Microsoft Cloud for Financial Services

Unlock business value and deepen customer relationships in the era of AI.

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Microsoft partners at Money20/20 USA 

Microsoft was proud to showcase powerful partnerships at Money20/20 USA, featuring many partner solutions driving AI transformation in the financial services industry.  

This included a suite of compelling demos from Microsoft partners including Temenos, Accenture-Avanade, Infosys, Backbase, Symphony AI, and Zafin. Accenture-Avanade demonstrated their Relationship Manager agent, which can improve relationship management across sales and services by freeing up capacity and enhancing client interaction quality. Additionally, Infosys’s Smart Agent and Smart Bank Assist showcased improvements to banking experiences for both employees and customers.  

Microsoft partners, including Cognizant, EY, Intellect Global Transaction Banking (iGTB), Personetics, D-iD, Integrate AI, and others, participated in theater sessions at the Microsoft booth. They presented their thought leadership around the most compelling AI-enabled use cases and deployment methods within banking and financial services. Additionally, Microsoft-sponsored panels with NVIDIA and BNY uncovered practical tips and considerations for scaling and deploying the latest AI technologies, further positioning Microsoft partners as thought leaders in the AI space. 

These collaborations reflect the Microsoft commitment to empowering partners to drive impactful, AI-powered solutions that help customers achieve their business goals and transform the future of financial services. 

Partners leading the way in delivering real-world AI value for financial services  

Taking a page from our Money20/20 USA presence, we’d like to share compelling examples where our partners are using AI to transform the banking experience, empower employees, help manage risk and compliance, and modernize core banking. These partnerships are not just exploring the possibilities of AI—they’re delivering concrete, measurable outcomes in the financial services space today.  

Transforming the banking experience 

Partners are transforming the banking experience by unlocking opportunities to enhance customer engagement. Backbase is delivering more compelling customer experiences around omni-channel for banking and wealth management based on their Engagement Banking Platform powered by Microsoft Azure AI. Capgemini, the Microsoft Global Financial Services Partner of the Year, has also driven AI innovation on the Microsoft platform, improving productivity and elevating the customer experience at financial services organizations worldwide.

“Capgemini and Microsoft have collaborated on enhancing business processes with Copilot Studio and Azure OpenAI Service, helping banks and insurers better serve their customers. For instance, Capgemini recently helped a major Global bank streamline and accelerate its customer onboarding process with Microsoft Intelligent Document Processing, using AI Builder for structured documents and Azure OpenAI Service for unstructured documents. These technologies have saved an enormous amount of time developing impactful solutions for our customers.”

Vivek Desai, VP and Global Head, Microsoft CoE for Financial Services.

Additionally, global financial services solutions provider, VeriPark, is advancing custom agents that span 40 use cases across corporate and retail banking. 

 “[Collaboration] allows us to deliver cutting-edge AI solutions that not only enhance operational efficiency but also empower banks to provide personalized, real-time services to their clients.”

Özkan Erener, CEO, Veripark 

Empowering employees 

There are also meaningful opportunities for AI to empower banking employees to be more effective trusted advisors to their customers. Using Microsoft Fabric and Copilot, Finastra’s Assist.AI, powered by Azure OpenAI, is boosting trade finance employee productivity with intelligent features that enable users to better prioritize and more efficiently complete everyday lending tasks. In addition, Tata Consulting Services (TCS) is modernizing how they engage with customers via an agent designed to optimize communication between banks and their users across all customer engagement channels. 

Managing risk and compliance 

When it comes to mitigating risk and crime, partners are delivering new intelligent approaches. ASC is providing institutions with more decision-making power around managing fraud and risk, while SymphonyAI is consolidating enterprise-wide risk and compliance across their Sensa Investigation hub solution, powered by Microsoft Azure and Azure Open AI. Additionally, partners like Holistic AI are helping customers such as Mapfre identify and mitigate risks associated with AI, while harnessing their data to ensure transparency, fairness, and compliance.  

Modernizing core systems 

Microsoft partners are also using AI in the mission-critical task of modernizing payments and core banking for greater efficiency, transparency, and high-value outcomes such as unlocking new revenue streams, reducing operational costs, and enhancing customer satisfaction. Temenos is delivering banking-specific solutions to provide agility, security, and innovation—to help banking customers reduce operational costs and uphold responsible AI standards via their commitment to explainability, secure operations, and safe deployment practices. Zafin advanced their leading software-as-a-service transformation and modernization platform for banks with Azure AI; this includes their de-risked implementation process that generates a 50% reduction in time to market¹. 

“The introduction of generative AI and Microsoft Fabric from a data standpoint are crucial…”

Chris Dickin, Executive Vice President, Zafin 

Additionally, the collaboration among Microsoft, our partner Quantexa, and European bank Novo Banco has delivered advanced banking data estate modernization in the era of AI. 

Learn more about financial services solutions from Microsoft 

Whether you joined us in person at Money20/20 to see the latest AI innovations from Microsoft and our partners, or are just now discovering the difference our technologies and partners are making in the industry, we invite you to collaborate with us on your own transformative AI experiences. 

• Learn more about Microsoft solutions in the financial services industry and our work with key partners by visiting Microsoft Cloud for Financial Services.  
• Learn how our partners are delivering industry-specific solutions faster with Microsoft Industry Clouds. 
• Visit our Solutions Partner learning path (which includes Microsoft Learn documentation, a playbook, and FAQs), and explore related financial services stories in our financial services industry blog.

¹Zafin launches Zafin IO and Zafin Data Fabric, a new offering to accelerate banking transformationThis offering will simplify integration processes, cut core modernization risks to support uninterrupted banking transformation, all while breaking down data silos and unlocking the power of banks’ first-party data – Zafin

The post Beyond Money20/20 USA: Microsoft partners redefining financial services appeared first on Microsoft Industry Blogs.

Microsoft for telecommunications

Accelerate telco transformation in the era of AI.

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But when we talk about “customers,” what do we really mean? Traditionally, it’s the subscriber, who interacts with telecom services daily. However, the reality is more complex. Telecoms must serve a dual audience: not only these external customers, but also their internal customers—their workforce and operational teams, whose efficiency and satisfaction are crucial for delivering seamless customer service. This dual focus reshapes how telecoms must approach innovation and transformation, making AI an important enabler for both external engagement and internal efficiency. 

AI-powered customer engagement and personalization 

When enhancing customer experience, it’s about delivering consistently excellent service at every touchpoint, including self-service systems and contact centers. Modern customers expect their telecom providers to understand and anticipate their needs, resolve issues quickly, and offer personalized solutions. Failing to meet these expectations can result in customer churn and lost opportunities. 

To meet these evolving demands, telecoms are increasingly partnering with technology providers to develop and implement advanced AI solutions that elevate customer engagement and operational efficiency. By using AI and cloud-based platforms, telecoms can create personalized, real-time responses and predictive support systems that align with customer expectations. This collaboration not only improves customer experience but also streamlines internal processes, enabling telecoms to adapt quickly in a competitive landscape. 

Telecoms deploy AI customer service solutions

A prime example of telecoms using AI to meet these demands is Vodafone’s AI chatbot, TOBi, showcased in a recent webinar². TOBi handles more than 45 million interactions per month³ across multiple languages, significantly reducing wait times and improving customer satisfaction by providing real-time, accurate responses. This capability is powered by Microsoft Azure, allowing Vodafone to efficiently scale support across 13 markets⁴. 

To fit the unique needs of telecom operators, Amdocs and Microsoft came together to create the Customer Engagement Platform, integrating advanced AI technologies and built-in capabilities, enriched with telecom-specific data. This platform integrates seamlessly with pre-sales, customer support, and beyond. For example, PLDT is partnering with Amdocs for digital transformation, leveraging real-time data from various touchpoints, such as billing and network usage to deliver highly personalized services.⁵ With the modular design of the Customer Engagement Platform, CSPs like PLDT can quickly deploy new services or updates, reducing resolution times, increasing agent productivity, and enhancing the overall customer experience, ensuring consistent and seamless interactions that enhance customer loyalty. 

Optimizing delivery with more autonomous agents

Additionally, Microsoft Dynamics 365 has introduced autonomous agents that further extend these capabilities, helping telecom companies optimize service delivery. The Customer Intent Agent dynamically identifies emerging customer needs by analyzing past and current interactions, autonomously updating knowledge libraries, and delivering contextually relevant solutions. By using Microsoft data security and AI best practices, telecoms can scale their customer care operations while maintaining competitive advantages. 

These AI-powered solutions help to ensure telecom providers can rapidly adapt to customer needs, driving satisfaction, loyalty, and retention. 

AI as the assistant for employees 

Just as customers demand excellence, the needs of employees and teams such as customer service agents, field technicians, and network engineers are a priority. AI technologies are important for streamlining workflows, surfacing actionable insights in real time, and automating routine tasks, enabling employees to focus on high-value activities and innovate within their roles. 

Applying GenAI to help address customer issues 

To illustrate, Vodafone’s integration of Microsoft Azure AI acts as an assistant for agents, automating repetitive tasks and providing insights that support complex customer interactions. By automating routine processes, Vodafone has successfully increased employee engagement and productivity, leading to an overall improvement in customer care quality. 

Similarly, the Amdocs and Microsoft Customer Engagement Platform⁶ enhances the employee experience by incorporating Microsoft Teams and Office tools. This integration equips telecom agents with real-time insights and predictive analytics, enabling them to address customer issues effectively and personalize support. The platform’s modular AI capabilities streamline workflows by automating routine interactions and consolidating multiple systems and data sources into a comprehensive 360-degree customer view. This empowers agents to make informed decisions quickly, enhancing both customer interactions and employee productivity. 

Amdocs’ low-code environment also empowers telecoms to rapidly develop and deploy virtual agents and process automation tools. These technologies assist non-technical employees in resolving customer queries efficiently while optimizing back-office operations such as billing and order management. This approach not only enhances productivity but also increases agent empowerment and engagement by allowing them to focus on more complex, high-value tasks, ultimately improving overall service quality. 

New agents to enhance the employee experience

New agents, such as Case Management Agent, further enhance these scenarios. By automating key tasks throughout the case lifecycle, from creation to resolution and follow-up, the agent reduces handle times, equipping agents with the insights needed for complex customer interactions. 

Both Amdocs and Vodafone demonstrate how Microsoft AI technology empowers telecom employees, streamlining operations and increasing efficiency by automating routine tasks and providing real-time insights. This AI-powered approach allows teams to focus on higher-value tasks that elevate service quality. 

AI as a catalyst for telecom innovation 

Amdocs and Vodafone demonstrate how AI enhances, rather than replaces, the human element in customer service. Technology is positioned as an assistant for agents, supporting them in managing routine tasks so they can engage in more meaningful, complex interactions. This approach helps telecoms provide more value-driven customer service while maintaining the human touch crucial for building customer relationships. 

AI’s transformative power extends beyond customer support centers. AI can support field services by optimizing routing, dispatch schedules, and resource allocation based on real-time data. This proactive use of AI minimizes downtime, optimizes field service operations, and further elevates customer experience. Additionally, Vodafone’s partnership with Microsoft uses AI to support neurodiverse staff and optimize network management, driving efficiency and personalized service. 

The path forward 

The future of customer care in telecom is deeply connected with AI, as demonstrated by Vodafone and Amdocs. Investing in AI leads to higher employee satisfaction, sustainable customer retention and growth, as well as ongoing innovation in a competitive landscape. As the telecommunications industry continues to evolve, embracing AI is important. Microsoft’s innovative solutions and strategic partnerships are designed to empower telecom companies to navigate this transformation successfully.  

By using AI, telecoms enhance customer experiences, drive operational efficiency, and create unique service moments. Embracing modernization of networks and the integration of real-time data analytics further position telecoms to lead in the digital age. Together, we can improve customer experience, unlock new revenue streams, and help to ensure long-term success in a rapidly changing landscape.

¹CSPs moving ahead with GenAI for cost reduction and efficiency gains. Omdia, Dec 2023

^2,3Transforming Customer Care: Vodafone’s AI Journey and Vision for the Future

⁴Magherita Della Valle, LinkedIn, Vodaphone Insights

⁵PLDT Selects Amdocs to Digitally Transform its Network Operations for Greater Agility and Enhanced Customer Experience | AMDOCS

⁶Amdocs and Microsoft Customer Engagement Platform

The post AI-powered customer care elevates customer satisfaction  appeared first on Microsoft Industry Blogs.

Consider, for example, that Americans who live past the age of 70 can expect on average to spend $172,000 for long-term care over their lifetimes.¹ But most families (as many as 83%²) say it would be impossible or very difficult to afford $60,000 for annual in-home or assisted living care expenses.

Life and health insurance companies are working to help bridge this ever-widening gap with long-term care insurance (LTCI). And thanks to a broad range of new innovations enabled by AI, Microsoft and our partners are helping to improve LTCI for policyholders and insurers alike. This is part of our vision for intelligent insurance and our work with Microsoft Cloud for Financial Services. 

In this case, helping to make long-term care more accessible and affordable is good not just for enhancing societal well-being and reducing the strain on public resources, but also for the viability of a critical insurance product.

The unique challenges of long-term care insurance

LTCI insures people for a very costly circumstance that is very likely to occur.

About 70% of seniors will require long-term care at some point in their lives,³ and Americans spend more than $471 billion annually for long-term care.⁴ Yet Medicaid covers only 42% of long-term costs. LTCI aims to address a significant portion of long-term care costs by covering a range of services for people who need assistance with daily living activities—for example, bathing, dressing, and eating—over an extended period, often provided at home.

Despite the prevalence and urgency of the need, however, LTCI has proven challenging for insurers. Rising healthcare costs and higher-than-expected claims have created unforeseen financial pressures. People are living longer, increasing the likelihood of needing to use LTCI, and fewer customers than expected are letting their policies lapse. For insurers, this results in profitability challenges and uncertainty, while customers face higher premiums, and thus reduced access.

How AI can help improve LTCI profitability and growth

The success of insurance companies in addressing the growing need for LTCI will depend on a variety of factors, including education, awareness, and the efficiency and effectiveness of regulation. Above all, technology holds the key for transformation in profitability and growth.

We are seeing tangible results in AI innovation with our insurance customers worldwide that have direct relevance for LTCI providers. These potential benefits are prompting many insurers to accelerate their cloud migration and data management investments—a transition that is key to the LTCI sector, which lags other insurance segments. With the scale, security, and resilience of the Microsoft Cloud combined with the advanced data and analytics capabilities of Microsoft Fabric and the AI development opportunities enabled by Azure AI Studio, insurance companies can innovate rapidly and confidently to meet their specific needs.

The future of insurance in the era of AI

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Here are some of the important benefits that insurers can apply to their LTCI offerings.

Enhance underwriting and claims management

AI can streamline underwriting and claims processing in ways that improve both accuracy and efficiency. One important area of focus is straight-through processing (STP)—the automation of an entire workflow, from the initial data entry to the final decision, without the need for human intervention. STP helps to reduce delays, minimize errors, and free up valuable human resources.

In the underwriting process, AI helps enable STP for tasks such as analyzing historical data, assessing risk factors, and predicting the likelihood of claims, which helps underwriters make more informed decisions and reduces the time required for manual reviews. It can also handle a larger volume of applications without a corresponding increase in resources.

In claims processing, STP can automate the assessment and triage of claims—for example, by quickly extracting and analyzing information from a wide range of documents, including medical records, policy applications, and claims forms. Many insurers have long used optical character recognition (OCR) technology to digitize these types of documents. But the addition of generative AI supercharges how they can be understood, evaluated, and acted upon.

Automate contact center experiences

With generative AI’s natural language processing and content creation capabilities, insurers can optimize contact center operations in ways that help both the customer and the company.

AI-enabled copilots and virtual assistants can handle larger volumes of routine inquiries, helping agents and customer service representatives provide faster, more accurate responses to policyholders’ questions about coverage, claims status, and more. For example, John Hancock implemented a new AI solution to provide support for common customer issues and questions, which helps call center representatives focus their efforts and expertise on the most complex cases, with better customer experiences and reduced wait times.

Automated systems can understand and respond to customer inquiries in a conversational way, and even authenticate caller identities with voice biometrics, streamlining the identification process and enhancing security. For LTCI, AI can enable corresponding benefits through more efficient operations, better resource allocation, and enhanced customer experiences.

Prevent fraud, waste, and abuse

In the realm of fraud detection, advanced analytics and AI-powered tools can analyze vast amounts of data from healthcare vendor invoices to identify patterns and anomalies indicative of fraudulent activities in a timely manner. With better insights, insurers can proactively detect and prevent fraud, helping ensure that legitimate claims are processed swiftly while minimizing financial losses.

AI can also help insurers identify unusual patterns or anomalies that could indicate fraudulent or wasteful activities, such as flagging a particular facility if it consistently submits higher-than-average claims for certain treatments. Analyzing historical data can also help inform insurers to create more robust, data-driven processes to determine which facilities to audit or to benchmark best-in-class operators.

Expedite regulatory, contracting, and auditing activities

LTCI is inundated with regulatory, contracting, and auditing activities, many of which rely on cumbersome manual processes. AI can improve the efficiency of many of these workflows while also improving accuracy, turn-around times, and regulatory compliance. Data validation, risk assessment, and regulatory monitoring can all benefit. Moreover, AI’s predictive analytics can spot potential compliance issues, and its enhanced reporting capabilities can aid strategic decision-making.

Advancing LTCI with AI and Microsoft

We believe that with focused, creative innovation with AI, LTCI providers and their customers can look forward to a bright future in which more people can live with dignity and financial security in their senior years, thanks to high-quality, robust insurance products and services. We are excited to work with industry and our global partner ecosystem to strengthen LTCI, in line with Microsoft’s responsible AI principles and our Secure Future Initiative. 

To learn more about all our solutions, visit our Microsoft Cloud for Financial Services website.

¹AARP, “Long-Term Care Costs May Double to $5.6 Trillion by 2047,” March 2018.

²KFF, “The Affordability of Long-Term Care and Support Services: Findings from a KFF Survey,” November 2023.

³Morningstar, “100 Must-Know Statistics About Long-Term Care: 2023 Edition,” March 2023.

⁴A Place for Mom, “Long-Term Care Statistics,” September 2023.

The post How AI is improving long-term care insurance for insurers and customers alike 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.

Digital transformation is essential for a resilient, durable, and sustainable mining sector. Geopolitical volatility and trade uncertainties are disrupting supply chains, while the industry grapples with the challenges of meeting the soaring demand for minerals essential for the energy transition. 

Existing deposits are being exhausted and new deposits are increasingly more difficult and expensive to discover. In 2015, McKinsey & Company reported that worldwide mining operations were 28% less productive than they were a decade prior, even after adjusting for declining ore grades.² Nearly a decade later, the shortage now impacts the availability of metals creating a potential risk for a near-term supply shortfall, particularly for copper, lithium, and cobalt vital to the energy transition. There is an expected supply deficit in critical minerals like copper with a potential shortfall of 9.9 million tons by 2035.³ 

The mining industry also faces a chronic labor shortage which adds even more to its challenges, with 86% of mining executives finding it increasingly difficult to recruit and retain necessary talent.⁴ Amidst these complexities, mining companies are striving to balance productivity and profitability with purpose using cloud-based platforms, the Internet of Things (IoT), mixed reality, and more recently, generative AI.  

Microsoft for Energy and Resources

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Accelerating digital transformation

In the December 2023 blog, I discussed how mining companies are adopting digital technologies to enable business agility, drive efficiency, and accelerate innovation across the entire mining value chain, from exploration and extraction to processing and transportation. While these efforts have traditionally centered around specific business outcomes, current trends emphasize broader goals such as corporate environmental, social, and governance (ESG) targets and the transition to net-zero emissions. 

Meeting these goals requires a strong data foundation, digital effectiveness, and digital maturity. Transformation starts with technology-savvy leaders who have a grounding in AI and a focus on sustainability. With a vision informed by a clear understanding of their organization’s challenges and opportunities, effective leaders can take a leap forward on their innovation roadmap with solutions like Microsoft Intelligent Data Platform, which provides a single, flexible platform for databases, analytics, AI, and data governance.  

Digital maturity deepens with an empowered, skilled workforce that harnesses AI to make informed decisions and streamline repetitive tasks, gaining more time for value-added activities. For example, in my last blog, I shared how Microsoft Copilot for Microsoft 365 in Microsoft Dynamics 365 Guides combines generative AI with mixed reality to help frontline workers in industrial settings complete complex tasks and resolve problems faster for minimal downtime and accelerated learning. 

Exploring innovation with a future-ready mindset 

At Microsoft, our enduring mission is to “empower every person and organization on the planet to achieve more.” We are privileged to work with a partner ecosystem that shares our vision.  

Digital innovation that stays relevant over time integrates people, processes, technology, and information. Multinational Japanese firm Asahi Kasei Group and ZEAL Corporation showcased that approach by implementing a data management platform based on Microsoft Azure Data Factory, Microsoft Purview, and Microsoft Azure Synapse Analytics. The platform unifies 1,200 systems across multiple diverse operations such chemicals, healthcare, electronics, construction, materials, services, and engineering. By eliminating data silos, the team can gain new insights that unlock business advantages.

Siemens is another great example of enabling people to achieve more. To empower employees, the company created an AI-powered collaboration app based on Microsoft Azure OpenAI Service and Microsoft Teams. Siemens aimed to enhance innovation, efficiency, and problem-solving agility by connecting field and shop floor workers with operations and engineering teams. Now, frontline workers who find problems in the design and manufacturing process can easily connect with engineers to resolve them. 

Employees can receive notifications, create problem reports, and collaborate on tasks on any device. The app provides preconfigured industrial machinery solutions and accelerates knowledge-sharing with an AI-powered natural language interface. For instance, employees can report issues in their own language, which is automatically translated into a common language. 

In my final example, Schieder Electric wanted to speed innovation for key goals such as reducing carbon emissions. With a vast portfolio of connected devices, solutions, and services, AI has become essential for generating data-driven insights and actions The company is using multiple AI services to fast-track innovation, including Microsoft Copilot, Microsoft Cloud for Manufacturing, Azure OpenAI, and Azure Machine Learning. Schneider Electric is using Copilot to automate routine tasks and to offer intelligent code suggestions that streamline programmable logic controller (PLC) programming. The company has also created bots to help with customer service and financial analysis. 

Creating durable innovation for a sustainable future 

Digital transformation can be a long journey, and the pressing issues of today can sometimes overshadow our efforts toward growth and innovation. For durable innovation, we incorporate the McKinsey Three Horizons Model into our digital transformation roadmaps. 

The model provides a structured approach that miners can use to allocate resources effectively, balancing immediate business needs with sustained innovation for future success. Organizations are encouraged to explore new markets and invest in business models, products, and technologies that align innovation programs with future challenges and growth opportunities. As a framework for strategic innovation and growth, Three Horizons Model can support miners during times of change, disruption, and uncertainty.   

In addition to innovation initiatives, we consider critical aspects such as user adoption, change management, change fatigue, organizational capabilities, culture transformation, workforce reskilling, and governance. These considerations are vital for futureproofing the mining enterprise and sustaining digital and AI innovation. 

How Microsoft can help

Digital transformation and AI adoption are poised to revolutionize the mining industry in the next decade and beyond. Microsoft technologies are already making a significant impact, with improvements in safety, productivity, profitability, safety, health, and environmental performance. From clarifying your vision for innovation and identifying top challenges to creating your solution roadmap, a disciplined approach is crucial for continuing this momentum. 

The digital sustainable mine of the future integrates physical, digital, and sustainable elements with information, innovation, and human ingenuity. The adaptive, resilient, forward-thinking mine offers a customizable reference model and roadmap to help mining organizations achieve their vision for the future. 

That vision isn’t just about the outcome, or business impact—it’s about investing in the processes and technologies that enable the mining industry to adapt to change and help us all accelerate toward a sustainable tomorrow.  

Learn more about Microsoft solutions

• Microsoft for Energy and Resources  
• Microsoft Industry Blogs: Energy and Resources
• Microsoft AI solutions  
• Microsoft Azure AI Services  
• Microsoft Intelligent Data Platform

¹Mining’s top ten ESG trends for 2024, Mining.com.

²Productivity in mining operations: Reversing the downward trend, McKinsey & Company.

³Tracking the trends 2024, Deloitte Global.

⁴Has mining lost its luster? Why talent is moving elsewhere and how to bring them back, McKinsey & Company.

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They decided to migrate their 10-year-old architecture and technology stack to a cloud-based solution to support their long-term goals and operate more efficiently. The question was how to make the move while also keeping the power on.  

At Microsoft for Government, we work with organizations and agencies around the world to help solve these kinds of challenges. We help each organization navigate their unique requirements and chart a path that works best for them, balancing the promise of AI and cloud native applications with the need to be more cost efficient, secure, and compliant.  

For Energinet, the solution was to build a new digital operating system based on Microsoft Azure, which is improving efficiency in automating energy balancing processes, lowering costs, and resolving issues in 15 minutes that previously took an hour. Modernizing helped them meet their near-term requirements, and it positioned them to remain agile and open to change as opportunities evolve.  

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Migrate to innovate—the benefits of modernization

In many government organizations, the migration to cloud computing has long been mitigated by important concerns, including cost, security, and a need to maximize legacy systems. As cloud technology has matured, however, the barriers to adoption have declined as the price of inaction has risen.  

With the promise of AI to deliver new efficiencies and opportunities for service improvements, cloud migration is now clearly the best path forward, provided it is done in ways that meet an organization’s unique requirements.  

For government organization, the advantages of cloud computing are compelling, and easier to realize than before. Governments that choose to migrate to Azure are realizing important benefits in many areas of their greatest concerns—among them: 

• Performance and resilience: Azure enables businesses to scale their operations globally with ease, with purpose-built infrastructure, dynamic compute capacity, scalable storage, and real-time disaster-recovery options. Governments such as the State of Alaska are migrating to Azure to achieve their vision of becoming digital public service innovators. To expand access to secure services, Alaska migrated 700 applications and one-third of its infrastructure in just three months. They not only achieved better resilience, cost efficiency, and security, but with the state’s vast geography and often isolated communities, the migration also sparked a cultural shift by bringing agencies together and unlocking unexpected value. 

• Security: To counter the expanding cybersecurity threat facing governments, Azure is supported by more than 8,500 security experts, more than 100 compliance certifications, and a cloud-native application protection platform that spans the application and infrastructure stack. Microsoft plans to invest USD$20 billion in security in the next five years to continue our commitment to a safe future.¹ The importance of ensuring world-class security was a key factor in the decision by Qatar’s Ministry of Communications and Information Technology to digitize government operations with Azure. The ministry established information assurance measures and security programs that not only enhanced the government’s data security and operational efficiency, but also achieved $7.3 million in cost savings. 

• Hybrid and multi-cloud management: Azure supports hybrid, multi-cloud, and edge environments with Microsoft Azure Arc, a solution that allows governments to build applications and services with a consistent development, operations, and security model across deployments. This proved essential for the World Bank, which provides lending services in 189 developing countries around the world to help lift people out of poverty. They wanted to build applications and services that could extract insights from their SQL Server estate and multiple cloud infrastructure providers. Using Azure Arc, they streamlined their cloud migration journey, built new solutions, and gained unexpected efficiencies. 

• Cost savings: By migrating to Azure, customers can optimize costs and resources by consolidating solutions and choosing from a variety of consumption models and flexible migration approaches. For example, the Statistical Office of Republic of Serbia saved time and money by conducting the nation’s first-ever paperless census using a hybrid cloud solution, which reduced the time required to publish official results from 18 months to just six. The solution delivered faster data encoding and more accurate results, and the Statistical Office of Republic of Serbia was able to streamline maintenance while ensuring optimal security, real-time monitoring, and improved data quality.  

A 3-step approach to becoming AI-ready

Modernization, which provides for greater scale, efficiency, and flexibility, also positions an organization to explore the benefits of AI. Governments recognize the potential of AI to generate new cost efficiencies and to power new offerings in service delivery. In the near term, this is motivating many to accelerate their digital transformation journeys. 

Implementing a cloud migration strategy is an absolute prerequisite to adopting and innovating with AI in a government organization. The cloud provides the hyperscale performance required for generative AI functionality, and a modern data strategy not only consolidates disparate data systems but also ensures access control and data security.  

Cloud migration is a long-term process, and the journey is unique to every organization. Whatever the course, governments should remain mindful of the following three steps, which are key to becoming AI-ready in ways that are efficient, effective, and responsible. 

Step 1: Co-locate data and workloads in the cloud

Strategically placing applications, databases, and AI resources into the Microsoft Cloud ecosystem delivers exponential improvements in performance and prepares data and services to take advantage of new AI innovations.  

Step 2: Infuse Microsoft Azure OpenAI Service and copilot integrations

Once your data and applications are co-located, you are ready to take advantage of AI services such as Microsoft Copilot for Microsoft 365, which integrates generative AI into everyday productivity applications, and Azure OpenAI, which enables the development of customized copilots, plugins, integrated AI services, and much more.  

Step 3: Ensure secure and responsible AI

From the outset, AI innovation should be delivered with the highest standards for security, assurance, and trust. Beyond taking a leadership role in ensuring safe, secure, and trustworthy AI at a global level, Microsoft provides comprehensive guidance for governments to ensure secure and responsible AI in their efforts, such as the Microsoft Responsible AI Standard, and Microsoft responsible AI practices.   

Continue your modernization journey and become AI ready 

No matter where your government organization stands in its digital transformation, Microsoft and our network of global partners are ready to help you move forward. For more, please explore the following resources: 

• To learn how Microsoft is helping governments solve society’s biggest challenges, see our Microsoft in Government website.  

• For guidance, expert assistance, and resources to help move to Azure, visit Azure Migrate and Modernize and Azure Innovate.  

• To develop a cost management strategy when migrating or operating in the cloud, see Cloud Migration Cost Management Resources.  

¹Microsoft commits $20 billion to advance cybersecurity following meeting with President Biden, Windows Central.

The post Migrate to innovate: How governments are modernizing in advance of AI appeared first on Microsoft Industry Blogs.

It is a remarkable shift, which I and others in Microsoft for government have gauged over the past year as we’ve worked to help city governments solve their most important challenges through technology. 

At the SXSW 2024 conference, the Esri Infrastructure Management & GIS Conference, and in my recent meetings with city leaders from Canada, Finland, and the Netherlands, generative AI has been at the center of most conversations. This excitement is notable because cities are traditionally cautious about technology adoption for important reasons such as risk, privacy, security, and governance, and many are still working through their cloud migration journeys.  

The potential benefits of generative AI to improve operations and service delivery are too compelling for many cities to ignore. To cite just one example, the City of Kelowna in Canada launched an early AI initiative and is using cognitive search and conversational AI to deliver a 24-hour helpline for its 150,000 residents. Project leaders report that generative AI also enables them to automate and streamline internal processes around data entry and analysis, refactor legacy databases and code, and create new apps in minutes.  

This type of innovation has prompted other cities to explore AI innovation, beginning with creating an effective and actionable plan. 

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Success factors for AI adoption in city governments 

Every city is unique, with its own ambitions for the use of generative AI and its own set of requirements and technology considerations. In our work with cities, we have identified a set of success factors that are common across cities investing time and money in generative AI and are enjoying early success.  

1. Empower the workforce with effective upskilling  

Realizing the value of AI starts with the workforce. According to research conducted as part of Microsoft’s Public Sector Insights on Skilling, the lack of skilled workers is often the number one barrier to AI implementation among organizations worldwide.

The imperative to upskill the workforce is particularly important for cities, whose early use cases usually focus on employee productivity and the internal processes they manage. Well-trained and confident workers also help ensure the success of public-facing initiatives. Executive support is key. Workers are empowered when leadership gives them the direction and license to responsibly use AI tools within the context of their day-to-day work. 

To answer the skilling challenge, cities should invest in learning programs, building public-private upskilling partnerships, and giving people adequate time to gain skills and confidence. An ongoing learning experience platform, such as the one developed by Bank of Canada, can promote a culture of learning. Microsoft offers effective resources and strategies, including the Public Sector Center for Digital Skills, which provides specialized insights, guidance, and content, and Microsoft Learn, which offers customized training options. 

2. Build an AI-ready data strategy 

AI is only as good as the data that is made available to it. In city systems, data is often siloed or locked in spreadsheets or other static locations. A modern data strategy is one that integrates such diverse data sources, ensures data quality, establishes rules and processes for data access and management, and keeps data and systems secure.   

An excellent example of how a complete data strategy can deliver ongoing AI benefits is the Smart Qatar (TASMU) Program built by the State of Qatar. Essentially a service platform built on a common data model across multiple domains, TASMU will empower a broad array of AI applications that are expected to help contribute 2% to the nation’s gross domestic product (GDP).  

This sort of comprehensive data strategy is an important long-term goal, but cities should not wait to begin innovation on AI. Many cities are taking an incremental approach, leveraging the quality data they have in hand, with their existing cloud foundations and data governance standards to experiment with new AI use cases. A careful step-by-step approach will guide your data strategy. 

3. Establish frameworks for governance, compliance, and sovereignty  

Some city governments have been reluctant to use AI due to concerns about security, privacy, and compliance requirements. To address these concerns, cities should establish transparent frameworks for AI governance and assurance. The goal is to identify risks and goals associated with both externally facing and internally focused use cases and codify courses of action to ensure success.  

Ensuring the residency of data within strict geographic borders is a key requirement for many cities. This calls for a solution that can ensure the required level of control of sensitive data while still providing a hyperscale cloud environment for a huge number of applications. 

Microsoft offers guidance for cities to establish AI governance and enhance trust and privacy in AI innovation. For cities with strict data residency concerns, we also offer Microsoft Cloud for Sovereignty, which offers tailored cloud services to help build cloud-based workloads in compliance with specific security, policy, and regulatory requirements. 

Take the first steps in building an AI-empowered city  

For city leaders who want to advance their AI journeys, our experts and industry advisors can work with you to identify potential use cases for early innovation based on your specific goals, requirements, and environmental conditions.  

To learn more about how Microsoft can empower cities and government organizations with technology to help solve society’s biggest challenges, visit the Microsoft for government website, read our Microsoft for Government e-book, or get in touch with your Microsoft representative or technology partner.     

The post How Microsoft empowers city governments on the road to AI adoption appeared first on Microsoft Industry Blogs.

Manufacturing is one of the most data-intensive industries, as massive amounts of data are generated from sources such as sensors, machines, enterprise systems, and human interactions. However, most of this data remains siloed, unstructured, and underutilized, thereby limiting the potential for data-driven insights and innovation. To overcome this challenge, manufacturers need a unified data estate that can connect, enrich, and model data across information technology (IT) and operational technology (OT) systems—enabling easy access and analysis of data for every employee.  

We are announcing the private preview of manufacturing data solutions in Microsoft Fabric and copilot template for factory operations on Azure AI, under the Microsoft Cloud for Manufacturing. These solutions help manufacturers unify their OT and IT data estate and accelerate and scale data transformation for AI on Fabric, our end-to-end analytics software as a service (SaaS) based platform. The copilot template for factory operation on Azure AI helps manufacturers to create their own copilots for their frontline workers using their unified data. They can use natural language to work with the data and handle scenarios such as root-cause analysis, knowledge discovery, training, issue resolution, asset maintenance, and more.  

These solutions, alongside our partners supporting it, will be showcased live for the first time at Hannover Messe Industrial Conference 2024.  

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Manufacturing data solutions in Fabric 

Manufacturing data solutions in Fabric brings together OT data like factory sensor telemetry, and IT data like inventory data, into a unified data foundation in Fabric. The solution extends the value of the data by enriching it with the relevant context, following an industry standard International Society of Automation (ISA-95) information model. For example, the temperature reading of a production equipment at a specific time (OT data), is overlayed with all the information of the batch of material going through that machine, from the production order from your enterprise resource planning (ERP) system, or test result from your quality system (IT data). 

The solution ingests data from different factory sources ranging from the Internet of Things (IoT) devices to systems of records like manufacturing execution systems (MES), and more. The data is stored in Fabric for unification, enrichment, modeling, and aggregation. This unified data foundation provides a scalable and repeatable pattern to tackle all factory domain data projects—accelerating the pace of innovation, freeing up IT resources, and maximizing the value of current technology investments. 

Copilot template for factory operations on Azure AI 

Once the data is enriched and ready for AI, manufacturers can leverage the factory operations copilot template plugin to Azure OpenAI Service, augmented for complex manufacturing systems like MES. The copilot template validates results against the manufacturing data solutions through post processing to avoid hallucinations and provides responsible AI guardrails to ensure only relevant and safe responses are given within the manufacturing setting. The users, such as a Quality Engineer or Plant Manager, can use a custom interface, like a chatbot or a dashboard, to communicate with the data in natural language to obtain insights and make improvement decisions. 

To learn more about technical aspects of these solutions, review our deep dive technical blog.

Realizing the value of factory data with AI 

These solutions are already supporting leading manufacturers globally to tackle complex use cases like production monitoring, waste management, quality management, and worker enablement. 

Intertape Polymer Group increases production performance with factory data and generative AI  

Intertape Polymer Group (IPG) uses Sight Machine’s Manufacturing Data Platform to continuously transform data generated by its factory equipment into a robust data foundation for analyzing and modeling its machines, production processes, and finished products. IPG is now using Sight Machine’s Factory Copilot, a generative AI with an intuitive natural language chat interface, powered by the copilot template for factory operations on Azure AI. This tool facilitates the team’s ability to rapidly gather insights and direct work on production lines which previously operated like black boxes. Instead of working through manual spreadsheets and inaccessible data, all teammates—including production, engineering, procurement, and finance—have better information to drive decisions on products and processes throughout the plant, improving yield and reducing inventory levels.

“Our partnership with Sight Machine and Microsoft is ever evolving and continues to become more important to our daily operations within the plant, facilitating real time decisions on real time data.”

—Bill Bourgeous, Plant Manager for the IPG Tremonton, Utah facility 

Schaeffler, democratizing information access across their factory workforce

Schaeffler, a leading motion technology company, has embarked on a mission to democratize information access across their factory workforce. Employees can gain easy access to key metrics like scrap rates, yields (the proportion of usable or acceptable components), and energy usage over time using the chatbot. This will be vital to help drive cost and carbon reduction co-benefits.

“Artificial Intelligence, and in particular Generative AI, is already having an impact on the daily business at Schaeffler. Especially in the field of manufacturing and operations, the ongoing operationalization of AI solutions, combined with intensive training, enables us to optimize, rethink, and innovate the core of our company—our plants. As a leading motion technology company, Schaeffler has the ambition not only to participate but to proactively shape this ongoing transformation.”

—Stefan Soutschek, Vice President Digitalization and Operations IT, Schaeffler

Bridgestone is creating a unified factory data foundation to enhance product quality

Bridgestone is partnering with Avanade to confront production challenges head-on, focusing on critical issues related to production disruptions and scheduling inefficiencies, like yield loss, which can escalate into quality issues. As a private preview customer collaborating with Avanade, Bridgestone aims to harness the power of manufacturing data solutions in Fabric and the copilot template on Azure AI. Their goal is to implement a natural language query system that enables frontline workers, with different levels of experience, with insights that lead to faster issue resolution. The team is excited to establish a centralized system that efficiently gathers and presents critical information from various sources and facilitates informed decision-making and enhances operational agility across Bridgestone’s production ecosystem. 

“We are excited to accelerate our industrial transformation with AI in partnership with Avanade and Microsoft Cloud for Manufacturing, particularly we recognize the disruptive ​potential of generative AI, and true to our values, we want to be at the forefront of innovation equipping our front-line workers with powerful tools, like copilots, to optimize our operations.“

—Bart Kerhofs, Vice President of IT for Bridgestone, Europe, Middle East, and Africa

Microsoft Cloud for Manufacturing partner ecosystem 

These solutions are enabled by an ecosystem of partners with deep industry expertise. Systems integrators and software vendors enable factory data ingestion from different systems by building custom or proprietary connectors into Fabric—embedding the solution capabilities into their applications or building custom UI experiences for the copilot templates on Azure AI. We want to thank our private preview partners for supporting these solutions and our customers.

• Accenture and Avanade: Private preview implementation partners for manufacturing data solutions in Fabric and copilot template on Azure AI.
• Sight Machine: Manufacturing Data Platform and Factory Copilot on Microsoft Cloud for Manufacturing.
• Litmus Automation: Litmus connector.
• AVEVA: AVEVA Connect and AVEVA Data Hub on Microsoft Cloud for Manufacturing.
• Rockwell: Integration of Rockwell’s Plex Smart Manufacturing Platform with FactoryTalk DataMosaix and Microsoft Cloud for Manufacturing. 

To learn more about each of our partners, review the deep dive technical blog. 

Learn more at Hannover Messe 2024 

With manufacturing data solutions in Fabric and copilot template on Azure AI, manufacturers can better connect factory ecosystems, drive productivity, and enhance business operations using conversational assistants and accessible data analytics from the factory floor. To watch a live demonstration of these solutions, discover the additional capabilities of Microsoft Cloud for Manufacturing and our partners, and to engage with subject matter experts, join us at the Hannover Messe Industrial Fair 2024, in Hannover, Germany from April 22 to 26, 2024 in Hall 17 Stand G06. 

Explore Hannover Messe announcements and Microsoft AI solutions

• Read Azure IoT’s industrial transformation strategy on display at Hannover Messe 2024.
• Read Microsoft unveils AI features for manufacturers at Hannover Messe 2024.
• Build intelligent apps at enterprise scale with the Azure AI portfolio.
• Reshape how everyone accesses, manages, and acts on data with a single, AI-powered platform.
• Work smarter, be more productive, boost creativity, and stay connected to the people and things in your life with Microsoft Copilot.

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To address these challenges and help manufacturers work towards digital maturity, we are announcing manufacturing data solutions in Microsoft Fabric, and copilot template for factory operations on Azure AI, available in private preview. These solutions enable manufacturers to:

• Ingest and unify data directly from diverse sources across the factory ecosystem. 
• Standardize and enrich data according to the International Society of Automation (ISA-95) model for seamless interoperability.  
• Utilize custom copilots for querying data through conversational interfaces. 

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Optimize production with manufacturing data solutions in Microsoft Fabric

Manufacturing data solutions in Fabric allows users to maximize the value of factory data and uncover operational insights for production optimization. This is accomplished by unifying information technology (IT) and operational technology (OT) data into an open and secure data platform. Organizations can realize further benefits by getting manufacturing data ready for AI by enriching it with semantic context that follows an industry standard ISA-95 information model. 

Fabric enables customers to accelerate time to insight generation by unifying, enriching, and modeling manufacturing data in Fabric. The solution ingests data from a variety of sources such as factory-domain data from sensors, systems of record like manufacturing execution system (MES) and enterprise resource planning (ERP), and industrial automation applications. The data is then stored on Microsoft Fabric One Lake for unification, enrichment, modeling, and aggregation. This unified data provides a scalable and repeatable pattern to tackle all factory-domain data projects, accelerating the pace of innovation, freeing up IT resources, and maximizing the value of an organization’s technology investments. 

Customers can extract the full value of their factory data and existing manufacturing solutions landscape using manufacturing data solutions in Fabric. For example, a production supervisor conducting a root cause analysis to determine a correlation between material batches, machine utilization, and quality issues might spend weeks manually aggregating data from several systems and require IT support. With manufacturing data solutions in Fabric, the supervisor has quick access to contextualized data for analysis, completing it in hours instead of weeks. This saves valuable time and immediately provides insights that increase agility and innovation.  

Increase agility with copilot template for factory operations on Azure AI

Creating a unified data lake with manufacturing data solutions in Fabric is essential to optimize AI capabilities. Copilots can enhance responsiveness and streamline communication across teams and roles. We are building an industry-specific augmentation loop to help partners and customers use the Microsoft Copilot stack more quickly with out-of-the-box prompt templates, connectors, and skills all packaged as a standard plugin. Customers can then use natural language to get timely and accurate data from complex systems like MES, quality management system (QMS), and supply planning with minimal effort.  

With copilot template for factory operations on Azure AI, a production supervisor for example, can open a custom chatbot and quickly query the data in a conversational way and identify quality issues in minutes instead of hours. The copilot template is a managed application in the customer-tenant, offering organizations full visibility and control of their data. The template features the latest Microsoft technologies such as Azure AI models, Semantic Kernel, and Azure Cognitive Search, and is extended through the Microsoft third-party independent software vendor (ISV) ecosystem. 

Microsoft Cloud for Manufacturing Partner ecosystem

Microsoft’s partner ecosystem with its deep industry expertise extends Microsoft Cloud for Manufacturing offerings. Systems integrators and ISVs are enabling factory data ingestion from different systems by building custom or proprietary connectors into Fabric: embedding the solution capabilities into their applications or building custom UI experiences for the copilot templates on Azure AI. 

Accenture and Avanade—Manufacturing data solutions in Fabric and copilot template on Azure AI 

Empowering customers to unlock the full potential of their factory data, Accenture and Avanade collaborated on the development of the Avanade Manufacturing copilot, powered by manufacturing data solutions in Fabric, which facilitates innovation, operational efficiency, and data-driven decision-making. By leveraging data from various sources, such as MES, programmable logic controllers (PLCs), sensors, and ERP, the copilot enables seamless querying and generation of insights in natural language for factory workers.  

As leading global system integrators and trusted private preview implementation partners for Microsoft Cloud for Manufacturing, Accenture and Avanade are spearheading the delivery of manufacturing data solutions and copilot templates. With expertise in integrating key Microsoft technologies, like Fabric and Azure OpenAI Service, and collaborating across the broader ISV ecosystem, Accenture and Avanade stand at the forefront of driving digital transformation in the manufacturing sector. 

“Avanade Manufacturing copilot, powered by manufacturing data solutions in Microsoft Fabric, can help AI systems understand data from diverse OT-IT systems that manage complex manufacturing supply chains, processes, equipment, and product ranges in near real-time. With our graph-of-graphs approach to knowledge management and the open ISA-95 standard, we’re able to supercharge the ask-an-expert capabilities of Microsoft Copilot. This is vital in an era of labor and skills shortages, rising production targets, and the need to cut costs and carbon emissions.”

—Brendan Mislin, General Manager, Avanade Industry X

To learn more about Accenture and Avanade Manufacturing copilot offerings, visit their AppSource page. 

Sight Machine Manufacturing Data Platform and Factory CoPilot on Microsoft Cloud for Manufacturing

Sight Machine’s Manufacturing Data Platform (MDP) helps global manufacturers unlock the power of industrial data to increase profitability, productivity, and sustainability. Sight Machine makes it easy to integrate contextualized production data in Fabric. With its data and analytics tools, Sight Machine’s MDP enables companies to combine and analyze contextualized manufacturing data with financial, supply chain, ERP, and MES data. This allows for unprecedented levels of knowledge and enterprise-wide insight. Sight Machine’s Factory CoPilot leverages Microsoft factory operations copilot template on Azure AI to provide conversational querying of the data within the UI of the Factory CoPilot. This enables plant managers and quality engineers to interact with the data to uncover insights faster and accelerate issue resolution.  

“Until now, industrial companies have been unable to incorporate their manufacturing data as a full citizen of their data estates. With Sight Machine on Microsoft Cloud for Manufacturing, companies can optimize production scheduling globally, determine which equipment is best at fulfilling an order, know which lines are at highest risk of going down, see the status of orders, and determine when to re-route them to another facility. It has never been possible to do this in a truly data-driven way.”

—Jon Sobel, Chief Executive Officer and Co-Founder, Sight Machine 

Learn more about Sight Machine solutions on Microsoft Cloud for Manufacturing, visit the Azure Marketplace.

Litmus Automation connector

In the dynamic landscape of industrial operations, Litmus stands at the forefront of data management, offering an advanced DataOps platform that seamlessly operates at the edge. With the ability to swiftly extract, normalize, and model data along with metadata, Litmus Edge empowers enterprises with edge data expertise. Paired with manufacturing data solution in Fabric, this collaboration pioneers a transformative approach, enabling the establishment of a robust hybrid edge-to-cloud infrastructure. From streamlining real-time machine dashboards to facilitating advanced machine learning, the synergy between Litmus and manufacturing data solutions in Fabric unlocks unprecedented efficiency and innovation, seamlessly bridging the gap between edge and cloud.

To learn more about Litmus solutions on Microsoft Cloud for Manufacturing, visit the Azure Marketplace.

AVEVA Connect Industrial Intelligence Platform, integrated with Microsoft Cloud for Manufacturing

AVEVA is collaborating with Microsoft on extending AVEVA’s Industrial AI Assistant to showcase how generative AI enhances supply chain production planning and plant floor production. It helps with scheduling, improving operational efficiency, and decision making in plants and across the supply chain. Using AVEVA’s Industrial Intelligence Platform, CONNECT, and Microsoft Cloud for Manufacturing, AVEVA unifies and contextualizes production execution data and supply chain production planning data in Fabric. AVEVA’s Industrial AI Assistant provides a seamless conversational experience, through a copilot template on Azure AI, that empowers plant floor and supply chain employees with valuable insights to resolve issues and accelerate decision-making activities. 

CONNECT unifies an organization’s industrial ecosystem in a single, secure platform—helping users do more with industrial data, driving digital transformation in real time with powerful intelligence and robust insights. 

Users can easily access software as a service (SaaS) capability through CONNECT to create an industrial hybrid architecture that offers the robustness of on-premises industrial applications with the scale and accessibility of cloud. With CONNECT, companies can engineer smarter and operate better with an open and neutral industrial cloud platform. Organizations can promote sustainable growth by achieving transformation faster, reducing costs, and optimizing at scale. Lastly, manufacturers can connect their business to their ecosystem of partners and accelerate time to value using proven industrial expertise. 

Rockwell Automation’s Plex on Microsoft Cloud for Manufacturing

Rockwell is collaborating with Microsoft Cloud for Manufacturing to introduce natural language copilot experiences within Plex. These innovations aim to streamline quality issue resolution through corrective actions and root cause analysis.  

Corrective action teams often struggle with accessing the correct data and determining root cause. With today’s high workforce attrition, the ability to generate insights and share knowledge about a problem or process is also key. Leveraging Microsoft AI capabilities, Rockwell’s Plex Smart Manufacturing Platform will accelerate the resolution of customer complaints by swiftly identifying root causes and accessing critical data for corrective actions.  

Stay tuned as Rockwell and Microsoft drive innovation in quality management for manufacturing. 

“With the integration of Rockwell’s Plex Smart Manufacturing Platform with FactoryTalk DataMosaix and Microsoft Cloud for Manufacturing, customers will benefit from transformative AI tools that help drive productivity, safety, and quality.”

—Anthony Murphy, Vice President, Product Management

Learn more at Hannover Messe 2024

Discover more about manufacturing data solutions in Fabric during a live demonstration at Hanover Messe in April 2024.  

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The new AI opportunities for public finance  

Public finance organizations are generally well positioned to take advantage of AI’s ability to redefine their services, operations, and impacts on government. Those who have adopted the Microsoft Cloud and Microsoft productivity applications are benefiting from the fact that, over the past decade, and especially the last 18 months, Microsoft has been integrating AI capabilities throughout our offerings.  

Copilots—AI-driven software assistants—are delivering immediate opportunities for ingenuity among ground-level and operational employees, as seen in Microsoft Copilot for Microsoft 365, the new Microsoft Copilot for Finance, and Microsoft Bing. For business and IT leaders, copilots across Microsoft Power Platform, Dynamics 365, Security, and GitHub make it simple to unlock powerful new capabilities with embedded, low-code features. And in cases where advanced solutions are called for, Microsoft Azure OpenAI Service enables the development of customized solutions such as virtual assistants, chatbots, automated systems, and intelligent applications.  

Thanks to the broad range of these capabilities, public finance agencies can move quickly to redefine their role and leverage new opportunities. To make this vision a reality, we focus on AI innovation with three specific objectives in mind.  

1. Simplify taxpayer experience and revenue collection 

One great opportunity with AI is to make it easier for people and businesses to pay the right amounts of taxes and fees, in ways that are embedded into their lives. AI powered solutions for taxation, customs, and license and permit processes can be simple and sensible while providing the security and compliance benefits of the cloud. AI helps with managing data and fostering faster ways of information sharing across agencies—a challenge that by one estimate costs European Union governments more than 50 billion euros a year.¹ 

In this regard, AI can help in many ways, including: 

• Modernizing taxpayer services—New engagement models can proactively build data intelligence to improve revenue collection, while reducing the cost of compliance, increasing agility, and improving productivity. Taxpayers can enjoy seamless experiences fostering a greater sense of trust in agencies. This proved to be the case with Estonia’s Information System Authority, which created an AI assistant that grants people with access to secure information about vital government services in a matter of seconds as opposed to days. 
• Boosting employee productivity—Employees tend to be more effective with tools that minimize drudgery and help them focus on delivering results and finding solutions. User-friendly, interoperable, and automated processes foster better productivity, and AI enables new ways to help employees find the right information at the right time. A key factor in realizing this potential is upskilling the workforce, which is why the Bank of Canada implemented an ongoing training initiative based on Microsoft Learn that provides individualized learning pathways with online on-demand and instructor-led content.  

2. Drive informed budgeting for economic development 

Trillions of dollars are distributed by governments around the world to households, businesses, local authorities, and others for stimulus, recovery, and resilience plans.² This puts an enormous responsibility on budget and treasury agencies, which have the complex task of allocating public resources in ways that measurably impact economic development. These agencies require innovative, secure tools that enable them to allocate the right support to the right beneficiary at the right time. Done well, these solutions also enhance collaboration between government and the private sector, which ultimately fosters financial inclusion. 

To meet these challenges, AI can help by: 

• Modernizing budget planning and execution—Employees in budgeting agencies often deal with legacy systems that are insufficient for accurate forecasting and planning. AI can help with new tools that improve these processes, as well as automate budget distribution, deliver reports, and improve forecast precision. Low-code, AI-enhanced tools can accelerate the creation of powerful solutions. In Japan, for example, the Ministry of Economy, Trade and Industry slashed development timeframes from one year to as little as one month by adopting Microsoft Power Platform.  
• Boosting employee productivity—Treasury agencies have significant management responsibilities, and high demands to operate with accountability and transparency. Cloud and AI can empower teams to better manage liquidity, optimize debt management, and manage reserves and investments, while also being efficient and secure. Productivity at the United Kingdom Department for Environment, Food, and Rural Affairs improved dramatically with a new cloud solution to provide a customer portal, streamline business processes, and add real-time reporting. By automating claim entry, they processed more than 40% of their annual 250,000 payments in the first three months.  

3. Mitigate fraud and corruption in public finance 

Fraud and corruption are major problems that incur trillions of dollars in losses worldwide every year.³ AI can help public finance agencies reverse the trend by helping to spot activities that may signal fraud, evasion, or abuse of public funds. To do this, agencies need solutions that give them fast, accurate, and comprehensive analytics, with a 360-degree view of taxpayer profiles to make informed decisions. 

Examples of how AI can help mitigate fraud and corruption include: 

• Improving compliance and protecting against fraud and corruption—Public finance agencies need solutions to combat illegal activities while also safeguarding taxpayers, employees, and all their data. AI enables solutions that analyze data from traditionally siloed, disconnected sources to detect anomalies and derive insights in previously impossible ways, while inherently protecting to ensure security and regulatory compliance. SymphonyAI, an enterprise software company that employs AI to solve financial crime, recently launched a copilot for investigators that automatically collects, collates, and summarizes financial and third-party information. Early experience shows that it can improve investigator productivity by more than 60%.  
• Enabling modern risk management—Risk is often inherent for public finance agencies, so teams need effective, modern approaches to risk management. These solutions should deliver monitoring and reporting across organizations and agencies, ensuring that everyone has complete, appropriate access to information. A good example is an Electronic Invoice Anomaly Detector built jointly by Microsoft and the Inter-American Center of Tax Administrations (CIAT), which strengthens electronic invoicing and reduces fraud and evasion for tax administrators in its member and associate member countries worldwide. 

The essential role of responsible AI 

The promise of AI would be impossible without trust. That is why Microsoft has long been a leader in ensuring the development of responsible AI, with principles designed to put people first. We believe AI exists to enhance human capabilities, not replace them, and we are committed to empowering responsible AI practices that benefit the world at large.  

The Microsoft Responsible AI Standard defines product development requirements for Microsoft technologies, guided by the principles of fairness, inclusivity, reliability and safety, transparency, privacy and security, and accountability. We believe this holistic approach can help public finance agencies deliver actionable results for their communities, with a minimum of risk and unintended consequences.  

Empowering public finance agencies with data and AI

It is an exciting time to be in public finance. Connected systems driven by data and AI set the stage for governments to unlock new possibilities such as tax compliance by design, intelligent connected trade windows, digital currency, outcomes-based budgeting, and cyber and financial crime detection and prevention convergence.

To learn more about how Microsoft is helping public finance agencies to reignite economies and improve accountability with AI, visit Microsoft for Public Finance.

¹ Politico, “Billions of euros lost to poor tax data, EU watchdog says,” Bjarke Smith-Meyer, January 2021.

² OECD, Global Outlook on Financing for Sustainable Development 2021, November 2020.

³ United Nations, “Global Cost of Corruption at Least 5 Per Cent of World Gross Domestic Product, Secretary-General Tells Security Council, Citing World Economic Forum Data,” September 2018.

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