kubernetes Service (AKS), helps teams accelerate app development and deployment with best-in-class tools and generative AI. With AKS, enabled by Arc, these benefits can also be extended to on-premises and edge-based applications 

5. Industrial data operations optimize OT data management

Companies want to combine information technology (IT) and operational technology (OT) systems for context driven decision making. 52% of respondents indicated that having a combined IT and OT data platform was very or extremely important for their company. Industrial data operations enhance the integration of IT and OT data by improving data flow, quality and value; therefore, 87% of companies have already adopted industrial data operations technology in some form or are planning to do so.

What are industrial data operations? 

Industrial data operations delivers data in a reliable, real-time manner for optimizing factories and plants. Industrial data operations manages and unifies data from various sources, facilitates seamless integration of information, and ensures data is accessible and usable for decision-making purposes. Industrial data operations helps break down data silos and improve predictive insights through an exchange and integration between shop floor and cloud environments.

To learn more, see how Azure IoT Operations handles data from equipment and systems in OT environments, ensuring that data is collected, pre-processed, and integrated into applications running onsite. This service, announced in public preview at Ignite 2023, embraces industry standards—such as, Open Platform Communications Unified Architecture (OPC UA), Message Queuing Telemetry Transport (MQTT), OpenTelemetry (OTel)—and natively integrates into Microsoft Fabric. Microsoft Fabric, handles data for cloud environments, centralizing data on one open, organization-wide data lake to eliminate sprawl and reduce duplication. It allows creating and managing AI models on a single foundation, reducing data movement and time to value.

6. Respondents are investing in underlying data architecture for AI 

According to the study, manufacturers plan to invest in AI-powered factories of the future within the next two years. On average, respondents expected their organizations to increase their investments in software for orchestrating edge AI by 11%. This investment shows that they recognize the need to overcome technical and skill gaps to fully exploit AI’s capabilities in future manufacturing processes. 

How to invest in underlying architecture for AI? 

Microsoft recommends adopting advanced technology frameworks such as centralized device management, software containerization at the edge, and unified industrial data operations to accelerate industrial transformation and prepare for AI. Azure’s adaptive cloud approach embraces all three advanced technology frameworks. 

Accelerate industrial transformation in manufacturing

To learn more read the full 2024 IoT Signals report, a comprehensive survey of manufacturers’ priorities, challenges, and plans for adopting new technologies, such as these, in their factories to prepare for AI. The report shows that manufacturers are looking for solutions that can help them secure, scale, and automate. Microsoft Azure is responding to these needs with its adaptive cloud approach, which offers a flexible and scalable platform for managing devices, applications, and integrated data across the edge and the cloud.

To view a presentation of this survey by IoT Analytics’ CEO and Microsoft’s GM of Azure IoT and Edge, recorded at HMI 2024, click here.

To discover more insights and best practices for accelerating industrial transformation, download the 2024 IoT Signals report below.

The post 6 findings from IoT Signals report: Manufacturers prepare their shop floor for AI appeared first on Microsoft Industry Blogs.

At the heart of this transformation is our global ecosystem of partners and developers who build industry solutions on the Microsoft Cloud. Organizations are only beginning to grasp the full extent of the possibilities that lie ahead to innovate and transform with AI. Microsoft and our partners are investing in industry-specific capabilities to help customers adopt revolutionary AI solutions faster like copilot templates to create AI assistants for high value scenarios and industry data solutions that provide a data and analytics foundation to ensure your data is AI ready. 

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The age of copilots

Copilots, your everyday AI companion that assists with complex cognitive tasks, helps streamline operations, and enhances decision making, are becoming integral to almost every aspect of work and creativity. Powered by advancements in machine learning and natural language processing, copilots are impacting nearly every industry and business function, such as healthcare, manufacturing, financial services, and agriculture.  

For example in healthcare, Stanford Medicine is deploying Nuance DAX™ Copilot, an AI assistant that automates clinical documentation such as visit summaries and care instructions, to reduce heavy administrative workloads that lead to physician burnout and expand access to personalized, high-quality care. In a preliminary survey of Stanford Health Care clinicians using DAX Copilot, 78% reported that it expedited clinical notetaking.  

In manufacturing, Volvo Group is using Microsoft Azure AI to streamline invoice and document processing in their customer service and finance departments, which had to process critical internal and customer-facing paperwork in various forms from emails to PDFs and written bills. By extracting data from images, like photographs and stamps, and translating documents to and from multiple languages, Volvo Group is saving more than 850 manual hours per month. 

These success stories are just the beginning. We are also collaborating with industry partners to bring the power of copilots to their workforce and their customers, including LSEG (London Stock Exchange Group) in financial services, Bayer in agriculture, and Siemens in manufacturing.  

LSEG (London Stock Exchange Group), one of the world’s leading providers of financial markets infrastructure with more than 45,000 customers in over 170 countries, is using AI to improve productivity with interoperable, secure, and compliant solutions that help optimize strategies and enable faster data-driven decisions in financial services. By integrating Microsoft Copilot capabilities into existing workflows, LSEG is working with Microsoft to build a new, interoperable solution to streamline meeting preparation for financial services professionals like investment bankers, built directly into Microsoft Teams. This solution makes it easier to discover data, summarize documents, and support investment bankers, making their customer interactions more efficient and informed. 

Additionally, LSEG is creating custom chatbots and copilots within its flagship LSEG Workspace platform that makes it easier to switch to Teams through seamless, end-to-end workflows, enabling interoperability with custom application environments to provide quick answers to financial queries. Capitalizing on AI, LSEG’s solutions will transform the financial services industry by improving productivity and accelerating value creation for customers. 

Bayer, a global enterprise with core competencies in the life science fields of healthcare and agriculture, is piloting a unique generative AI solution for agriculture, trained by Bayer agronomists using proprietary Bayer product data. The solution aims to assist Bayer team members by providing quick and accurate answers and support to agronomy, farm management, and Bayer agricultural product-related questions. The system responds to natural language queries, generating concise, relevant information within seconds, a significant improvement over the traditional time-consuming process of information gathering and synthesizing. AI is quickly becoming an indispensable technology for the agriculture industry, with the potential to serve agronomists and benefit farmers globally. The collaboration with Microsoft as a leading technology partner is enabling exploration of ways to integrate this technology into Bayer’s digital offerings, with broad opportunities for collaboration with other agricultural offerings and partners. 

Siemens is a leading technology company focused on industry, infrastructure, transport, and healthcare. Siemens’ Industrial Copilot is a generative AI-powered assistant designed to enhance human-machine collaboration and boost productivity in manufacturing, exemplifying the transformative solutions and sustainable growth potential of our global partner ecosystem. Siemens Industrial Copilot allows users to rapidly generate, optimize, and debug complex automation code, and significantly shorten simulation times from weeks to minutes. It ingests automation and process simulation information from Siemens’ open digital business platform, Siemens Xcelerator, and is enhanced with Microsoft Azure OpenAI Service.  

To find out more about solutions specific to your industry, please visit Microsoft AppSource.  

New copilot templates for retail and sustainability

In our ongoing effort to foster innovation, we are excited to introduce more ways to help you jumpstart your copilot journey. At Microsoft Build 2024, we announced new copilot templates for retail and sustainability. 

1. Store operations help retail frontline workers improve customer service and productivity by using natural language to query store operating procedures, processes, and policies on topics such as product returns. 

2. Sustainability insights enable users to easily obtain insights, facts, and data around their own company’s sustainability goals and progress. 

Available through Copilot Studio, these templates provide ready-made dialogs, intents, entities, prompts, and actions that can be easily customized and extended according to the user’s needs. 

Additionally, we will be adding industry-specific prompts to the Microsoft Copilot Lab. These new prompts will help customers quickly get started using Copilot for sector, job, and role-specific scenarios and can be customized with domain specific details, best practices, and industry context to reduce trial and error and ensure high-quality output. 

Fuel AI with industry data solutions in Microsoft Fabric

An AI-ready data estate is critical to the success of AI. Analyzing vast amounts of data, often unstructured or semi-structured, poses a significant challenge for any organization. Our industry data solutions built on top of the Microsoft Fabric platform provides a one-stop-shop for data integration, data engineering, real-time analytics, data science, and business intelligence without compromising the privacy and security of your data. Data solutions in Microsoft Fabric provide a robust platform for customers and developers to manage all their data in one place, leverage a suite of analytics experiences that work together seamlessly, and apply AI to help make data driven decisions that address challenges unique to their industry. Some of these data solutions available in preview include:  

Healthcare data solutions in Microsoft Fabric (preview) 

This tailored solution enables healthcare organizations to break down data silos and harmonize their disparate healthcare data in a single unified store where analytics and AI workloads can operate at-scale. Leveraging the native capabilities of the platform, healthcare organizations can create connected experiences at each point of care, empower their workforce, and unlock value from clinical and operational data.  

Retail data solutions in Microsoft Fabric (preview) 

For retailers to truly deliver personalized experiences through generative AI for their customers, the first step is to break down data silos within their organizations and get a holistic understanding of their data estate. A unified data platform is the key to unlocking deeper, actionable insights that give retailers the ability to drive more meaningful experiences for customers. Achieving data compatibility is also a key step to getting value from AI investments, ultimately allowing retailers to optimize store operations, enhance store associates’ performance and productivity, and uncover insights for product upselling and shelf optimization. Partners like Sitecore are already connecting and building on top of the platform to further help retailers overcome data incompatibility and unlock new capabilities in Microsoft Cloud for Retail. 

Sustainability data solutions in Microsoft Fabric (preview)  

The solution allows organizations to centralize and transform disparate data into standardized environmental, social, and governance (ESG) data lakes. It also enables the collection and processing of subscription and resource level emissions data. Users can connect to their data in Microsoft Cloud for Sustainability solutions to create custom environmental notebooks and build insights to better understand their carbon, water, and waste emissions. These capabilities are provided through prebuilt and preconfigured Fabric resources, that can be easily configured for your sustainability needs. 

Resources to drive innovation

To get started and learn more about our complete set of data and AI industry solutions, visit Microsoft Industry Clouds or sign-in to your account on Microsoft Cloud Solution center. 

Learn more at the Copilot learning hub, where you can discover how Microsoft Copilot can help you in your specific industry.  

Learn more about these announcements at Microsoft Build 2024

• Microsoft Build opening keynote with Satya Nadella, Kevin Scott, and Rajesh Jha
• Next generation AI for developers with the Microsoft Cloud
• Enabling ISVs to transform industries in the age of copilots
• Launch AI applications and get to market faster with marketplace
• Transforming the most valuable industry workflows with Copilot
• Shaping next-gen development: the future of Copilot in Power Platform
• Microsoft Fabric: What’s new and what’s next
• Build your own copilot with Microsoft Copilot Studio
• Grow your business with Copilot extensions and marketplace

¹Number of employees worldwide from 1991 to 2024, Statista.

The post Accelerating business transformation with industry AI and copilots appeared first on Microsoft Industry Blogs.

1. Amplify human ingenuity with a copilot for everyone: Offering built-in and extensible AI capabilities in Microsoft Copilot to help people be more productive, creative, and efficient.
2. Deliver transformational experiences with build-your-own intelligent apps: Making it easy for customers and partners to build their own copilot solutions using the same stack and AI services Microsoft used to build its own copilots.
3. Safeguard business and data with a trusted AI platform: Microsoft has demonstrated leadership and delivered powerful tooling to help build safety and responsibility into AI solutions from the start—this includes guidance and best practices around responsible AI as well as secure AI principles that empower organizations with an end-to-end cyber risk approach that reinforces human control.

Part of enabling customers to adopt AI and deploy copilots includes empowering partners. Microsoft helps partners benefit from its unified data estate platform to create personalized, role-specific AI that can empower customers with meaningful and relevant experiences. Copilots can enhance development capabilities and allow partners to share the value of their domain experience with customers, reinforcing their commitment to innovation and excellence. Partners can extend and customize existing copilots from Microsoft or modify how copilots assist with core business functions, such as human resources, sales, or customer service interactions.

Building with partners

Partners play a crucial role in extending Microsoft’s offerings to customers with their domain expertise. When tailored to specific roles, copilots can personalize generative AI experiences, offering access to relevant business flows and data, when and where users need it.

The partners featured here have created copilots and AI platforms that support a wide range of industries and lines of business:

• TomTom has created its Digital Cockpit to turn cars into conversational companions.
• Modern Requirements has created an AI work item and requirements management assistant for healthcare, finance, automotive, aerospace, government, and defense industries.
• Dynatrace has developed Davis® AI which empowers countless use cases, supporting Microsoft Azure customers in areas like observability and security.
• Intellect Design has developed generative AI-powered copilot which allows a relationship manager to generate valuable insights from ISO 20022 payments repository data thereby helping corporations manage their funds better.
• Datamatics has created a partner onboarding copilot to help streamline and reduce the time spent on the onboarding process for vendors, partners, and more.
• MiHCM has developed an AI-powered human resources (HR) copilot called MiHCM SmartAssist.

TomTom

The TomTom Digital Cockpit is an open, modular in-vehicle infotainment platform. Their new AI-powered voice assistant enables users to engage in natural conversation with their cars and tackle complex driving requests. The voice assistant can handle follow-up questions and maintain contextual understanding, which means users can engage in multi-turn conversations and get relevant responses.

Key features include:

• AI-powered voice interaction: The digital cockpit enables natural voice communication with the vehicle, allowing drivers to control navigation, infotainment systems, and vehicle settings through voice commands.
• Integration with Microsoft Azure: TomTom utilizes Microsoft Azure OpenAI Service, Azure Cosmos DB, and Azure Kubernetes Service to provide a robust and scalable infrastructure, supporting advanced data handling and AI capabilities that enhance responsiveness and personalization.
• Customizable user interface: Automotive manufacturers can customize the digital cockpit to match their brand’s aesthetics and functionalities, making it adaptable to different vehicle models and consumer preferences.
• Cost efficiency: The system offers a cost-effective solution that reduces development expenses by up to 80%, providing a sustainable and economically viable option for car manufacturers.

Modern Requirements

Copilot4DevOps Plus is an AI-powered work item and requirements management assistant, which can be utilized by multiple industries such as healthcare and medical devices, finance, automotive, services and technology, aerospace, government, and defense. This tool, seamlessly integrated with Azure DevOps, optimizes requirement workflows with an easy-to-use interface and improves the requirements management process by enabling several key functions:

• Efficiency and productivity: It allows teams to focus on meaningful work by automating repetitive tasks and improving collaboration. In addition to powerful AI elicitation, analysis, conversion, and summarization, it gives teams cutting-edge features like pseudocode generation, dynamic prompts, and test script creation.
• Enhanced quality and security: Copilot4DevOps improves the quality of requirements by analyzing and refining them according to best practices in technical writing. It also incorporates Microsoft and OpenAI’s latest security features to help ensure data security.
• User control and customization: Users have the final say over the AI-generated content, with options to pick, edit, and refine outputs as per their specific needs.

Copilot4DevOps Plus is available as an add-on with Modern Requirements4DevOps or as a standalone in the Azure and Visual Studio Marketplaces.

Dynatrace

The Dynatrace platform delivers AI-enhanced cloud observability, security, and overall operational efficiency for global enterprises across all industries. With Davis® AI copilot, Dynatrace combined its predictive and causal capabilities and generative AI, built with Azure OpenAI, to bring Dynatrace Davis® hypermodal AI to market. This boosts the technical capabilities of IT teams by simplifying complex processes, enabling businesses to focus more on innovation and less on operational management.

Key features include:

• Davis® AI Engine: This core component leverages predictive, causal, and generative AI to provide deep insights and actionable recommendations. It automates tasks like anomaly detection, root cause analysis, and workflow automation, significantly reducing the manual effort required in managing complex IT environments.
• Predictive operations: The platform predicts potential issues before they impact operations using AI to forecast and automate responses, thereby ensuring reliability and proactive management of IT systems.
• Intelligent observability: Dynatrace uses AI to analyze real-time data across applications, services, and infrastructure. This helps in pinpointing issues quickly and accurately, which is crucial for maintaining optimal operational performance.
• Automation and integration: The platform’s automation capabilities extend to auto-discovery, auto-instrumentation, and auto-baselining, ensuring comprehensive coverage and real-time, dynamic responses to changes within the IT landscape.
• Azure native software as a service (SaaS): Azure Native Dynatrace Service seamlessly provides deep cloud observability, advanced AI for IT operations (AIOps), and continuous runtime application security capabilities native to all Azure customers empowered with Azure OpenAI generative capabilities

Intellect Design

The iGTB Copilot helps banking professionals generate insights and provide cross-sell assistance in commercial and corporate banking. It leverages generative AI to streamline operations and client interactions, allowing relationship managers to spend less time on manual data analysis and more on strategic client engagement. Here are the key functionalities:

• Comprehensive payment analysis: It enables users to perform detailed analyses of historical payment data, helping to identify trends and patterns without the need for any programming skills. It also helps in identifying delayed payments.
• Visual data summarization: The iGTB Copilot can automatically transform complex data into easily understandable visual graphics and provide insights and suggested actions.
• The iGTB Copilot, composed on the Purple fabric of eMACH.ai, is powered by Azure OpenAI, GPT-4 Turbo model, and other Azure infrastructure services.

Datamatics

Datamatics Copilot for Partner Onboarding is integrated with Microsoft Teams and leverages Microsoft Copilot, Microsoft Teams bot framework, and Azure OpenAI technologies. The application is designed to streamline the onboarding of vendors, business partners, freight forwarders, and employees across different geographies, making what is traditionally a complex and tedious process much more efficient.

Key functionalities include:

• Natural language querying: Users can query the status of onboarding processes and receive updates using conversational language.
• Automation and integration: The Copilot automates the creation of partner records and integrates seamlessly with other business systems for efficient data management.
• Real-time updates and communication: Enables prompt communication with partners about their onboarding status, including rejections, directly from Teams.
• Document management: Maintains and enforces compliance by specifying required documents for each country, ensuring partners submit the correct documents.

MiHCM

MiHCM SmartAssist is an AI-powered HR copilot designed to streamline HR processes. This tool is part of the MiHCM platform and offers a range of functionalities and customizations that simplify various HR tasks.

Key features include:

• Document generation: SmartAssist, built on top of Azure with services, including Azure OpenAI, Azure AI Search, Azure App Service, and Azure SQL Database, and leveraging Microsoft’s Copilot framework, can quickly generate employee letters with just a few keystrokes. It ensures that these documents are personalized by dynamically incorporating employee data.
• Job description creation: It automatically generates job descriptions that reflect the company’s unique voice and tone, including key performance indicators (KPIs), qualifications, and experience requirements.
• Customization capabilities: Users can easily adjust the content generated by SmartAssist, ensuring the output meets their specific needs.
• Data analysis and reporting: SmartAssist leverages employee data to analyze and calculate statistics, generate reports, and provide information at high speeds, enabling business leaders to make informed decisions quickly. This tool can answer high-level questions, going beyond mere facts and figures to provide valuable insight quickly. Information that would take days to gather can now be analyzed and provided in seconds.

Next steps to adopt AI and deploy copilots

• Check out our digital session at Microsoft Build 2024, that discusses enabling independent software vendors (ISVs) to transform industries in the age of copilots.
• Assess the drivers of AI success so you can realize meaningful business impact with AI.
• Learn how to power your AI transformation with Microsoft.
• Learn more about creating generative AI experiences with Microsoft Cloud across many Microsoft solutions.
• Envision boosted creativity and work productivity with Copilot for Microsoft 365 and learn how to extend it.
• Start using GitHub Copilot and Microsoft Copilot for Sales, now generally available.
• Learn how to build safety and responsibility into your AI journey from the start.
• Learn more about the featured ISVs: TomTom, Modern Requirements, Dynatrace, Intellect Design, Datamatics, and MiHCM.

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