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

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The power of mobility copilots 

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

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

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

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

The latest mobility partner copilots 

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

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

Fleet operations copilot from Netstar 

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

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

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

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

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

Repair and maintenance copilot from KPIT  

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

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

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

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

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

Tools for building your own copilot 

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

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

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

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

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

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

Explore mobility solutions

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

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

In India, one of the world’s largest agricultural producers, the sector sustains over 43% of India’s workforce.¹ However, many Indian farmers face challenges due to limited access to crucial information and agronomic expertise. This gap can hamper their ability to access time-sensitive information, like changes in monsoon patterns, making it even more challenging to adapt to the rapidly growing demand for agricultural products. As India’s agricultural landscape evolves, leveraging generative AI not only supports the shift away from harmful pesticides and fertilizers, but it also helps farmers boost efficiency. 

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Copilots: Working toward sustainable change 

Azure Data Manager for Agriculture is a powerful tool designed to enhance agricultural practices by leveraging high-quality datasets and AI capabilities. This platform connects farm data from various sources, enabling organizations to develop innovative solutions that provide valuable insights into farming operations. With Microsoft copilot templates, organizations easily create custom copilots to seamlessly retrieve and analyze data in natural language—making it easier to gain actionable insights. Microsoft supports its customers and partners by offering comprehensive tools and resources, fostering collaboration, and driving innovation across the agricultural value chain. Microsoft is working closely with customers like ITC, a versatile Indian multi-business company, to optimize agricultural decision-making and promote sustainable farming practices. 

ITC is deeply committed to sustainability and the welfare of small holder farmers, and they have developed Krishi Mitra, aptly named “farming friend.” This agricultural super app, created using Microsoft’s copilot template, enables farmers to ask questions in their own language and uses generative AI plugins to provide answers on weather and agronomy. By incorporating natural language chat functionality powered by generative AI, Krishi Mitra offers tailored guidance on crop management, pest control, soil health, water conservation, and more. Additionally, Microsoft language localization tools enable the app to cater to a diverse linguistic audience, ensuring that farmers across various regions can access crucial farming information in their preferred language. 

Microsoft is working closely with partners like ITC to extend Azure Data Manager for Agriculture. Supporting farmers by providing AI-powered tools, Microsoft and its partners are working together to provide optimized agricultural decision-making. ITC plans to bring generative AI to over 100,000 farmers in India by end of 2024, with an anticipated user base of around 10 million by 2030. Plans include integrating the copilot with Azure Data Manager for Agriculture in subsequent phases, allowing for access to a wide range of additional data sources.

A streamlined development process using plugins 

The development process of Krishi Mitra was streamlined using orchestrated plugins, which access specific functionalities—such as weather data and farming advice. This method ensures a flexible and efficient user interface from ITC, eliminating the need for substantial modifications to the core system architecture. Moreover, the application of contextual indexing and retrieval-augmented generation (RAG) techniques has significantly refined the quality of the app’s responses. 

Krishi Mitra’s queries are meticulously processed by a Semantic Kernel-based orchestrator, which then gets responses from Microsoft plugins. This feature empowers farmers to pose questions on weather forecasts and get agronomic advice for crops while the app identifies and utilizes the most suitable plugin to retrieve the optimal answer for each inquiry. This seamless integration and user-friendly interface are what set Krishi Mitra apart, making it an essential tool for farmers aiming to enhance their agricultural efficiency and outcomes. 

Boost productivity and profitability with AI 

In addition to conventional farming challenges such as soil fertility and climate, many farmers contend with limited access to agricultural technology and relevant information that can support their work. Krishi Mitra delivers a comprehensive array of benefits to farmers by equipping them with the necessary tools and information to refine their agricultural practices and market strategies. The app’s core objective is to provide instantaneous access to critical information, boosting the productivity and profitability of smallholder farmers while promoting sustainability and climate resilience.  

In 2021, approximately 61,000 metric tons of pesticides were used in India for agricultural purposes.² Some pests that were once minor have become major threats thanks to rising temperatures that alter insect-crop interactions. With access to Microsoft AI tools, Krishi Mitra can continuously learn and adapt from new agricultural data and user interactions. This feature allows the app to improve its recommendations and stay updated with the latest farming techniques and information, helping farmers stay ahead of pest issues and use fewer pesticides when they catch problems early. 

Personalized data enhances farming opportunities  

Maximizing profits for small farmers hinges on determining the optimal harvest time to ensure crops are of the highest quality and yield, while also capitalizing on the best market prices. Krishi Mitra empowers farmers with immediate access to essential information like precise weather forecasts, enabling farmers to align their farming operations with upcoming weather conditions. Additionally, it provides comprehensive market insights, including detailed data on market locations, pricing, and other critical factors. Data like this helps farmers make strategic decisions regarding irrigation, the timing of their harvests, and choosing the most profitable buyers located nearest to their farms.  

The diversity of languages in India has traditionally posed challenges to widespread technological adoption among farmers. Krishi Mitra addresses this barrier with its capability to process natural language queries and offer translations in local languages. This functionality allows farmers to use their smartphones not just for communication but as a tool for receiving actionable farm management advice in a language they understand. The app’s personalized advisories are tailored to meet the specific needs of each farmer, ensuring that the guidance they receive is not only relevant but comprehensible. This personalized support is instrumental in improving agricultural yields and subsequently increasing the income of the farmers, truly making Krishi Mitra a transformational tool in the hands of the Indian agricultural community. 

Discover agriculture solutions 

• Learn more about Azure Data Manager for Agriculture features.
• Explore Microsoft Cloud for Sustainability solutions for agriculture.
• Learn about Headstorm’s AgPilot tool.

¹ World Bank Group, Employment in agriculture (% of total employment)(modeled ILO estimate)—India, February 2024.

² Statista, Volume of pesticides used for agriculture in India from 2011 to 2021, March 2024.

The post AI in the fields: Copilot powers smarter farming appeared first on Microsoft Industry Blogs.

Maximizing AI: Category management and more

Buying habits shift quickly in today’s consumer-driven world. For retailers, especially grocers, providing customers with affordable, fresh, and convenient options while navigating the impacts of inflation and supply chain disruption is critical. Meeting these expectations requires creating and maintaining a supply chain centered around customer demand—no easy task when supply chain functions are siloed, data is disparate, and needs change from day to day.

Together, Blue Yonder and Microsoft are unlocking a new era of value for retailers with AI. With AI-powered solutions, retailers can empower their teams to make decisions based on access to real-time data and intelligent insights. AI has allowed us to reimagine planning, making it possible for retailers to operate more effectively by transforming category management into an agile, responsive, and ongoing process that is tightly synchronized with the broader supply chain.

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AI-powered category management makes it simple to keep the end consumer the focal point of your supply chain functions, helping retailers quickly achieve several critical capabilities:

• Address demand across every channel
• Plan at the hyperlocal level
• Optimize for demand in real time
• Factor in space and labor parameters
• Monitor and adjust instantly
• Identify and respond to opportunities and concerns quickly
• Enable continuous learning with constant space and assortment performance feedback
• Share updated demand forecasts across the supply chain

Enabling AI in this way facilitates a constantly improving demand forecast as the AI model builds iteratively on the data provided, allowing planners across the entire value chain to make better decisions for the business. It’s clear that, properly integrated, AI is not just a technological advancement but rather a strategic tool that can lead to improved customer experiences, operational efficiencies, and ultimately, financial growth and scale for retailers.

Blue Yonder and Microsoft teams recently collaborated to present a webinar titled “Supercharge Your Category Management Process with AI Assistance.” In this presentation, we introduced category managers to the many ways AI-powered assortment can help streamline category management and empower faster, smarter decision-making.

But category management is just one piece of the modern supply chain puzzle. In this blog post, we’ll discuss some of the major connecting points between category management and the overarching supply chain and how understanding the interplay between components can help you begin to realize the art of the possible with supply chain AI.

To that end, we’re looking at three major considerations for making the most of category management within a broader, AI-powered supply chain.

1. Synchronizing with the overall supply chain

One crucial thing to consider is the extent to which your category management process must be synchronized with the broader supply chain to enable an agile, responsive, iterative process. This requires thinking about how you get the initial data, and then how you operationalize it — how you put the data to work. Everything should be framed in terms of the end consumer as the focal point, making sure that you address demand across all channels. Doing so normalizes the physical and the digital channels, enabling hyperlocal planning at the individual store level.

It used to be that whatever the practice was, you would cluster stores and talk about stores that had similar formats, planning similarly for all store locations based on one generalized model. Now, with the integration of AI-powered insights and analytics, we’re getting into hyperlocal store planning, where you can really reflect not only the local community shoppers who are making the trip into brick-and-mortar locations, but also support the way that buyers want to shop online, normalizing those two experiences.

But this also requires acute awareness around demand planning, as you have to essentially make sure that demand planning is optimized in real time. This is why the correlation with the supply chain is so important: because you’re reflecting the latest trends, but you’re also working around the space and labor parameters in the store and optimizing in real time to make sure that demand planning is updated accordingly. This ability to execute on constantly changing data across workstreams—to monitor and adjust on the fly—is key to achieving the agility piece that’s so necessary for responding with flexibility to market demands and driving better margins for the business.

2. Enabling collaborative data sharing

Data sharing sits squarely at the intersection between retail consumer goods and category management. In an AI-supported category management process, you have category captains managing entire shelves of a category and gleaning invaluable insights in the process about the performance of products on the shelves, both physical and digital. These insights inform and support their retail partnerships in ways that weren’t possible until very recently.

Cross-capability data sharing allows you to identify the problems and root causes, understand them quickly, take action, and then implement that continuous learning. With interoperability, you can leverage that AI-powered continuous learning component around space and assortment performance, feeding that data back into the forecasting engine to generate an updated view of demand that can be shared across the supply chain so that the demand forecast is constantly improving, allowing planners across the entire value chain to make better decisions.

But a plan is only as good as the ability to execute it, so we move on to thinking about the execution piece and how to optimize that with store-level compliance.

3. Pulling in the store as a node in the supply chain

Syncing this concept of category management with the supply chain is critical for high-impact results because this is where operationalizing your data becomes real. It’s important to understand that integrated architecture is not an orchestrated ecosystem. In order to have a holistic view of the business, synchronization has to take place. You’re reducing the latency to have better data synchronization across various supply chain functions; you’re enabling the collaboration both with store associates but also with brands and retailers, empowering adaptive decision-making by connecting the planning and execution functions.

What’s pivotal to realize here is a theme that we’ll see become more prominent over time: the store is now a huge data source that needs to be integrated with the rest of the supply chain. As we see customer experience playing an increasingly pivotal role in the supply chain, we see a greater need to incorporate store-specific data. It’s no longer that we’re just optimizing store operations off to the side—the store and its operations are now part of the supply chain itself.

Many organizations seek to address concerns around siloed technology, and yet, the retail store often continues to be an overlooked component. Many retailers have warehouse management systems that are connected to their transportation management solutions (TMS), but very rarely do they also connect the stores as being a node in the supply chain for real inventory visibility. So, when we think about optimizing across the different channels with e-commerce and fulfillment, structuring warehouses and the fulfillment network, it becomes more relevant to connect the data across these functions.

Powering a connected supply chain with Microsoft and Blue Yonder

Integrated AI across the supply chain has incredible potential to enhance business performance and reduce volatility with predictive intelligence. Together, Microsoft and Blue Yonder are making it easier for retailers to get ahead with technologies that empower agility, transformation, and innovative operations at scale.

Bringing together the best of supply chain technology and cloud platform capabilities, Blue Yonder and Microsoft are at the forefront of a cognitive revolution of supply chain innovation. Blue Yonder’s Luminate® Cognitive Platform lays the foundation for a truly intelligent autonomous supply chain with predictive and generative AI capabilities that are industry-specific. It’s built on Microsoft Azure, which is a game changer in the cloud platform space, ensuring data is unified for centralized and accessible insights. Our partnership enables supply chain innovation by connecting information across the value chain for better collaboration, scalability, security, and compliance.

Sainsbury’s: Results that speak for themselves

Sainsbury’s is a trusted UK brand, loved by millions of consumers and operating more than 2,000 store locations across its Sainsbury’s and Argos brands. A longtime user of Blue Yonder’s warehouse management, Sainsbury’s sought to implement new AI-powered solutions in 2023 to improve forecasting and replenishment capabilities and increase sustainability.

Blue Yonder has helped Sainsbury’s to tackle several significant goals:

• Realizing improvements in inventory stockholding and availability key performance indicators (KPIs) with machine learning (ML) forecasting and multi-echelon replenishment
• Transforming Sainsbury’s architecture and business processes to become easier to understand, scalable, resilient, and nimble, as well as able to support any future business changes quickly
• Reducing the current number of key systems to eliminate redundant functionality, reduce technology risk, and improve the user experience for colleagues, suppliers, and business-to-business (B2B) customers
• Offering a more automated, simplified user experience and standardized workflows to increase user productivity

Our partnership with Sainsbury’s has already resulted in significant savings for the organization as part of its ongoing plan to future-proof the business. Sainsbury’s leadership confirmed in April 2024 that the company is unlocking significant savings and have already improved ambient availability, using real-time forecasting to optimize sales, waste, and stock equation.

Implementing Blue Yonder’s solutions built on the resilient, scalable Microsoft Azure cloud platform, Sainsbury’s has elevated its ability to monitor and respond to changing customer needs with new capabilities allowing prediction and prevention of potential supply chain disruptions. Blue Yonder has helped Sainsbury’s take advantage of ML-based forecasting and ordering capabilities to help stores better manage fresh and perishable products, while also achieving visibility, orchestration, and collaboration across the end-to-end supply chain, using automation to make better business decisions.

Explore solutions from Microsoft and Blue Yonder

• Learn more about Blue Yonder category management and Microsoft Azure
• Learn more about Blue Yonder Luminate Cognitive Platform
• Learn more about Blue Yonder Orchestrator
• Explore Microsoft Cloud for Retail

The post Supply chain AI for the new era of value realization appeared first on Microsoft Industry Blogs.

The goal of achieving net-zero emissions by 2050 requires tremendous investment and rapid innovation. From solutions that optimize grid management and carbon capture and storage to more sustainable, resilient mines, AI technologies can help address the biggest challenges in the complex, multidimensional global energy transition.  

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Accelerate the clean energy roadmap with new AI innovation 

We’re proud to share some highlights from the past year, starting with the announcement that Cognite is Microsoft Partner of the Year 2024. Cognite and finalists Scheider Electric, Accenture-Avanade, and Kongsberg exemplify the new wave of innovation currently transforming the energy sector.  

Cognite is integrating new AI advances shared at last year’s Ignite event, including Microsoft Fabric and expanded Microsoft Copilot experiences. In January 2024, Microsoft and Cognite announced a collaboration that integrates flagship product Cognite Data Fusion with Microsoft Fabric and Azure OpenAI Service. Cognite AI is a prebuilt, comprehensive AI architecture specifically designed for energy and resource companies to deliver a faster path to implementing AI. Cognite Data Fusion incorporates AI across the data stack from generative AI-powered contextualization to an intuitive natural language Copilot interface embedded in day-to-day tools. Most recently, Cognite announced a new solution, Cognite Atlas AI which brings context augmentation generation to Microsoft Azure OpenAI Service, pushing the boundaries of what language models can do for industrial organizations

Schneider Electric continues making an impact with solutions that accelerate digital transformation and sustainability. Built on Azure, the Schneider Electric EcoStruxure Grid solution portfolio shows the company’s commitment to a more digital and electric world, and together with its Grid Operations Platform as a Service, supports the growth of distributed energy resources, microgrids, energy communities, and other flexible resources across digitally planned, designed and operated lifecycles. AVEVA, part of Schneider Electric, also uses Microsoft technology to help accelerate the energy transition and support long-term decarbonization with a cloud-native industrial data and application platform to give energy companies a digital backbone to unlock, contextualize, and share data for better decision making and more profitable and efficient operations. 

Driving more sustainable, efficient operations in asset-heavy industries, Kongsberg leverages the Microsoft Cloud and AI for its Industrial Work Surface, an industrial metaverse that includes mixed reality and digital twins. The solution is designed to help energy companies improve decision-making, maximize business performance, and drive value across the organization—in support of the world’s growing demand for more secure, equitable, and sustainable energy.

Microsoft partners SLB, Halliburton, and Accenture are also innovating with Microsoft Azure Data Manager for Energy, a secure, reliable, hyperscale and fully managed cloud-based data platform service. Customers can speed toward goals by taking advantage of easy interoperability across an extensible application ecosystem. They can integrate virtually any dataset, application, or cloud service while leveraging the applications they already use from SLB, Halliburton, Accenture, and many others. The platform is expanding to new regions and offers a new developer tier pricing to increase accessibility for more partners and customers. 

We are also pleased to announce EY as the Sustainability Changemaker for the second year in a row. Creating customer tools built on Microsoft technology has positioned EY as a leader in sustainability consulting within the energy sector. With EY’s tailored solutions, decision-makers in the energy industry can now oversee transformations across their enterprises, leveraging technology and data to modernize governance structures, tackle industry-specific risks, meet environmental, social, and governance (ESG) obligations, and deliver value for both their organizations and their stakeholders. These solutions provide a comprehensive view into energy demand, verifiable and assured value chain data, and sustainability performance management, enabling energy companies to achieve their sustainability goals and enhance operational efficiency.

Sharing thought leadership at industry events 

You can learn more about Microsoft and partner innovations at Microsoft Ignite either online or in person in Chicago on November 18 to 22, 2024. This is the first Ignite event to include both customers and partners, and we hope you’ll join us to celebrate our partners and learn more about how the latest advances in AI are delivering business value to our energy customers. 

The Microsoft Energy and Resources Industry team is also excited to connect with customers and partners at upcoming events including the ONS conference in Stavanger on August 26 to 29, 2024 and the SLB Digital Forum 2024 in Monaco on September 16 to 19, 2024. These events will feature how new developments in AI and other digital technologies are transforming energy systems for a more secure, equitable, and sustainable energy future. You can always anticipate exciting news at the SLB Digital forum, where two years ago SLB announced the availability of the SLB Enterprise Data Solution, a comprehensive data management toolkit built on Azure Data Manager for Energy. The innovation is a result of the expanded strategic partnership between SLB and Microsoft, includes enhancements to Azure Data Manager for Energy, and a carbon capture and storage (CCS) initiative with Northern Lights joint venture to support global climate goals by accelerating development of scalable, cost-effective solutions for the CCS value-chain. 

Energizing the energy transition with new startups 

The climate crisis affects people globally, and an inclusive startup ecosystem is critical for helping ensure that solutions have far-reaching benefits. We are proud to support underrepresented startup founders at events like CERAWeek and through programs such as Advancing Climatetech and Clean Energy Leaders Program (ACCEL) from Greentown Labs, Browning the Green Space, and the Energy Transition Studio for Startups which we launched this year in cooperation with high-growth climate tech companies FlexDAO, Line Vision, and Utilidata. The program is designed to empower energy transition startups worldwide, and we are pleased to welcome six more companies to the first cohort, including Carbon Guardian, GridBeyond, Hygenox, IEMS, Noda Intelligent Systems, and Norwegian Hydrogen.

Investing in sustainable AI 

In addition to supporting startups, we are also engaging in strategic regional partnerships to help ensure a sustainable future and equitable access to energy and digital technologies for everyone. Microsoft is investing $1.5 billion in G42, a leading AI company based in Abu Dhabi, to co-innovate and deliver advanced AI solutions with Azure across the Middle East, central Asia, and Africa. Microsoft and G42 are partnering to invest $1 billion in a data center and Kenya, which will be powered by geothermal energy and give east Africa access to Microsoft Azure. Other global investments include a $2.2 billion investment in Malaysia’s cloud and AI transformation, and a significant commitment to enable a cloud and AI-powered future for Thailand. 

Unlocking the transformative potential of AI for sustainability also requires best practices for investment, digital and data infrastructure, resource usage—such as Microsoft’s deal with Brookfield Asset Management to invest more than $10 billion on renewable energy capacity to power data centers—policy and governance, and workforce development. To learn more about AI enablement, read the Microsoft AI and Sustainability Playbook. We are also investing in the sustainability of AI itself, with projects to optimize datacenter energy and water efficiency. 

Partnerships to advance our energy future 

This blog reflects the power of partnership and the growing importance and potential for AI in the energy industry and beyond. This has been a year of exciting change, with groundbreaking advances like the launch of Copilot+ PCs—from both Microsoft and our OEM ecosystem—partnership with OpenAI, and a rethinking of our cloud infrastructure to optimize performance and energy efficiency. 

Microsoft Copilot continues to evolve, with innovations that include the world’s first Copilot in both CRM and ERP with Microsoft Dynamics 365 Copilot. Chevron is already using Copilot in Dynamics 365 Guides to transform frontline operations and optimize its operations, empower workers, and infuse informed decisions throughout its value chain. 

Success stories like these remind us once again that people working together are at the heart of every broad-sweeping, foundational transformation. The world’s complex energy challenges demand global collaboration as we advance toward a more secure, equitable, and sustainable future in an ever-evolving ecosystem of innovation.  

Learn more about Microsoft Energy and Resources solutions 

• Energy and resources – Microsoft Industry Blogs 
• Microsoft energy partner webinar series 
• Microsoft AI solutions  
• Microsoft Azure AI services  
• Microsoft Intelligent Data Platform   

The post Microsoft partners celebrate AI innovation appeared first on Microsoft Industry Blogs.

The telecommunications industry stands at a pivotal juncture, where the convergence of technology and communication is accelerating at an unprecedented pace. Microsoft’s role in this transformation is not just as a participant but as a leader, driving the conversation and action towards a more integrated and efficient ecosystem. Our efforts with the TM Forum and ODA over the years have been instrumental in setting new standards and fostering an environment of open collaboration.

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TM Forum DTW24-Ignite

This year’s TM Forum DTW24-Ignite event serves as a vibrant showcase of progress, partnership, and potential. Sessions will feature discussions on the latest trends and challenges facing the industry, while the Catalysts provide a hands-on look at the innovative solutions being developed.  

Catalyst projects are collaborative initiatives that bring together the collective power of the brightest minds and most influential industry figures to co-create solutions driving industry change through Open APIs, ODA, AI, and automation. Companies collaborate to unlock the possibilities of efficiency for businesses, optimize end-user experiences, and sustainable growth for all. This year Microsoft is thrilled to be actively contributing to two new phase catalysts alongside leaders from Vodafone, AT&T, Bell, Orange, Verizon, STC, Du, BT Group, and more.

• Responsible AI—Improving generative AI’s reliability for adoption at scale: This catalyst aims to address the challenges and risks associated with deploying generative AI models at scale, such as explainability, drift, and bias.
• DarkNOC: Generative AI propels insights driven NetOps—A new AI-driven cloud native stack for network assurance and service management: This catalyst aims to showcase how generative AI can enhance network assurance and service management, using a cloud native stack that aligns with industry-standard architecture, such as TM Forum ODA and Open APIs.

For those seeking a more granular view of the event, my LinkedIn post offers a wealth of information. My detailed account captures the essence of our presence at the event including information on all speaking engagements. 

Innovation Hub and ODA Accelerator

Our recent collaboration with the TM Forum Innovation Hub marks a significant milestone in our journey. By contributing to the ODA Accelerator initiative, we are helping to shape a modular, agile, and future-proof digital architecture that will serve as the backbone of the telecommunications industry for years to come. 

Microsoft has significantly contributed to the ODA program by signing the ODA Manifesto, joining the Innovation Hub, and supporting its development. We aim to transform the industry from legacy operation support system (OSS) and business support system (BSS) to cloud-native software, using standardized plug-and-play components, data models, and Open APIs. We have also created a cloud-based telecommunications ecosystem using the ODA reference canvas on Microsoft Azure, helping to drive digital transformation in the telecommunications sector.²

Our booth will serve as a hub for engagement, where attendees can experience our technologies and interact with our experts. Our in-booth presence includes stations covering: 

Developer velocity

At Microsoft, we believe that empowering developers is key to driving innovation. The ODA canvas and accelerator, along with GitHub Copilot for Open APIs, are revolutionizing the way developers work, enabling them to build more efficiently and effectively. The success stories from Orange and Lumen, as detailed in their respective case studies, are a testament to the transformative impact of these tools.

Our collaborations with TM Forum members Exos Systems and Tata Consultancy Services (TCS) have enriched the developer ecosystem, providing a range of tools and resources that enhance productivity and creativity. Notable projects with Jio, Proximus, Amdocs, Lifecycle Software, and the AT&T SHINE Catalyst further illustrate the breadth and depth of our commitment to developer velocity.

As part of the AI Service Portfolio, TCS has developed their AI First Telco Modernization framework leveraging their rich experience in TM Forum ODA and our strategic partnership with Microsoft.

It combines the power of TM Forum, ODA Framework, and GitHub Copilot for an accelerated modernization of software applications spanning across ideation, development, testing, and deployment. TCS has successfully implemented these generative AI tools for its clients resulting in higher productivity gains and faster innovation. TCS and Microsoft invite you to join our special GitHub Copilot session, featuring experts from Microsoft, TCS, and Proximus.

Jio is at the forefront of technological innovation within the telecommunications sector, consistently pushing the boundaries of what’s possible.

To accelerate the TM Forum ODA Component project, Jio has contributed to the ODA canvas reference implementation. Their journey began with the deployment of the ODA Canvas on Azure, which has evolved to encompass a suite of components, each designed to enhance telecommunications operations:

• Jio Network Performance Management ensures optimal network functionality.
• Jio Integrated Inventory Management streamlines asset tracking and management.
• Jio Floworx revolutionizes product validation and ordering processes.

These innovative components showcase Jio’s commitment to leading the industry’s digital transformation.

Microsoft is excited to collaborate with Jio and TM Forum on this groundbreaking journey. We invite you to experience this innovation firsthand at Jio booth (Jio Platforms Limited—Booth 232) and the Azure ODA Canvas reference implementation at Microsoft booth (Booth—315J), where the future of telecommunications comes to life.

Customer experience

Customer experience is at the forefront of our efforts in the telecommunications industry. Microsoft Dynamics 365 Contact Center is a prime example of our dedication to improving customer engagement. With Microsoft Copilot Studio, we are enabling the rapid development and deployment of intelligent, generative AI-powered automated care bots capable of resolving the vast majority of customer inquiries.

To assist telcos as they move to incorporate AI across their business, Microsoft, Accenture, and Avanade collaborated on a whitepaper titled “Reinventing telecommunications in the era of generative AI.” This paper explores the transformative potential of generative AI in the telecommunications industry and discusses how AI technologies can enhance network efficiency, improve user experiences, and redefine communication.

Vodafone is a great example of the effectiveness of these bots in a real-world scenario, demonstrating how they can significantly improve customer experience while reducing costs, expediting care, and improving net promoter score (NPS).

Charles Lamanna’s keynote at Microsoft Build 2024 provides further insights into these advancements, highlighting how telcos can use Copilot Studio to rapidly create intelligent Copilots of their own. Charles details how telcos can evolve today’s virtual agents into powerful Copilots that don’t just chat, but are capable of running in the background, asynchronously, and executing workflows with true agent capabilities.

To boost productivity and streamline employee experiences, Lumen Technologies has embraced Microsoft 365 Copilot. This generative AI tool integrates seamlessly with Microsoft Teams, providing employees with an intelligent virtual assistant. Finally, the collaboration between Microsoft and ServiceNow is pivotal in this journey. By combining our expertise, we’ve created a smarter way to work, where generative AI assistants coexist and interact. By integrating Now Assist, ServiceNow’s generative AI experience, telco employees receive conversational responses to requests and connects them to AI-powered workflows on the ServiceNow platform.

Network intelligence

The transformation of network operations is a critical component of our vision for the telecommunications industry. Microsoft Fabric Real-Time Analytics is at the heart of this transformation, enabling the collection and analysis of massive quantities of network data from complex, multi-partner environments. 

Accenture and Microsoft are demonstrating the powerful capabilities of Microsoft Fabric and Azure Data Explorer, enhanced by Accenture’s crowdsourcing data and exceptional engineering.

This collaboration aims to deliver actionable insights for Network Quality of Experience (QoE) management and planning, transforming the optimization efforts of mobile operators.

Our focus is to visualize performance issues that are:

1. Easy to comprehend and analyze.
2. Prioritized based on Accenture, umlaut score, and subscriber impact.
3. Root cause analytics, such as coverage and interference issues.
4. Easily integrate with daily workflows and additional data sources.

We will showcase how Accenture, leveraging Microsoft technology, can deliver an advanced platform built using crowdsourcing data, enriched by our custom analytics, and delivered through a user-friendly web-based front end. 

The Accenture integration shows how these capabilities align with the TM Forum Autonomous Networks initiative. Our Azure Programmable Connectivity, detailed in Ricardo’s latest blog, along with the participation of leading carriers, underscores our commitment to adhering to industry standards like the TMF931 Open Gateway Onboarding and Ordering Component Suite. 

Tecnotree recently authored an article titled “Delayering in Telcos: A Path to Agility and Efficiency” which discusses the significant transformation in the telecommunications sector, driven by the need for cost optimization and operational efficiency. It highlights the importance of delayering organizational structures and the role of Azure Programmable Connectivity (APC) in enhancing agility and customer experience.

Our partnership with Norwood Systems in voice intelligence is another example of how we are enhancing network operations. CogVoice™, their innovative AI Agent platform, is designed to re-monetize communications service provider (CSP) voice networks by delivering highly personalized and low-cost cognitive AI agent applications with breakthrough dialog performance. Leveraging Microsoft Azure OpenAI Service and Azure AI Speech, CogVoice brings exceptional natural language processing and speech-to-text capabilities to CSP-hosted agentic services. 

The new telco data model

We are excited to introduce a new Azure Synapse database template for wireless that promises to redefine how data is managed and utilized within the telecommunications sector. This model is designed to streamline operations, foster innovation, and enable a more seamless integration of services across the industry. 

The TM Forum Modern Data Architecture (MDA) is a strategic framework that outlines how data is collected, managed, and utilized—leveraging technologies like cloud computing and big data platforms to support scalable, flexible, and efficient data processing and analysis. We’ve been working with customers and partners to define and implement data platforms that apply this methodology. Most recently, Tech Mahindra launched a unified workbench on Microsoft Fabric, enhancing data workflow efficiency and accelerating digital transformation for enterprises. Similarly, LigaData offers a transformative approach to telecom data management with its Telecom Data Fabric, which leverages Azure to reduce integration time and enhance enterprise data agility and innovation.

Connect with us

Microsoft’s journey with the TM Forum and the ODA is a story of continuous innovation and unwavering support for the telecommunications industry. As we look to the future, our commitment remains strong—to foster an ecosystem where collaboration, technological excellence, and a shared vision drive us toward a more interconnected world. Join us at the event and connect with us online to be part of this exciting journey. 

¹Microsoft expands commitment to ODA and all other TM Forum highlights from MWC 2023!, TM Forum.

²Microsoft expands its commitment to TM Forum’s Open Digital Architecture, inform.tmforum.org.

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To address this growing need, Microsoft Cloud for Sustainability data solutions in Microsoft Fabric (preview) can help organizations take sustainability data in any format, organize, and normalize the data for sustainability regulatory reporting. This quantitative data reporting approach is complemented by a joint solution from Accenture and Avanade that leverages generative AI to provide qualitative insights. This enables organizations to manage workflows associated with multiple sustainability reporting frameworks globally, including CSRD, Global Report Initiative (GRI), and the International Sustainability Standards Board (ISSB). Organizations can optimize both quantitative data from Microsoft Cloud for Sustainability solutions and qualitative data with Accenture and Avanade’s generative AI-powered solution. 

The solution integrates seamlessly with Microsoft Sustainability Manager, offering a comprehensive platform for managing sustainability key performance indicators (KPIs) across different frameworks. The solution’s collaborative features, generative AI-enhanced insights, and streamlined data integration can help organizations simplify compliance-related processes. Meanwhile, the improved richness of its sustainability reporting enables organizations to take more effective actions to achieve their ESG targets.  

Sustainability data solutions in Fabric

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Navigate the complexities of reporting frameworks

All ESG reporting frameworks carry their own complexities. However, the CSRD has been top of mind in 2024 for organizations in and outside of the European Union as they begin to gather, analyze, and report the required data. This is no simple task—the CSRD encompasses 12 standards and 82 reporting requirements, which amounts to approximately 500 KPIs and over 10,000 underlying data points. In addition to managing this large array of ESG data, companies face other significant challenges associated with CSRD compliance and data management including reporting on the entire value chain versus only on their own organization. The evolving nature of sustainability criteria and metrics further complicates the reporting process. 

Navigating the intricacies of a multitude of reporting frameworks and intricate regulations necessitates extensive data gathering and assimilation. The process of ESG reporting often engages various departments and resources within an organization, introducing its own set of risks and costs. The more manual a process, the more opportunities there are for errors to occur, and the complexities of each reporting framework require time, diligence, and accuracy. A proficient solution can help simplify the process and effectively aid in the generation of accurate reports with fewer resources required. 

Accenture and Avanade’s generative AI-powered solution allows users to select from different reporting frameworks and adapts to the specific requirements of the chosen framework, displaying relevant categories and reporting structures. Users can access the breadth and depth of their data and translate it into the necessary reporting frameworks. This flexibility is crucial for organizations that are subject to multiple reporting obligations or need to adhere to international standards beyond local mandates. 

Streamlining data management using Microsoft Azure OpenAI Service

Accenture and Avanade’s solution addresses the dual challenges of qualitative and quantitative data in sustainability reporting, utilizing Azure OpenAI for enhancing its reporting capabilities, especially for qualitative data input. Using Azure OpenAI to create an AI assistant, Accenture and Avanade’s solution offers a unified platform for sustainability reporting, simplifying the process of compiling CSRD reports, making it easier for users to interact with data and generate reports quickly.  

• Qualitative data management: Leveraging Azure OpenAI integration, Accenture and Avanade’s solution assists in drafting responses to qualitative questions, such as detailing a company’s sustainability policies, practices, and goals. This AI assistant ensures that responses are not only in keeping with reporting standards but also reflective of best practices and forward-thinking sustainability strategies.  
• Quantitative data management: The integration of Microsoft Sustainability Manager allows for the automatic import of calculated quantitative metrics. This means that insights or recommendations provided by Accenture and Avanade’s solution is informed by the data in the user’s ESG platform. The AI assistant enables identification of trends and patterns in both qualitative and quantitative data sources, aiding in a more holistic analysis.   

An enhanced collaborative workflow  

One of the biggest pain points that companies have related to ESG reporting is managing the approval workflow with multiple process and approval steps. It’s important to have a trail of accountability, which depending on organization size, can exist across several departments and users. Accenture and Avanade’s solution enables organizations to assign responsibility and accountability, thereby streamlining the process of preparing the report and its associated approval processes.   

Importantly, team members can work on the same sections of the report simultaneously and the platform maintains comprehensive audit trails of all changes made to the report. This transparency is vital for accountability, enabling team leaders to monitor progress and ensure that all contributions align. 

Learn more about sustainability solutions

By facilitating clear communication, structured workflows, and shared access to data in Microsoft Sustainability Manager, Accenture and Avanade’s generative AI-powered solution enables teams to work together toward their sustainability reporting goals. 

To learn more about Accenture and Avanade’s generative AI-powered solution and how it can be customized for your industry and region, register for a complimentary workshop.  

The post Leverage AI to simplify CSRD reporting   appeared first on Microsoft Industry Blogs.

Microsoft Azure Data Manager for Agriculture

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Driving change with copilots 

By leveraging advanced technologies such as machine learning, AI, and data analytics, copilots can provide farmers with real-time insights and recommendations to improve crop yields, reduce waste, and increase profitability. For Microsoft, part of facilitating the adoption of AI and use of copilot templates involves empowering partners. We assist partners by leveraging our unified data estate platform to create tailored, role-specific AI solutions that provide meaningful experiences to customers.  

AgPilot, designed by Microsoft’s partner Headstorm, leverages generative AI along with data from Microsoft Azure Data Manager for Agriculture and agricultural retailers to create actionable insights for agronomists in real time. AgPilot gives them access to essential information ranging from customer purchase histories and product inventories to weather data, enabling proactive management and strategic decision-making. 

Microsoft is working closely with partners like Headstorm to extend Azure Data Manager for Agriculture, a cloud-based platform that enables farmers to collect, store, and analyze data from various sources—including sensors, drones, and satellites. By using this platform, farmers and organizations can gain a deeper understanding of their operations and make data-driven decisions to improve their yields and reduce costs. Supporting agronomists by providing AI-powered tools, Microsoft and its partners are working together to provide optimized agricultural decision-making. 

Enhance communication using AI-generated insights 

AgPilot enhances communication between agronomists and growers, which is crucial for the efficient management of agricultural operations. By leveraging advanced data analytics and AI-driven insights, AgPilot facilitates real-time access to critical agricultural data like soil health, crop conditions, weather forecasts, and pest and disease information. This allows agronomists to quickly gather and analyze relevant information and communicate necessary actions to growers. For example, AgPilot pulls relevant weather data from Azure Data Manager for Agriculture, and if an unexpected frost is predicted, agronomists can promptly advise growers on protective measures to mitigate crop damage. 

AgPilot also includes features that allow agronomists to draft and send customized messages and recommendations directly to growers. These communication tools make it easier to maintain regular contact and ensure that all advice is clear, concise, and actionable. By streamlining and enhancing communication channels, AgPilot helps agronomists deliver a higher level of service, making agricultural management more collaborative, informed, and proactive. This improved communication is key to achieving the ultimate goal of increased productivity and sustainability in farming.

Facilitate sustainable practices with real-time data 

Growers and agronomists working towards more sustainable farming methods—agronomists working with specialty crops (like tree fruit, tree nuts, vineyards) can particularly benefit from AgPilot. Growing specialty crops usually requires more intensive management practices compared to traditional crops. This includes closer attention to the specifics of plant care, such as precise water needs, specialized pest and disease management, and labor-intensive harvesting processes.  

Agronomists can use AgPilot to identify potential pest and disease threats before they become widespread. This proactive approach allows for more effective and minimal use of chemicals, supporting eco-friendly pest control methods. For specialty crops in particular, water management is crucial. AgPilot offers insights into optimal irrigation schedules based on weather data and soil moisture levels, promoting efficient water use and helping to prevent over-irrigation. 

Deployment is simple 

Headstorm has made it very straightforward for existing Microsoft Azure customers to get started right away by subscribing to AgPilot through the Azure Marketplace, available soon. This approach ensures that the setup process aligns with Microsoft cloud infrastructure, leveraging its security and scalability features. Once subscribed, AgPilot is deployed directly into the customer’s Azure instance, adhering to the established data privacy and security protocols of Azure. This setup helps maintain data integrity and compliance with industry regulations, providing peace of mind for users.

Users can tailor AgPilot to align with their specific data sources and systems, integrating it with internal mechanisms such as inventory management, customer relationship management (CRM), and agronomy systems utilized by agricultural retailers. AgPilot combines proprietary customer data with real-time, real-world data from Azure Data Manager for Agriculture. This integration facilitates the generation of alerts that link crop health insights with current weather conditions sourced from Azure Data Manager for Agriculture, enabling quicker and more informed decision-making. Azure Data Manager for Agriculture delivers up-to-date, predictive weather information using an extension-based and provider-neutral framework, permitting integration with any chosen provider. 

AgPilot, leveraging Azure and Azure Data Manager for Agriculture, helps agronomists provide enhanced decision-making to support sustainable management of both traditional and specialty crops. Future roadmap items for AgPilot include leveraging Azure Data Manager for Agriculture satellite imagery to provide on-demand scouting intelligence to the agronomist simply by requesting the intelligence about a particular farm through the chat prompt interface.  

Learn more

• Explore our Azure Data Manager for Agriculture resources.
• Discover how you can accelerate innovation with Microsoft Cloud for Agriculture.
• Learn how Headstorm’s AgPilot tool can help your business.

The post AgPilot: Enhancing productivity and efficiency with AI for smarter farming appeared first on Microsoft Industry Blogs.

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

Microsoft Industry Clouds

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The age of copilots

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

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

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

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

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

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

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

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

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

New copilot templates for retail and sustainability

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

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

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

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

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

Fuel AI with industry data solutions in Microsoft Fabric

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

Healthcare data solutions in Microsoft Fabric (preview) 

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

Retail data solutions in Microsoft Fabric (preview) 

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

Sustainability data solutions in Microsoft Fabric (preview)  

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

Resources to drive innovation

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

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

Learn more about these announcements at Microsoft Build 2024

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

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

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

Microsoft Cloud for Financial Services

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Today, 18 months into the 10-year partnership, we’re seeing incredible progress in bringing that joint vision to reality—with generative AI playing a pivotal role. 

As Matthew Kerner, Corporate Vice President of Microsoft Cloud for Industry, noted at the Sibos 2023 conference, the partnership will ultimately evolve the customer experience at-scale across global financial markets to deliver advanced, easily accessible financial data and actionable insights through empowered workflows. 

In my previous blog post, I reviewed a set of principles that I recommend for successful AI adoption in financial services. Here, I’d like to share three essential lessons from our work with LSEG that are relevant to other financial services organizations, specifically on how to determine a good solution, strategy, and focus for AI innovations.  

Generative AI: The next phase of digital transformation  

On the day of the LSEG-Microsoft partnership announcement, barely two weeks had passed since the unveiling of ChatGPT by OpenAI. Generative AI had not yet captured the world’s imagination, although it soon would. While it may have seemed to some people to have arrived overnight, at LSEG and Microsoft it was the logical extension of technical advances that we’d been focused on for years. 

The emergence of generative AI represents the next phase of digital transformation. A central aspect of the first phase involved instrumenting operations, processes, and products across scenarios and industries to gain visibility into how things were working (or not) and organizing that telemetry into ever more sophisticated data stores to glean valuable insights. Generative AI supercharges that capability with large language models (LLMs) that go far deeper in mining data at incredible speed, and conversational interfaces that let people interact using natural language. The result is a democratization of empowerment and insights at a level not seen since the advent of the internet.  

This is good news for financial services organizations who have made bet-the-company investments on digital transformation. It means that they are well-positioned to capitalize on the foundational attributes of hyperscale cloud computing, including security, compliance, and assurance. From there, the factor that can help realize the greatest innovation with generative AI is a data strategy that ensures the right data is made available to the right LLMs, and ultimately only to the right people.  

With this broad baseline, here are three important generative AI lessons from our work with LSEG thus far.

1. Choose the right AI solution for the right problem

Generative AI is so cool that it’s tempting to try to employ the full scope of its capabilities. Resist this temptation. Focus your attention on problems that actually need solving, as opposed to searching for ways to put AI to work.  

Start with problems that burden your users—for example, laborious processes among people whose time is expensive—and work backwards. Examine the applications and environments in which people spend most of their time and consider how to optimize them. One thing we’ve learned is that integrating AI directly into existing experiences and seamlessly adding support to existing workflows is far more effective than trying to create new application destinations. If you can suddenly summarize a document in 30 seconds that previously required 10 minutes, you are certain to find value.  

In the LSEG partnership, we’re focusing on lighting up experiences within existing Microsoft investments, notably Microsoft Teams, Microsoft Power Platform, and Microsoft Fabric. Among the early highlights of this approach is a new solution in the works to streamline meeting preparation for investment bankers, built directly into Teams. 

We’re also working together to create custom chatbots and copilots within Teams to minimize switching to custom application environments, and answer questions such as, “Show me the P/E ratio of [company].” 

2. Apply your strategy for data management, tenancy, and residency 

The highly regulated nature of financial services means that system design and software architecture are uniquely complex. Different people within the same organization will often require different levels of access to key data under management, and those rules must be respected by an AI solution.  

Rather than developing new ways to handle data access and security for AI, the best approach is to build on top of existing solutions that deliver those capabilities to enact and implement the required access and regulatory controls for AI. If existing solutions are inadequate, then the key order of business is to upgrade. In other words, fix the foundations first, and then build your AI solutions upon them. 

This enables you to understand the topology of what is happening where—such as, which actions occur in which tenant (for example, LSEG customer data versus the Microsoft Graph)—while assuring comprehensive security and compliance. It will also allow you to continue your existing practices around data residency, as well as those for high-availability and disaster recovery (HA/DR). 

With LSEG, we’re focusing on innovations designed to evolve how customers gain value from their data to unlock new opportunities. This involves combining LSEG’s data and content sources in Microsoft Fabric and integrating them into the enterprise-wide data catalog and governance framework of Microsoft Purview. 

“Together with Microsoft, we are empowering our customers by increasing productivity while offering greater efficiency, resilience, and scalability across all workflows, and equipping the industry with the right tools for the next generation of financial professionals. Our multi-discipline practice of data trust is integral to LSEG’s open ecosystem for financial services, built on the foundation of transparency, security, and integrity of information. It aims to deliver rigorous data quality and governance processes, scalable technology powered by Microsoft Fabric and Microsoft Purview, and the “responsible AI” principles.”

Satvinder Singh, Group Head of Data & Analytics at LSEG 

3. Evolve towards greater customer-centricity 

In the early stages of innovation, a common challenge is how to deal with an overabundance of interesting opportunities and ideas from a very broad set of stakeholders. With so many compelling options in front of us with AI, we realized we needed to sharpen our focus to prioritize decision-making based on potential value to the business. 

It is important to resist the temptation to “boil the ocean” by trying to solve too many problems at once. Instead, identify a handful of use case scenarios that focus on benefiting the end customer in ways that measurably impact business goals. To achieve this, our teams developed a methodology involving scoring and ranking of potential initiatives to identify the most promising options. Then we surveyed LSEG’s end customers to help us better understand their needs and inform us on their preferences.  

By combining rigorous customer discovery and a clear validation prioritization process, we were able to identify opportunities we might have otherwise missed—for example, recognizing an emerging set of personas sitting at the intersection of data and AI that we could expect to grow in value in coming years. Embracing a customer-centric approach also created a discipline to quickly test and invalidate hypotheses that would be shown to offer minimal customer value at unacceptable cost. 

Looking ahead with LSEG and Microsoft 

As we move forward in our partnership, LSEG will continue to move beyond delivering data-focused products to offering services that are built on the company’s expertise, data assets, and insights gleaned through AI. This will help solidify LSEG’s pole position in the marketplace as it delivers new solutions to drive financial stability, empower economies, and enable customers to create sustainable growth. 

For every firm, there is a profound opportunity to reimagine financial services. We are excited to continue partnering with LSEG to deliver this value to customers and the industry at large. 

Learn more 

• Discover Microsoft Cloud for Financial Services. 
• Learn more about Microsoft perspectives on the era of generative AI:
  • The era of generative AI: Driving transformation in banking  
  • The era of generative AI: Driving transformation in insurance  
  • The era of generative AI: Driving transformation in capital markets  

The post 3 lessons in financial services AI transformation from the LSEG-Microsoft partnership appeared first on Microsoft Industry Blogs.

To ensure that no one is left behind amidst rapid change, resolving the energy trilemma is a top priority for the industry with a focus on decarbonization, security, and reliable access to affordable energy.

Microsoft is dedicated to helping drive these changes. Our mission to empower every individual and organization on the planet is reflected in our sustainability commitments: To be carbon negative by 2030, and by 2050 to remove from the environment all the carbon the company has emitted since it was founded in 1975.

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We recognize that the future energy mix will be based on cleaner hydrocarbons and renewables, and we are working hard to make that vision a reality. The world needs to invest in more low-carbon energy and infrastructure to meet growing demand and offset the decline of oil production, which falls by 3% to 4% annually.² From technology innovations like generative AI to global collaboration across the energy industry, we are working hard to help drive global change and make that vision a reality.

I’d like to highlight some of those efforts, which include joining other changemakers at CERAWeek 2024 and partnering on a broad range of exciting initiatives.

Driving global change

To increase energy resilience based on cleaner hydrocarbon and renewables, we need innovations and collaboration across the globe. Last month at CERAWeek 2024 in Houston, Texas, CEOs, policymakers, financial communities, and technology leaders gathered to offer insights into the roadmap of this multidimensional energy transition.

We shared insights with industry partners and other global energy stakeholders on complex challenges and multidimensional strategies for energy transition. Microsoft leaders across energy, sustainability, cloud and AI, and security addressed a wide range of topics including the transformative impact of AI and other technologies.

CERAWeek 2024 takeaways

You can read more about the event and Microsoft speakers in last month’s energy blog on enabling energy transformation with AI. Key takeaways included the role of AI in creating a sustainable future, the multifaceted approach required to decarbonize electricity grids, carbon capture, methane mitigation, green hydrogen, and other strategies for addressing climate change. Strategies include nuclear licensing and the AI-methane framework developed with Accenture that brings point solutions together through a strong, affordable digital platform and an ecosystem of partners for end-to-end methane management.

You can read more about how Duke Energy teamed with Accenture and Microsoft to innovate a pioneering solution to meet goals for curbing methane emissions and potentially advance industry and regulatory standards.

Other distinguished speakers at CERAWeek 2024 included Accenture’s Chair and CEO Julie Sweet and Microsoft co-founder and philanthropist Bill Gates. Julie Sweet spoke about challenges and approaches for achieving decarbonization, the need to speed adoption of generative AI in the energy sector, and to dream big to advance the energy transition. She noted human innovation and participation are as important as the technology and data platform driving AI transformation.

Bill Gates discussed emerging clean technologies for investment and deployment, including nuclear and fusion energy, and carbon capture and storage (CCS). He also urged utilities to prepare for rising AI adoption, which he anticipates will increase power consumption, impacting chip makers and electricity cost. This was just one of many discussions at CERAWeek on the need to address AI energy use.

Supporting sustainable AI

During the past year, the pace of AI adoption has accelerated significantly, ushering in groundbreaking advances, discoveries, and solutions with the potential to help address humanity’s biggest problems. Alongside the incredible promise and benefits of AI, we recognize the resource intensity of these applications and the need to address the environmental impact from every angle.

In line with our commitment to responsible AI and our ambitious sustainability commitments, we’re determined to tackle this challenge so the world can harness the full benefits of AI. There are three areas where we’re deeply invested and increasing our focus. The first is optimizing datacenter energy and water efficiency. The second is advancing low-carbon materials, creating global markets to help advance sustainability across industries. And the third is improving the energy efficiency of AI and cloud services, empowering our customers and partners with tools for collective progress.

With AI we are enabling more efficient energy transmission and integration of renewable power. LineVision, an AI-enabled transmission line monitoring solution for expanding the capacity of existing overhead powerlines, is one of many Microsoft partners helping to accelerate the deployment of clean technology and a company which the Microsoft Climate Innovation Fund has invested in. After successfully deploying LineVision Dynamic Line Rating in the United States, global energy company National Grid implemented the technology in Great Britain. The technology has the potential to unlock enough additional capacity to power more than 500,000 homes and save an estimated GBP£1.4 million (US$1.7 million) annually.

Powerful partnerships for transformative solutions

Microsoft and its partners underscore the value of collaborating to accelerate the energy transition in a fair and orderly manner while addressing climate challenges. It is no longer about point solutions, but an end-to-end energy value chain driven by digital and AI which will help us move forward in a rapidly changing world. Recently, EDP Renewables and Volt Energy announced their collaboration with Microsoft to help under-resourced communities build climate resistance.³ Another clean energy initiative announced during CERAWeek between Microsoft, Google, and Nucor Corporation intends to accelerate development of nuclear, next-generation geothermal, clean hydrogen, and long-duration energy storage.⁴

Northern Lights, a partnership between the Norwegian government, Microsoft, and energy firms Equinor, Shell, and Total aims to standardize and scale CCS across Europe. A new CSS plant is expected to process up to 1.5 million tons of liquid CO2 annually and more than 100 million tons over time.

In the United States, Conservation Science Partners, bp, and Microsoft have partnered to create a digital platform for environmental and biodiversity monitoring in Washington state. Called the Cherry Point Refinery, the solution shows how technology can advance our understanding of ecosystems and enable sustainable practices. Other projects include accelerating permitting processes, reducing risk and capital for implementation of carbon capture projects, helping enable the sequestration process for permanent storage with companies like SLB, and supporting environmental credit services.

The future of clean energy and sustainability

I also want to recognize some amazing, underrepresented climate tech founders and CEOs featured at the Microsoft Agora House at CERAWeek who are driving the future of clean energy and sustainability. If it takes a village to raise a child, it will take companies of all sizes and backgrounds to address the growing need for energy and decarbonization by simultaneously meeting goals for energy security, accessibility, affordability, and climate change: Adrienne Pierce (New Sun Road, P.B.C.),  Celine King (GreenIRR Inc.), Chidalu Onyenso (Earthbond), Christie Obiaya (Heliogen), Donnel Baird (BlocPower), Jhana Porter (Frakktal), Liz O’Connell (Arolytics), Nicholas Flanders (Twelve) and Steph Speirs (Solstice).

As part of our commitment to supporting the development of cutting-edge technologies to advance the energy transition, Microsoft is also proud to partner with Greentown Labs and Browning the Green Space’s ACCEL program to fund and mentor the next generation of underrepresented founders. Innovation is the key to solving the global climate challenge, and that innovation must be inclusive and equitable. Energy resilience depends on us all to come together to deliver reliable, accessible, and affordable access to a mix of cleaner hydrocarbons and renewable energy. Our complementary goals for achieving carbon-free energy by 2030 and empowering people and businesses to achieve more goes beyond technology.  

The complex sustainability challenges the world faces today require multi-sector, multidisciplinary collaboration.

We’re not only providing productivity applications, cloud capabilities, cybersecurity, and innovative technologies like AI for end-to-end digital platforms, we’re also honored to be partners and collaborators for accelerating a more secure, equitable and sustainable future.

Learn more about Energy and Resources solutions with Microsoft

• Microsoft for Energy and Resources
• Accelerating sustainability with AI
• CERAWeek 2024 
• COP28: Outcomes and Next Steps
• Transformative AI solutions powering the energy and resources industry

¹ The return of energy security | S&P Global

² World Energy Outlook 2023 Executive Summary, IEA

³ EDP Renewables North America and Volt Energy Utility Announce Solar Project with Microsoft Focused on Environmental Justice

⁴ Google, Microsoft, and Nucor announce a new initiative to aggregate demand to scale the adoption of advanced clean electricity technologies

The post From pledge to action: Enabling the multidimensional energy transition with data and AI appeared first on Microsoft Industry Blogs.