Yet despite broad cloud adoption, migration and modernization remain complex. Legacy architectures, fragmented environments, and persistent skills gaps continue to slow progress, pushing organizations to find ways to migrate faster while minimizing operational risk. 

The IDC study highlights agentic AI as a critical unlock. These intelligent systems automate assessments, orchestrate migration and modernization efforts, and optimize operations across hybrid environments—helping organizations shift from periodic, manual initiatives to continuous, adaptive modernization. This momentum is driving unprecedented growth, with IDC forecasting the public cloud services market will reach USD1.9 trillion by 2029. 

While migration frameworks may be horizontal, their real-world impact is industry-specific. Healthcare, financial services, and manufacturing each face unique constraints shaped by regulation, operational risk, and mission-critical systems. 

In this blog, we explore the key migration and modernization challenges across these three industries—healthcare, manufacturing, and financial services—through real customer stories that highlight the tangible impact cloud adoption is delivering today.

Healthcare: Modernizing securely while powering next-generation clinical experiences

Healthcare faces the toughest modernization headwinds: strict regulations (HIPAA/HITECH, HITRUST), fragmented clinical data across electronic health records (EHRs) and imaging systems, aging on-premises infrastructure resulting in high Capex, and heightened exposure to ransomware.¹ Clinical environments also demand extremely low latency and high reliability.

The IDC study notes that these constraints slow modernization—but accelerate the need for it, as organizations push to scale telehealth, imaging workloads, genomics pipelines, and AI-powered clinical workflows.¹ 

What healthcare organizations need, according to the IDC study: 

• Secure, compliant integration across EHRs, picture archiving and communication systems (PACS), genomics systems, and Internet of Things (IoT) medical devices.¹
• Elastic compute for high-throughput imaging and genomics. 
• Stronger disaster recovery and recovery time performance.¹
• Ambient documentation and AI-supported diagnostics.
• Secure clinician collaboration and modern patient digital front doors.

Customer spotlight: Franciscan Health

Facing aging infrastructure and disaster recovery risks, Franciscan adopted a pragmatic workload placement strategy—moving its Epic EHR to Microsoft Azure.

The results included: 

• $45 million in savings over five years after migrating Epic to Azure.
• 90% faster disaster recovery compared to the prior environment.
• Around a 30-minute failover, reduced from hours.
• $10–$12 million per day in potential downtime risk avoided.

Learn more about Franciscan Health’s journey to migrate its Epic EHR to Azure.

Healthcare’s modernization mandate is clear: reduce operational risk, meet regulatory demands, and harness cloud AI to improve patient outcomes. 

Financial services: Enabling real-time intelligence and automated compliance

Financial institutions operate in one of the most regulated environments, including the payment card industry data security standard (PCI DSS), the Sarbanes-Oxley Act (SOX), the Gramm-Leach-Bliley Act (GLBA), Basel capital frameworks, and know your customer (KYC) and anti-money laundering (AML) requirements, and rely heavily on legacy mainframes that are difficult to modernize. Today, regulatory pressure is intensifying further as new frameworks such as the EU’s Digital Operational Resilience Act (DORA) and the EU AI Act raise the bar for operational resilience, third-party risk management, model transparency, and ongoing compliance monitoring. Under DORA, financial services firms must demonstrate continuous information and communication technology (ICT) risk management, advanced incident reporting, and resilience testing across critical systems and cloud service providers. Meanwhile, the EU AI Act introduces governance requirements for high-risk AI systems, including explainability, data lineage, human oversight, and auditability—with direct implications for fraud models, credit scoring, and customer decisioning platforms.

IDC interviews highlight accelerating demand for real-time risk analytics, fraud detection, digital onboarding, and infrastructure elasticity to support peak activity—capabilities that are increasingly mandated, not optional.¹

Key challenges the IDC study identifies: 

• Strict data residency, model risk governance, explainability, and eDiscovery requirements.¹
• Heightened expectations for operational resilience, cyber defense, and third-party risk oversight.
• Legacy systems and common business-oriented language (COBOL)-based batch processes resistant to change.
• Rapidly evolving regulatory mandates requiring continuous compliance rather than point-in-time audits.

Cloud—especially especially platform as a service (PaaS) and managed services—helps financial institutions shift from static, batch-driven compliance to continuous controls and real-time observability. By reducing batch windows from hours to minutes, modern cloud platforms enable real-time insights, automated evidence collection, resilient architectures, and policy-driven compliance workflows aligned with DORA and AI governance requirements.¹ Learn more about how Microsoft can help financial institutions navigate these requirements. 

Customer spotlight: Crediclub

To accelerate product innovation and meet expectations from Mexico’s national banking and securities commission (CNBV), Mexican fintech Crediclub modernized its databases to a serverless platform as a service (PaaS) architecture and adopted microservices.¹

The impact:

• Uptime improved from around 80% to 99.5%.
• 90% reduction in network latency through Multiprotocol Label Switching (MPLS) and dark fiber.
• Rapid deployment of new financial products via Kubernetes and DevSecOps.

For financial institutions, modernization is no longer just about efficiency—it is foundational to resilience, trustworthy AI, and regulatory compliance at scale. 

Manufacturing: Unifying IT and OT for predictive, data-driven industrial operations

Manufacturers operate in one of the most complex operating environments—defined by legacy and proprietary operational technology (OT) protocols, historically air-gapped manufacturing execution systems (MES) and supervisory control and data acquisition (SCADA) systems, and globally distributed supply chains. Stringent low-latency requirements for safety-critical systems, intermittent connectivity at the edge, and the need to protect intellectual property further compound the challenge. The ability to modernize and unify these environments—without compromising safety, reliability, or performance—represents a critical inflection point for industrial transformation.

Unique modernization challenges according to the IDC study:

• Ultra-low latency requirements for safety-critical operations.
• Massive telemetry ingestion and time-series analytics at scale.
• Operational complexity across global, distributed supply chains.
• Secure protection of intellectual property across edge and cloud environments.

Opportunities unlocked by cloud:

• Predictive maintenance with IoT ingestion.¹ 
• Reduced unplanned downtime and improved overall equipment effectiveness (OEE).
• Digital twins for plants, lines, and products.
• Computer vision for real-time quality and safety. 
• High-performance computing (HPC) simulations for engineering and design. 
• Standardized, global data models.

Customer spotlight: ASTEC Industries

ASTEC unified fragmented systems across its rock to road value chain—from aggregate processing through asphalt production and paving—by adopting Azure, modernizing to timeseries databases, and building a universal connectivity platform using Azure IoT Hub, Azure Events Hub, and Power BI.¹

The results:

• Realtime operational visibility across fleets.
• Predictive maintenance for reducing downtime.
• New digital services supported by connected equipment.

Manufacturing’s modernization imperative: unify OT and IT, scale real-time intelligence, and enable global efficiency. 

Microsoft’s approach: Continuous, intelligent, collaborative modernization 

Microsoft’s strategy is grounded in a simple principle: modernization should be continuous, intelligent, and collaborative. The IDC study emphasizes that successful enterprises adopt a balanced, multipath migration strategy, blending rehost, replatform, refactor, and software as a service (SaaS) substitution based on workload criticality.¹

Microsoft enables this approach through a comprehensive set of tools and offerings, including Azure Copilot and GitHub Copilot. Agentic automation enables:

• Discovery and dependency mapping.
• Security assessment and 6R recommendations.
• Application refactoring, code remediation, and modernization. 

Azure Migrate provides unified discovery, assessment, migration execution, and modernization services. Azure Accelerate complements this with a coordinated framework that includes:

• Guided deployments through Cloud Accelerate Factory.¹ 
• Funding and Azure credits for planning, pilot, and rollout. 
• Expert partners and tailored skilling programs.

The IDC study concludes that organizations using Microsoft Azure for migration and modernization achieve lower operational costs, improved resiliency, faster modernization timelines, and stronger security postures—especially in regulated industries.¹

Looking ahead: Agentic modernization as the foundation for AI-ready enterprises

Across all industries, IDC’s findings are consistent: agentic AI is emerging as the new force multiplier for modernization, enabling organizations to keep pace with rising complexity, regulatory demands, and competitive pressure. 

Healthcare, financial services, and manufacturing each face unique constraints—but cloud modernization remains the foundation for innovation, operational excellence, and enterprise AI. 

Microsoft’s approach gives organizations the unified automation, intelligence, and tooling they need to modernize securely and at scale. 

• Explore how Azure Copilot accelerates cloud migration.
• Discover GitHub Copilot for app modernization.
• See how Azure Accelerate supports transformation.

¹ IDC White Paper, Cloud Migration and Modernization Strategies for Healthcare, Financial Services, and Manufacturing, February 2026.

The post Modernizing regulated industries with cloud and agentic AI appeared first on Microsoft AI Blogs.

Yet social services leaders are under growing pressure to deliver both human outcomes and financial stewardship at scale. Backlogs, fragmented records, and manual evidence reviews strain frontline staff, while delayed verification and siloed data expose programs to error and misuse. The challenge is no longer choosing between inclusion and integrity. Modern eligibility systems must deliver both. 

Why does this matter now? 

The financial implications are significant. Around the world, governments are confronting the cost of improper payments, fraud, and administrative inefficiencies: 

• In the United States, the Government Accountability Office reports that 16 federal agencies estimated about $162 billion in improper payments in FY2024, with roughly 84% due to overpayments.¹ 
• In the United Kingdom, public sector analyses estimate £33 Billion to £59 billion annually in fraud and error.² 
• In Australia, the Australian National Audit Office reports that in 2021–2022, Services Australia delivered $124.7 billion in welfare payments, with an estimated 6.71% in overpayments.³ 
• In India, a government press note summarizing a quantitative assessment highlights ₹3.48 lakh crore in cumulative savings attributed to leakage reduction enabled by the country’s Direct Benefit Transfer program.⁴ 

At the same time, large-scale digital identity and cash transfer reforms around the world demonstrate  what’s possible when delivery systems modernize. These transformations show that improving both inclusion and fiscal stewardship is not only possible—it’s already underway. Modernizing eligibility is no longer just an IT upgrade. It is a service delivery transformation, a fiscal stewardship strategy, and a trust- building effort between governments and the people they serve.

Microsoft’s point of view 

Microsoft’s point of view is simple: modern eligibility is not about replacing human judgment with automation. It is about augmenting frontline staff with secure, interoperable, AI-enabled tools that fit into the systems governments already rely on. 

That’s why our approach emphasizes identity as infrastructure, evidence as data, and AI with humans in the loop—so agencies can modernize incrementally, maintain accountability, and adapt as policies evolve. 

What changes when eligibility is designed around real lives? 

When eligibility systems are designed around programs rather than people, friction is inevitable. Households move across life events faster than policies or systems can adapt, forcing staff to reconcile fragmented records, incomplete documentation, and outdated rules. 

Leading agencies are addressing this by treating eligibility not as a one-time decision, but as a continuous, connected process—grounded in strong identity, structured evidence, and shared data across programs. 

What modern eligibility looks like

Modernization is not a monolithic system replacement. It is a set of incremental, coordinated capabilities that governments can adopt without wholesale replacement.

Below are the core capabilities that define modern eligibility today. 

Identity as eligibility infrastructure 

Eligibility starts with a foundational question: Who is applying, and is it really them? 

Identity theft doesn’t just divert public funds—it can lock legitimate residents out of help. Treating identity as a side project is increasingly a risk. 

In South Australia, the Department of Human Services uses Microsoft Entra ID to strengthen identity protection through role-based access controls, multifactor authentication, and print and screen access safeguards. These steps help protect sensitive records and support secure self-service—without adding friction for legitimate users. 

Turning documents into usable data 

Documents are often the hidden tax on benefit delivery. Much of the delay in eligibility processing comes not from policy rules but from handling paperwork—reading scans, re-entering information, or chasing missing pages. 

The Czech Republic’s Ministry of Labor and Social Affairs addressed this by using Azure AI Document Intelligence to extract data from paper forms and accelerate payment of childcare allowances. The Jenda portal also gives families visibility into application status and connects them to upskilling opportunities—illustrating how digitizing evidence can improve both speed and experience. 

Connecting fragmented records to see the full picture 

A resident may interact with multiple programs, often across separate systems. Fragmented data can lead to duplication, inconsistent decisions, or missed support. 

Singapore’s Central Provident Fund Board modernized its data management approach with Azure Databricks to serve more than four million people with a more holistic view—a strong example of how connected data improves outcomes while reinforcing integrity. 

Aligning eligibility with life events

Eligibility is not static. Circumstances change: employment shifts, caregiving arrangements evolve, households expand or contract. 

Modern systems use AI—responsibly and with humans in the loop—to: 

• Collect and structure evidence 
• Surface relevant context 
• Reduce administrative effort 
• Route complex cases to specialists 

The Washington, DC Child and Family Services Agency (CFSA) built an AI-enabled platform that saves 45 minutes per intake and expects even greater time savings for investigations, while enabling new features to be deployed faster and at lower cost. 

All AI capabilities described here align with Microsoft’s Responsible AI principles and maintain human accountability throughout the process. 

Detecting anomalies earlier to protect funds

Fraud and error often exploit timing: delayed verification, siloed data, or missing crosschecks. 

European public sector fraud authorities are increasingly looking to augment AI‑powered analytics platforms with broader datasets, such as sanctioned entities and dormant companies, to strengthen early detection capabilities and help investigators surface potential risks sooner.

A practical path forward for social services and government leaders

Many eligibility modernization efforts stall because they focus on a single dimension—speed, cost reduction, or compliance—at the expense of the others. Microsoft’s approach is designed to advance service delivery, integrity, and trust together, using platforms that governments already operate and govern. That balance is what allows modernization to endure beyond a single program or funding cycle. 

Whether a program is just beginning modernization or aiming to scale next-generation capabilities, leaders can start with achievable, high-value steps: 

• Start where friction is highest: Identify the program with the heaviest documentation burden or the largest backlog. Early wins build momentum and trust. 
• Treat identity as foundational: A strong identity layer protects against impersonation and enables secure self-service for residents and staff. 
• Digitize the evidence pipeline: Use document intelligence to convert evidence into structured data so staff can focus on exceptions—not re-keying information. 
• Connect data to reduce duplication and missed support: A holistic view—especially at the household level—helps ensure decisions reflect real circumstances and prevents duplicative benefits. 
• Embed continuous integrity: Use signals, analytics, and network insights to focus oversight where risk is highest without creating barriers for eligible residents. 
• Measure what matters: Track speed, accuracy, integrity, and resident experience together. Modernization that improves only one dimension rarely endures. 

This is where Microsoft differentiates—enabling agencies to modernize eligibility without sacrificing accountability, trust, or program continuity.

A more trusted, human-centered future for benefits 

For social services leaders, the next step isn’t a wholesale system replacement. It’s identifying where eligibility friction is highest—and where stronger identity, smarter evidence handling, or connected data could immediately improve outcomes for residents and staff. 

Learn how agencies are applying these capabilities today and explore where modernization can start in your own programs.

Are you attending HIMSS Global Health Conference and Exhibition in March this year? Make sure to check out the Microsoft sessions and expo booth.

¹US Government Accountability Office

²Global Government Finance

³Australian National Audit Office

⁴Government of India Press Information Bureau

The post Right benefit, right person, right time: How AI is reshaping administration of benefits programs worldwide appeared first on Microsoft AI Blogs.

That’s why I’m excited to share that Microsoft Azure has completed an independent, industry‑led GxP supplier audit conducted through the Joint Audit Group managed by Ingelheimer Kreis (IK).

GxP refers to regulations that ensure quality, safety, and data integrity in highly regulated environments, particularly in life sciences. This milestone provides independent validation that Azure’s systems and processes meet the standards required to support regulated workloads in the cloud, giving organizations greater confidence to accelerate their AI transformation and scale innovation responsibly.

“Overall, the audit observed strong organizational maturity, robust processes, and effective governance structures. Microsoft demonstrated a high degree of transparency, collaboration, and readiness to address regulatory expectations. Furthermore, Microsoft demonstrated strong maturity in quality, security, compliance, engineering, and operational processes. The organization showed strong commitment from leadership and robust operational controls.”

As quoted by the Joint Audit Group managed by Ingelheimer Kreis

This milestone builds on Azure’s longstanding commitment to compliance, reinforcing trust across life sciences and other highly regulated industries while helping accelerate broader cloud and AI adoption.

Raising the bar for cloud trust in life sciences and beyond

IK conducted a GxP-aligned supplier audit of selected aspects of Microsoft’s cloud service operations within an agreed scope. The sessions provided insight into governance, security and software engineering practices, and operational processes that may impact regulated GxP use of Microsoft Azure and related services. The audit was performed using a spot-check approach and reflects the information presented by Microsoft during the sessions. The IK audit results provide IK members with assurance regarding the Azure controls environment, enabling members to work to remove compliance blockers, accelerate their adoption of Azure services, and obtain confidence and trust in the security and sovereignty controls of Azure.

The joint GxP audit provides pharmaceutical and life sciences organizations with a higher level of confidence that Azure’s operational, security, and compliance practices meet industry expectations for validated GxP workloads. By having a coalition of major pharmaceutical manufacturers audit Microsoft’s cloud controls, customers gain assurance that Azure’s change management processes, evergreen update model, and underlying operational rigor align with the standards historically required in on-premises validated environments. This independent industry assessment reduces longstanding adoption barriers for regulated workloads and gives customers a basis for trusting Azure as a compliant, reliable platform for GxP relevant applications.

Microsoft Azure is designed to meet stringent requirements for data residency, privacy, and compliance. With Microsoft, organizations can keep sensitive data within defined geographic boundaries and under local jurisdictional control.

Microsoft offers a comprehensive set of compliance offerings to help organizations comply with national, regional, and industry-specific requirements. Backed by more than 100 compliance certifications—including ISO, HIPAA, and HITRUST, Azure meets rigorous security and privacy requirements across global and industry frameworks.

Securing the future: a collaborative approach

Security and compliance in the cloud is a shared responsibility, and the division of those responsibilities between the cloud service provider and customer depends on the cloud offering utilized. Microsoft works to ensure that we are compliant with industry and international standards, and customers are responsible for ensuring their data within the Microsoft Cloud is protected in a manner that is compliant with the standards and regulations imposed on the customer.

Azure integrates with services such as Microsoft Purview Compliance Manager and Defender for Cloud to provide organizations with visibility into their compliance posture and enable proactive governance across cloud environments.

We also provide clear guidance and detailed, auditable evidence through the Microsoft Trust Center and the Service Trust Portal. These tools exist to give customers transparency and confidence, pairing high‑level trust principles with concrete proof customers can use to meet their own regulatory and assurance needs.

With independently audited controls now recognized by leading multinational pharmaceutical companies, Azure gives life sciences organizations the confidence to run their regulated workloads in the cloud—so they can focus on what truly drives value: discovering new therapies, accelerating R&D, scaling clinical operations, and manufacturing medicines reliably at global scale. Instead of diverting resources toward duplicative cloud platform audits, customers can trust that Azure’s underlying operational rigor, change management processes, and security practices meet GxP expectations.

The audit strengthens the foundation that lets life sciences innovators move faster, modernize safely, and keep their focus on bringing breakthrough medicines and devices to patients. For more information on the audit, contact the team.

Empowering our customers

Microsoft remains committed to meeting today’s compliance, security, and regulatory standards. Across our cloud platforms and services, we maintain rigorous and independently validated controls, adhere to applicable laws and industry requirements, and continually strengthen our frameworks to protect the confidentiality, integrity, and availability of customer data. This commitment is reinforced by foundational company policies, a robust global compliance program, and active oversight from senior leadership—ensuring that every Microsoft offering is built on trust, transparency, and responsible innovation.

By working with industry leaders and regulators to shape compliance frameworks and advance sovereign cloud capabilities, Azure supports the next era of regulated AI innovation. By upholding these standards, we empower organizations in regulated industries to operate confidently, knowing their workloads run on a platform designed to meet stringent expectations today and evolve alongside emerging regulatory guidance, validated by independent experts and experienced by customers every day.

More on our approach to trust and compliance

• Dive deeper into how leading life sciences organizations are building readiness and resilience with trusted cloud platforms. Explore the e-book, Reshaping Manufacturing and Supply Chain in Pharma and MedTech, to discover actionable strategies for compliance, innovation, and operational excellence in regulated manufacturing.
• Explore From Vision to Value: AI Use Cases Transforming Healthcare to learn how healthcare and life sciences organizations are applying AI today on trusted cloud platforms.
• To learn more about Microsoft’s approach to trust and compliance, explore resources at the Microsoft Trust Center.

Connect with us at upcoming industry events to see how Azure can help your organization achieve more with confidence.

The post Microsoft Azure achieves GxP milestone, reinforcing trust for regulated workloads appeared first on Microsoft AI Blogs.

• Category: AI

September 4, 2025

Could AI help save one of the Pacific Northwest’s most vulnerable animals?

By

• Deborah Bach

On a cool morning in early summer, Zhongqi Miao stands behind a tree in the Asian small-clawed otter exhibit at Seattle’s Woodland Park Zoo tinkering with a small camera hidden among the leaves.

The Microsoft AI for Good Lab scientist’s focus is on Little Frei and Connor, the two furry residents clambering over rocks and swimming in a pool, because they’re similar in size and shape to Pacific martens — an animal that has perplexed conservationists for years.

The zoo is piloting a new wildlife monitoring system with built-in AI that could eventually help determine why the Pacific marten, a small tree-climbing creature in the weasel family, has apparently nearly vanished from Washington’s Olympic Peninsula.

Woodland Park Zoo is among 20 organizations to receive a grant earlier this year from Microsoft’s AI for Good Lab to support innovative AI-based projects in Washington state. The zoo is testing SPARROW (Solar-Powered Acoustic and Remote Recording Observation Watch), an AI-powered system the lab developed that collects wildlife data from cameras and acoustic sensors and transmits it directly to the cloud via satellite, enabling researchers to access — and act on — real-time insights.

Designed to enable biodiversity monitoring in remote locations around the world, the open-source platform, announced in December 2024, can be built and used by anyone. The zoo, under its Living Northwest conservation program, hopes to use SPARROW to find and evaluate Pacific martens in isolated areas of the Olympic Peninsula. 

The technology is being deployed in other projects in several countries, but the zoo pilot is its first application in Washington, where the technology was developed on Microsoft’s Redmond campus.

“Having innovative partners like Woodland Park Zoo provides us with early insights into how the technology is performing and what could be improved,” says Juan M. Lavista Ferres, chief data scientist and director of the Microsoft AI for Good Lab.

“And starting in our own backyard allows for quicker adjustments in a more controlled setting before SPARROW is deployed in more remote, harsher conditions.”

Real-time detection

The zoo originally planned to test SPARROW to understand how animals live and interact with humans in urban areas, but conversationists realized the technology could be more valuable for the zoo’s Olympic Marten Project, which aims to determine why marten populations on the Olympic Peninsula remain small and how they might be restored.

Those efforts are challenging in part because biologists working on the project retrieve data from wildlife cameras only during summer, given the region’s rugged terrain and winter conditions. If a camera detects one of the elusive martens over the winter, researchers often don’t find out until months later.

“We only get data once a year from the cameras we’ve currently put out,” says Robert Long, senior conservation scientist and director of the Living Northwest program.

“So for us to have feedback about how a population’s doing or whether an animal even occurs in an area, we usually have to wait almost a full year between visits.”

If SPARROW detects martens on the Olympic Peninsula, biologists could quickly go to those sites and set devices to collect genetic samples that can help determine population size and viability. Having an array of remote cameras providing real-time alerts of detections could be key to helping save Pacific martens in the Olympic Mountains.

“Because martens are so rare in the Olympics, this technology would allow us, if we have a detection, to really intensify our efforts to collect a DNA sample,” says Paula MacKay, a carnivore conservation specialist with Living Northwest.

“The potential conservation value really lies in that real-time detection for rare species,” she says. “That allows researchers to take the next step, whatever that next step would be, toward better informing the scientific knowledge about that particular species.”

Accelerating wildlife research

Located on the northwestern tip of Washington state, the Olympic Peninsula is a 3,600-square mile expanse encompassing glacier-capped peaks, mossy rainforests and a rugged Pacific coastline. Martens were once widespread on the peninsula, inhabiting both forests and high-elevation subalpine zones.

But by the 1960s, martens had become rare due to habitat loss, trapping, climate change and other pressures. During the 1990s, there were no Pacific martens sighted on the Olympic Peninsula at all. Then in 2008, a young female marten was found dead on a peninsula trail — the first confirmation of the species in the area in almost 20 years. There were just a few sightings over the ensuing years.

In 2015, Long and a colleague from Idaho Fish and Game collaborated with a Microsoft engineer to develop an automated scent dispenser that could operate through the winter and replace the bait lures traditionally used for wolverine monitoring, which need to be rebaited every few weeks. But rebaiting isn’t always feasible in winter, when remote mountainous areas are often avalanche-prone or inaccessible due to snow.

By contrast, the battery-powered scent dispensers, placed in trees with cameras facing them, could be programmed to emit a small amount of liquid scent lure daily for a year or more without any maintenance. 

“It was super successful,” Long says. “It bumped up our wolverine detection rate by three to four times what we had experienced previously.” 

The new scent dispenser approach also led to 13 marten detections in Olympic National Park between 2017 and 2019, more than the total number recorded in the previous half-century. With the help of volunteers, Woodland Park Zoo started building the scent dispensers and selling them to other conservation biologists interested in attracting a variety of carnivore species.

Now, Long and his colleagues hope to build on their earlier success by pairing scent dispensers with SPARROW technology. They plan to test SPARROW in Washington’s Cascade Range, where martens are prevalent, then deploy the technology to look for martens on the Olympic Peninsula.

The solution’s AI can be trained to recognize particular species, sifting through millions of images and isolating only those showing a specific animal. That ability, Long says, could make SPARROW useful for the zoo’s monitoring of other vulnerable populations in the Cascade Range, like wolverines and Canada lynx.

“We could program it for the six or seven species we’re most interested in and move our data analysis process far ahead,” he says, “instead of waiting to get a huge dump of data once a year that we then have to analyze.” 

Otters and tigers and bears

Back at the zoo, Miao and Rahul Dodhia, deputy director of the AI for Good Lab, installed two additional cameras outside the Malaysian tiger exhibit and the nearby sloth bear exhibit, using zip ties and poles to rig the cameras in locations not accessible by the animals.

The goal, Dodhia explained, is to have multiple cameras communicating with a single SPARROW unit to gauge if the cameras are communicating properly, the system is sufficiently powered and the satellite signal to the Wi-Fi is functioning. The system is programmed to identify only animals, leaving out any images of people the cameras might capture.

“The idea is, how does this SPARROW system perform when it’s going 24 hours a day, every day of the week, because we want it to be operational without any human intervention for at least a year,” Dodhia says. “This is a safe simulation of a wild environment.”

Tools like the SPARROW system and scent dispenser are crucial to the zoo’s emphasis on using non-invasive monitoring methods to study rare and threatened species, says Katie Remine, Living Northwest’s conservation manager.

“This type of technology is so important,” she says. “It allows you to learn about the animals without stressing them.”

‘Transformative potential’

The catalyst for SPARROW emerged through conversations Lavista Ferres had with biodiversity experts at a conference in May 2024.

In talking with those experts, Lavista Ferres realized that the main challenge in collecting biodiversity data wasn’t access to AI models, which many conservationists were already using, but the slow process of manually collecting data. Seven months later, the lab launched SPARROW to enable conservationists to place devices in the most remote regions of the world without needing to physically retrieve data.

“By removing this barrier, SPARROW reduces the data cycle from months to days, or even hours,” Lavista Ferres says. “When you combine this with AI, we unlock transformative potential — not just accelerating the pace of conservation work, but expanding the very kinds of questions and research these experts can now pursue.”

Long and MacKay hope that by providing real-time data, SPARROW might help conservationists determine how Pacific martens can thrive on the Olympic Peninsula as they once did.

“It would probably allow us to do something that we really won’t be able to do otherwise,” Long says, “so it’s pretty important.”

Lead photo: A Pacific marten in the North Cascades. (Photo by Daniel Harrington )

The post Could AI help save one of the Pacific Northwest’s most vulnerable animals? appeared first on Microsoft AI Blogs.

Manufacturers face existential challenges around several key and often conflicting goals; the need to increase revenue whilst at the same time reducing costs across the value chain—spanning engineering, manufacturing, and supply chains, starting with product design and engineering. These challenges have impacted everything from product requirements and capabilities to product development all the way to sourcing and production. A recent IDC report highlighted how for product managers, investing more in engineering and research and development (R&D) correlates with lower cost of goods sold (COGS) and higher revenue growth for manufacturers, suggesting that investments in product engineering investments drive financial success.¹    

Benefits of generative AI in product engineering  

As product complexity and connectivity has continued to increase, engineers’ roles have become multi-disciplinary, requiring interaction with various data sources and tools, such as product lifecycle management (PLM), computer-aided design (CAD), computer-aided manufacturing (CAM), application lifecycle management (ALM) for software requirements, and computer-aided engineering (CAE). In addition to manufacturability, engineers need to incorporate aspects such as sustainability, regulatory compliance, quality, materials, and supplier and supply chain considerations much earlier in the product design process. The many lines of software code now prevalent in physical products and the growth in software requirements, also pressures traditional manufacturing information technology (IT) to support a proliferation of software tools, data, and infrastructure.      

Generative AI is transforming product engineering and R&D to enable manufacturers to realize these benefits:  

• Cost reduction: Optimizing product designs for cost, sustainability, and manufacturability can reduce product development and production costs.  
• Better decision-making: Facilitated through data analysis and scenario simulation, generative AI provides valuable insights for informed decisions that can enhance product development, improve product quality, and better meet customer demands.  
• Productivity and skills gap: Helps experienced designers automate tasks they do often, and inexperienced designers to get up to speed quickly and avoid errors with best practice guidance.  Assists with analysis and optimization of existing designs and can even generate new designs with user input.   
• Efficiency: Reduce the time taken by engineers to both search across, and interact with, product data from various sources across the product lifecycle.  
• Faster time-to-market: Shorter product development cycles mean products can reach the market faster to capitalize on new opportunities more quickly. 
• Innovation: Continuously analyzing product-related data from various sources, customer feedback, and learning from it with generative AI can suggest innovative solutions that might not be more readily apparent.   

Microsoft partners play a pivotal role in transforming product engineering and R&D by building industry-specific solutions that integrate data unification and contextualization capabilities with Microsoft technologies which, combined with the Microsoft Cloud, are revolutionizing engineering functions.    

Establishing a secure engineering data foundation  

Product engineering and R&D involve handling many types and modalities of data, including CAD files, technical specifications, product data and configurations, requirements, and process data. Manufacturers commonly use a range of systems, including PLM, ALM, and enterprise resource planning (ERP) systems, to manage this complex data. These form a secure data foundation on which transformation of product engineering is built upon, and sensitive IP can be protected.     

The following are examples where generative AI is helping to deliver value in a secure, engineering data foundation with AI on the Microsoft Cloud.  

• Siemens has integrated Microsoft Teams, Microsoft Azure OpenAI Service, and Siemens’ Teamcenter PLM solution into an app to facilitate real-time communication and collaboration among frontline workers and engineers.
• Aras has introduced AI-assisted search and an intelligent copilot, using Azure OpenAI Service and Microsoft Copilot Studio on Azure, enhancing user interaction with PLM data, facilitating quicker access, analysis, and action on critical information through scalable search and conversational AI, user interaction with PLM data, facilitating quicker access, analysis, and action on critical information through scalable search and conversational AI.
• PTC Codebeamer Copilot focuses on requirements authoring and analysis for the flagship Codebeamer Application Lifecycle Management (ALM) solution. This AI-powered agent, being used by Volkswagen Group, improves the efficiency of the design phase, helping to ensure potential issues with system requirements are identified and addressed early in the process and a productivity boost as users manage complex hierarchies of requirements.
• Bluestar PLM are leveraging Microsoft Copilot for Dynamics 365 to automatically generate summaries for an engineering object based on data both from Dynamics 365 and Bluestar PLM, and automatically generating item descriptions in multiple languages to make it easier to generate quotes, bills-of-materials (BOMs), invoices, and other documents in different languages.  

Accelerating product engineering and R&D 

Engineers use a range of complex solutions in product engineering when producing product designs from CAD, CAM, and CAE applications. This also involves creating and using many different data types, from 3D CAD and CAM files, to CAE simulation datasets, documents, specifications, and various knowledge repositories.   

The following are examples where customers and generative AI-powered partner solutions are helping to deliver value in accelerating product engineering and R&D with AI on the Microsoft Cloud: 

• HARTING reduced design time from weeks to minutes by introducing an AI-powered assistant fueled by Azure OpenAI Service and Microsoft Cloud for Manufacturing, interoperating with Siemens NX CAD for rapid design. This solution reduced configuration time by 95%, a significant improvement in efficiency and the rapid creation of custom electrical connector prototypes that are speeding up time-to-market.
• Hexagon AI-powered automated CAM programming solution, ProPlanAI, reduces the time taken to program factory machine tools by 75%. This solution is part of Hexagon’s cloud-based Nexus connectivity and collaboration platform for discrete manufacturers, and is powered by Azure OpenAI Service, Microsoft Azure Cosmos DB, and Microsoft Azure Databricks.
• Siemens copilot for NX X software uses an adapted industry AI model to help users ask natural language questions, access technical insights, and streamline design tasks for faster product development. It provides CAD designers with AI-powered recommendations and best practices to optimize the design process within the CAD experience, aiding engineers in implementing best practices quickly, ensuring high-quality results from design to production.
• Rescale is transforming engineering innovation by integrating AI-powered tools with Microsoft technologies to enhance simulation data workflows with Rescale Automations, automating data processing for real-time insights, improving decision-making and collaboration with AI models including Phi-4 to reduce cycle times and costs while maximizing simulation insights.
• Siemens has announced an industrial foundational model (IFM) to enhance the productivity of engineering and automation tasks across the industrial sector. For example, it will help engineers automate CAM programming with context-aware recommendations, support Structured Control Code (SCL) generation and accelerate the creation of Process Flow Diagrams (PFDs) and Process and Instrumentation Diagrams (P&ID). The IFM is built on Microsoft’s Azure platform. 

The next step: Unlock innovation in product engineering with AI-powered digital threads 

The next stage in revolutionizing product engineering and R&D sees the addition of multi-agent AI systems that can orchestrate, collaborate, and scale across complex enterprise workloads, including product engineering solutions, supply chain, manufacturing execution systems, customer relationship management, field service, and enterprise resource planning.   

Microsoft, along with partners like PTC, Autodesk, and Aras, believe that digital threads are becoming a reality for industrial customers due to unified data foundations and generative AI. Unified data foundations make data usable by securely sourcing it from various systems and automating contextualization. Generative AI agents use this data to provide insights and take actions, unlocking numerous use cases across the manufacturing value chain, including product engineering, all through unified data foundations and generative AI.  

The following are several such examples of innovations that are fueling the emergence and promise of AI-powered digital threads: 

• Aras InnovatorEdge is a new low-code API management framework for extending product digital thread ecosystems, which will also integrate with Microsoft Fabric, Microsoft 365 Copilot, and Microsoft Cloud for Manufacturing, enabling seamless connectivity for advanced analytics and AI-powered insights.
• Autodesk Fusion connects people, data, and process through the product development lifecycle. Autodesk Data Solutions in Fusion Manage and Microsoft Fabric enable data management and process optimization. Additionally, Autodesk’s digital twin offerings through Tandem, factory simulation through FlexSIM, and factory operations management with Fusion Operation all benefit from this collaboration across the IT and operational technology (OT) ecosystem.
• PTC is collaborating with Microsoft on an enterprise data framework and agentic model for PLM scenarios in PTC Windchill within Microsoft Fabric to accelerate manufacturers digital thread strategies and unlock insights and workflows across the value chain using AI-powered agents.
• Toyota is deploying AI agents to harness the collective wisdom of engineers and innovate faster and more efficiently in a system named “O-Beya,” or “big room” in Japanese. The “O-Beya” system currently has nine AI agents—from a Vibration Agent to a Fuel Consumption Agent, bringing together numerous functional experts.  

By using Microsoft Cloud for Manufacturing and AI-powered solutions from our partner ecosystem, manufacturers can securely unlock new levels of impact. The integration of AI-powered solutions and AI agents unlocks innovation, reduces costs and improves operational efficiencies, meaning manufacturers are better equipped to navigate challenges and seize opportunities.    

Microsoft in manufacturing and mobility industries 

Learn more about Microsoft Cloud for Manufacturing and Microsoft for automotive, and how companies are using Microsoft AI capabilities in Microsoft AI in Action. 

Learn more about the unique use cases and solutions driving innovation in product engineering and R&D from our presence at Hannover Messe 2025.

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¹ IDC Research, Investing in Product Engineering — Increase Revenue and Decrease Cost, Doc # US51892224, February 2025. 

The post Shaping the future of product engineering and research and development with generative AI appeared first on Microsoft AI Blogs.

While cloud adoption is accelerating, many OT systems, such as Supervisory Control and Data Acquisition (SCADA), Energy Management Systems (EMS), Distributed Energy Resource Management Systems (DERMS), and Outage Management Systems (OMS), require hybrid architectures to ensure operational continuity, compliance, and secure integration with real-time grid control.

The challenge is clear: how do energy providers unlock the full potential of the cloud while helping to ensure mission-critical operations remain secure, resilient, and interoperable with legacy infrastructure?

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Adaptive cloud: The bridge between IT, OT, and AI-powered intelligence

The Microsoft adaptive cloud approach provides a seamless, scalable, and secure framework for unifying on-premises, edge, and cloud environments. Rather than forcing a one-size-fits-all migration to the cloud, the Microsoft adaptive cloud integrates IT and OT seamlessly, bringing together on-premises control systems and edge intelligence with cloud-scale analytics. Instead of forcing a binary choice between on-premises versus cloud, adaptive cloud supports energy providers to:

• Integrate on-premises systems with cloud-driven intelligence while meeting global compliance and sovereignty requirements.
• Utilize complex AI algorithms and real-time data streaming to unlock operational efficiencies, increase resilience, and enhance reliability.
• Strengthen cybersecurity with built-in Zero Trust protections and industry-aligned security frameworks.
• Support edge computing for localized grid control while harnessing the cloud’s computational power.

At Microsoft, we’re working with energy leaders around the world to implement this adaptive cloud approach that unites and integrates siloed teams, distributed sites, and operational systems into a unified model for operations, security, applications, and data. With a foundation built on Microsoft Azure and spanning more than 60 public cloud regions, our approach supports energy providers to utilize cloud-native and AI capabilities across the enterprise while bringing together IT and OT systems to accelerate energy production and help teams manage increasingly complex environments more efficiently.

Meeting growing demand while driving critical efficiencies

As population growth and rapidly changing markets continue driving demand for energy, industry leaders are faced with immense pressure to not only provide secure, equitable, and sustainable energy, but to optimize every aspect of business for continued growth. The Microsoft adaptive cloud environment sets the stage for critical improvements that help energy companies keep up with demand without overextending their own resources. These improvements include:

• Secure integration of cloud AI with critical OT systems. Many grid control systems such as SCADA, EMS, and DERMS must interact with real-time operational data while helping to ensure security and compliance. The Microsoft adaptive cloud supports these systems to securely connect to cloud-based AI and analytics without disrupting mission-critical workflows.
• Enhanced security. The increasing sophistication of cyber threats makes security a non-negotiable priority. Supporting an adaptive cloud-based environment is a critical step in improving security measures and allowing quick responses, helping to ensure that energy systems are protected against evolving cyber threats. Real-time OT and IT threat detection is an imperative going forward.
• Faster data analytics. Energy operators require high-speed decision-making, but traditional OT systems often rely on static models that struggle to adapt to real-time fluctuations. Running enterprise systems in Azure facilitates faster, more informed decision-making based on real-time data and supports cloud-based, high-speed analytics that ingest, process, and visualize terabytes of operational data from the grid. These data-driven insights can be applied to predictive maintenance, which helps reduce unplanned downtime and mitigates related operational expenses. Applying AI capabilities on top of analytics can supercharge the value of enterprise data, saving time and empowering decision-makers with actionable information.
• Compliance with global regulatory and data sovereignty requirements. Energy companies navigate a complex web of regional regulations, including:
  • NERC CIP (North America)—critical infrastructure protection for utilities
  • GDPR (European Union)—data privacy and protection regulations
  • Schrems II Ruling (European Union)—restrictions on data transfers from the EU to third countries
  • ISO 27001 & IEC 62443—international cybersecurity frameworks for industrial control systems

• Edge computing for low-latency control and decision-making. Certain grid operations require millisecond response times, making local processing at the substation or field level critical. Adaptive cloud allows real-time decision-making at the grid edge while still syncing with cloud-based AI for broader optimization.
• Increased scalability and flexibility. An adaptive cloud also supports energy providers to remain agile with changing demands and adopt new technologies that can easily integrate with current infrastructure investments.

Global energy leaders unlock new value with Azure

Microsoft collaborates with energy customers to unearth insights that help them make better, faster decisions and optimize efficiencies across the enterprise. For many, that starts with introducing cloud solutions that make it easier to collect and organize data. But data regulations, legacy on-premises systems, and a growing number of applications to manage are just a few challenges that pop up along the way. Below are two recent examples of how Microsoft has worked with energy leaders to address these and other challenges.

Uniper: Standardizing IT and OT with a hybrid cloud strategy

Uniper, the world’s largest power generation company, wanted to introduce cloud solutions but faced strict regulations around where certain applications could operate depending on the type of data involved, making it difficult for the IT team to manage all applications in a uniform, secure way. Their solution:

• Microsoft Azure Arc and Microsoft Azure Monitor created a single dashboard for managing applications across cloud and on-premises environments.
• Microsoft Azure Stack HCI allowed hybrid use of cloud services while helping to ensure compliance with European data regulations.

With this adaptive cloud strategy, Uniper can now manage IT and OT environments in a standardized way, launch new services faster, and optimize performance without disrupting critical infrastructure. This translates to launching orders more quickly, bringing new services to market faster, and building new systems with just a few clicks.

Emirates Global Aluminum (EGA): AI-powered edge intelligence for industrial operations

EGA is another energy leader that turned to Azure to pave a path for sustainable, scalable infrastructure. EGA’s on-premises environment couldn’t deliver the level of flexibility needed to manage increasingly complex and data-intensive operations with scalable computing infrastructure. EGA needed a hybrid cloud approach to support real-time AI and analytics across its energy-intensive operations. To address this challenge, the company deployed a hybrid environment managed by Azure Arc. The new environment allowed EGA to connect private cloud services through on-premises datacenters—which host operational data, quality control data, environmental and energy data, and supply chain and market data—with the public cloud. This helped optimize latency, support advanced AI and automation solutions, and offer sustaining commercial savings by applying intelligence at the edge. It also streamlined processing for massive amounts of real-time readings from sensors, machinery, and production lines.

Using an adaptive cloud approach went a long way in helping EGA accelerate industrial AI use cases and improve production processes. The company experienced 10 to 13 times faster AI response time, lower latency, and 86% cost savings associated with AI image and video use cases. They also developed and trained a model on 100,000 images to define and differentiate between what makes a good anode and what makes a bad one, ultimately helping to improve the overall quality of their aluminum production.

An adaptive cloud approach to power a sustainable energy future

As enterprises from across all industries aim to reduce their carbon footprint through more efficient, sustainable practices, there’s little doubt that all eyes are on the energy industry to lead the way. Microsoft is proud to be recognized as a Leader in the 2024 Gartner® Magic Quadrant™ for Distributed Hybrid Infrastructure (DHI), placing Microsoft Furthest and Highest in Completeness of Vision and Ability to Execute. Microsoft offers an adaptive cloud approach and can help energy companies make real progress toward a resilient and sustainable future by setting the stage for significant value-adds like improved data management and generative AI capabilities. Collectively, these improvements help strengthen security posture, simplify management of applications, improve operational performance, and, critically, reduce carbon footprint.

By partnering with Microsoft, global energy providers can:

• Unify IT and OT systems across on-premises, edge, and cloud for seamless integration.
• Meet global regulatory and compliance requirements while maximizing cloud capabilities.
• Enhance cybersecurity with real-time threat detection and Zero Trust protections.
• Scale AI and analytics to energy infrastructure, reduce downtime, and improve efficiency, reliability, and resilience.

By embracing adaptive cloud, energy providers can future-proof their operations, strengthen cybersecurity, and build the resilient energy systems of tomorrow—without compromising compliance, security, or operational continuity.

We’re here to support customers and partners along the way, as we all look to accelerate the energy transition and build a sustainable energy future for the next generation.

Explore more energy solutions and resources

• Read the Microsoft Industry Blogs: Energy and resources to learn about themes and actions critical for energy transition.
• Learn how to achieve more in the energy and resources industry with trusted data and AI solutions from Microsoft.
• Check out the on-demand recording of our recent webinar, AI Transformation in Energy, to learn how data and AI are driving change across the industry.

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, Magic Quadrant is a registered trademark of Gartner, Inc. and/or its affiliates and is used herein with permission. All rights reserved. 

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. 

The post Unifying on-premises, edge, and cloud data with Microsoft appeared first on Microsoft AI Blogs.

AI innovation is a critical component of delivering more energy with less emissions—and combined with strategic partnerships and collective action, it’s a way to supercharge change. The World Energy Council elevates the idea of “Humanizing Energy” as its visionary foundation for transitioning the world away from fossil fuels. But change of this magnitude will be complex. According to the World Energy Council, humanizing energy involves “more people and diverse communities in understanding their roles and choices and remaining realistically hopeful about making progress by enabling hundreds and thousands of smaller steps along multiple, diverse pathways.”²

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At Microsoft, we believe that change happens through collective progress that brings people and technology together. Even as enterprise data management and AI solutions become key enablers for successful digital transformation, we can’t lose sight of the importance of keeping people and communities engaged. When people are actively involved in modernizing the processes, workflows, and tools they use every day, they’re empowered to not only work more efficiently but to recognize all the new opportunities and roles they play in supporting a more sustainable energy future.  

There are countless applications of AI in energy operations and workforce transformation, all of which can add up to big change. This blog explores just some of the industry-leading AI innovations and steps we can take to advance the global energy transition together.  

Protecting and strengthening critical infrastructure and energy operations 

Many energy systems today, especially power and utilities infrastructure, are prone to persistent cyberattacks. Left unresolved, security risks can quickly spiral and complicate already-existing issues like technical debt, tool fatigue, and employee burnout. It’s a prime example of how technology can enhance human capabilities to create a secure energy supply. Several of the industry leaders we work with are leveraging generative AI to streamline security processes and improve security posture, allowing their security personnel to focus on the highest-priority work. For example, international power company Uniper relies on Microsoft Security Copilot to help their IT security personnel work smarter and faster. Microsoft Security Copilot immediately flags potential incidents, allowing them to identify and address risks up to twice as fast. It also helps them manage access and quickly compile new emergency plans based on current drafts. It can even create a list of inactive devices that pose potential security risks.  

Uniper is just one of the many energy companies that keep critical services secure with a platform powered by the Microsoft Cloud. We continue working with industry leaders to secure the global energy supply, leveraging the enormous potential of data and AI to optimize systems and reduce emissions for a more resilient and secure digital energy ecosystem.   

Improving frontline worker productivity and safety with real-time insights 

The world runs on the products and services provided by millions of energy and resources workers. As the industry grapples with changing customer demands and pressures to reduce emissions, the workforce is undergoing a transformational shift to better accommodate these needs. But they also face gaps in areas like skilling and productivity that require strategy and innovation to overcome.  

AI-powered tools like Microsoft 365 Copilot empower workers with the right information at the right time. Industry leaders like TotalEnergies are using Microsoft 365 Copilot to help workers be more efficient and productive, with every employee receiving AI training throughout the past year. Another energy leader, Petrobras, uses AI technology from Azure OpenAI Service to power its custom text generation tool used by more than 110,000 employees. The tool helps democratize AI in a secure, compliant way and enables employees to perform their work in less time and with less manual labor. In yet another example, Repsol, a global multi-energy provider, is reaping the benefits of AI capabilities with a study showing that its adoption of Microsoft 365 Copilot has helped employees with productivity gains of up to 121 minutes per week, with nearly 62% of employees reporting reluctance to return to work without access to Microsoft 365 Copilot. What’s more, the company reduced procurement costs by 15% while observing a 16% increase in deliverable quality.³ 

It’s clear from these examples that AI is a game changer when it comes to empowering the energy workforce. By connecting workers with purpose-built tools and experiences, energy companies can set the stage for maximizing productivity and working in new, flexible ways.  

Enhancing energy supply with real-time monitoring and predictive maintenance  

When it comes to the energy business, even a fraction of a percentage in efficiency can make a significant difference in providing a reliable, high-quality supply. Advanced data and AI solutions can pull together and organize vast amounts of disparate enterprise data, enabling energy suppliers to more effectively monitor operations, forecast production, and predict maintenance requirements.  

Enerjisa Üretim, for example, built a remote operations center that leverages advanced analytics powered by Microsoft Azure. The powerful data processing allows the company to monitor its 20 hydropower, wind, and solar plants every day and provide timely response to any operational or production issues. Enerjisa Üretim has also developed a tool that uses Azure OpenAI Service to access and analyze its Internet of Things (IoT) data from more than 40,000 datapoints and combine it with operational data to increase efficiency and streamline processes across power plants—ultimately reducing the data collection and analysis time from hours to seconds. The company also uses generative AI capabilities to forecast daily power generation for turbines by analyzing factors like asset condition, weather, and wind speed. The AI capabilities provide immediate answers and offer more flexibility when it comes to staffing multiple experts for every project. 

Accelerating research and modeling with insights and intelligent search  

High-quality data and advanced analysis capabilities are essential for the energy and resources industry. In mining, for instance, these are needed to create the 3D models necessary for accurate and efficient mineral recovery. The process of preparing the data, however, can be extremely time-consuming, as geologists must sift through massive volumes of documents that have often been accumulated over the course of several decades. Now, mining leaders are leveraging Microsoft AI technology to accelerate intelligent search velocity and accuracy across the large geological data sets they use.  

We recently worked with a mining industry leader to implement a solution built with Azure OpenAI and Azure AI Document Intelligence. The solution automates data extraction and storage, elevates the most relevant information, and produces critical insights quickly through a generative AI bot, ultimately enhancing accessibility and interpretation of geological, geophysical, and other data for users of all experience levels. Streamlining this process helps them create 3D models faster by significantly reducing the time spent searching and preparing data—from weeks down to just minutes. These overall productivity gains free up time to increase recovery, reduce waste, and improve safety and cost-efficiency.         

Streamlining permitting and automating complex utility rate case workflows  

In the energy and resources industry, permitting and rate case processing are common and necessary to adhere to important legal, financial, and environmental compliance and regulatory requirements. They can also be extremely costly and time-consuming, especially for nuclear energy permitting, which requires unique expertise and can often take many years and tens of millions of dollars to complete, and for complex utility rate cases, which require detailed data sources and documentation.

Generative AI can significantly reduce the time and costs associated with permitting and rate case processing. In a recent example of AI design innovation, Microsoft’s energy and resources industry team worked with Neudesic, an IBM Company, to develop a rate case assistance accelerator to streamline processes for leading utilities worldwide. The AI-powered solution significantly reduces the time and costs associated with internal processes, resulting in up to 22% productivity gains and saving up to USD45,000 in operational costs per document. With time and monetary savings, energy companies can focus on higher-value business goals, reliability, and customer service.    

Finding information faster with AI agents 

As AI becomes more prevalent across global industry operations, we’re increasingly seeing the benefits and vast potential for supercharging productivity. AI agents, for example, can help users find the right information faster, and they can execute a specific set of tasks, allowing workers to spend more time on innovative and creative work. This will be a gamechanger.

In December 2024, the International Energy Agency (IEA) announced a new AI agent, currently in beta testing, that helps users explore the 2024 edition of the World Energy Outlook. The GPT tool, built on Microsoft Azure using Microsoft Copilot Studio, answers questions using natural language and helps readers quickly locate data and information of interest. AI agents like this one don’t just save time—they also make information more accessible to more people. That means you don’t need to be a data scientist or energy expert to interact with and understand reports and other scientific documentation. Instead, a reader can simply type a question using conversational language, and the AI models—trained on the industry terminology and relevant documentation—can provide user-friendly and fast responses.    

Explore more AI innovation in energy 

At Microsoft, we’re committed to working with the global energy industry to accelerate the energy transition and enable a more secure, reliable, equitable, and sustainable future. Through our cloud-based data and AI solutions, energy leaders can accelerate their digital transformation to maximize value across their entire enterprise—and we’re here to support along the way. You can check out our additional resources to learn more about working with the Microsoft energy and resources industry team. 

• Read the Microsoft Industry Blogs: Energy and resources to learn about themes and actions critical for energy transition.
• Learn how to achieve more in the energy and resources industry with trusted data and AI solutions from Microsoft.
• Explore innovation in sustainability through our publication, For Life on Earth.
• Learn about Microsoft security solutions. 

¹ Peak energy emissions: A historic moment overshadowed by the endurance of fossil fuels, World Economic Forum, November 2024.

² World Energy Trilemma 2024: Evolving with Resilience and Justice, used by permission of the World Energy Council, 2024.

³ MIT Technology Review, Impact of generative AI adoption on efficiency, quality and employee experience in a global energy company.

The post Charting a new energy future with AI innovation and collective action appeared first on Microsoft AI Blogs.

These initiatives focus on harnessing data insights from smart technologies such as automation, Internet of Things (IoT), and AI, to improve how products are made and distributed. By unifying this and other data—including siloed data sets—into a single ESG data estate, manufacturing organizations can gain holistic views and granular insights to help them not only meet ESG reporting requirements, but also drive the sustainability of sourcing, making, transporting, and disposing of products—and implement business practices that advance a circular economy.  

To support your organization as you explore options and identify cost-effective steps in this era of industrial transformation, we’ve gathered learnings and recommendations into the Leader’s Guide to Sustainable Business Transformation. We’ve also created an ESG data readiness assessment to help you get started quickly. 

A more responsible, competitive path forward 

Manufacturing and mobility organizations that develop smart, automated, and data-driven processes as part of industrial transformation—and incorporate sustainability into those processes—are well positioned to gain a competitive advantage. ESG insights can help manufacturers achieve a range of goals across the value chain, such as:  

• Improved risk management and the protection of critical production processes.
• Engagement with vendors and suppliers to address Scope 3 emissions, reduce exposure to impacts from climate risks, and governance loopholes.
• Reduced costs and improved traceability with streamlined technology resources.
• More responsible capital deployment.  

With advanced solutions, organizations have already begun making these improvements. For example, Sandvik, a leader in mining industry manufacturing, implemented Microsoft AI and cloud technologies to enhance predictive maintenance and lower emissions, allowing them to cut down on waste and optimize resource use. 

ESG data: The input that fuels comprehensive sustainability 

To achieve the full potential of ESG data—from the shop floor to the board room—manufacturing and mobility organizations can benefit from evaluating sustainability comprehensively, in terms of environmental concerns as well as social and governance impacts. This approach uses ESG data insights to improve risk management and protect the value of critical product processes, and to make decisions that improve energy use, labor practices, supply chain transparency, regulatory compliance, and more.  

For example, Outokumpu, a worldwide leader in stainless steel production, tapped into the power of data by developing an industrial digital platform based on Microsoft Azure. The insights this platform provided led to significantly reduced waste (due to fewer defects) and energy usage—contributing to lower CO2 emissions. 

Key ways to maximize the benefits of ESG data in manufacturing and mobility include: 

• Build a data-driven infrastructure: ensure that systems are in place to collect and integrate accurate ESG data seamlessly across all departments.
• Leverage predictive insights: use AI and analytics to forecast and optimize operations, including by using natural language querying to enable all teams to access insights—enabling efficient resource use and proactive risk management.
• Foster a culture of sustainability: from executives to front-line workers, train employees in how ESG data can improve decision-making and drive sustainability outcomes. 

Implementing these ideas can provide the foundation for using ESG data to drive long-term success, and to make significant improvements relatively quickly. For instance, Nordic-based OSTP Group, which specializes in manufacturing stainless steel products and custom equipment, is using Microsoft technologies to track and report CO2 emissions. The data insights they gained led to a 70% reduction in direct CO2 emissions from 2021 to 2023. 

Schneider Electric, a global leader in energy management and industrial automation, has also reduced carbon emissions and optimized energy use—leveraging Azure OpenAI and other Microsoft AI technologies to boost not only sustainability, but also their engineers’ productivity. 

How Microsoft is powering sustainable transformations  

Microsoft has emerged as a leading partner for manufacturing and mobility organizations on their journey toward sustainability. We’ve designed our solutions to help businesses in three primary ways: 

1. Improve ESG data transparency: We’re continuously innovating to enable our customers to glean consolidated data intelligence from across their operations and value chain.
2. Deliver actionable insights: Microsoft has a deep slate of expertise helping manufacturers maximize operational efficiencies using sensor-enabled data management and automated scenarios powered by the Microsoft Cloud.
3. Create new opportunities: We are a global leader in enabling digital transformation through our data and AI solutions, to help businesses grow while becoming more sustainable. 

We’re delivering for these solution areas by bringing together a growing set of ESG data and AI capabilities from Microsoft and our global ecosystem of partners, in Microsoft Cloud for Sustainability.  

A core solution in this suite is Microsoft Sustainability Manager, which allows businesses to more easily record, report, and reduce their environmental impact through data connections and powerful AI-powered analytics—and can be integrated with virtually any business system. With this solution, manufacturing and mobility teams advance on carbon, water, and waste management, as well as circularity.  

Businesses can also implement the purpose-built ESG capabilities of Sustainability data solutions in Microsoft Fabric, to integrate, normalize, and analyze ESG data—and other enterprise data—on a single digital platform. Together, these capabilities help improve ESG data accuracy and transparency, simplify reporting processes, and accelerate progress toward goals.  

Swedish forestry giant Södra is showing what’s possible with these capabilities. Södra utilizes Microsoft Sustainability Manager to improve supply chain transparency and track sustainability data across its entire operation, allowing them to reduce reliance on carbon-intensive materials, displacing 8.8 million tons of CO2 emissions annually. Södra estimates the positive impact of this accomplishment as equivalent to one-fifth of Sweden’s annual reported carbon emissions. 

A sustainable future begins with smarter solutions 

As manufacturing and mobility continues to transform, both smart technologies and ESG data will help companies drive sustainability, meet compliance and reporting requirements, and uncover new opportunities for growth. Microsoft is here to help organizations make the transition with solutions to help reduce their environmental impact, improve operational efficiency, and position themselves for long-term success in a rapidly changing world. To gain a view of your ESG data across key areas, as well as customized guidance on how to drive sustainability progress and add business value, complete our readiness assessment.

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The post Data is driving a more sustainable industrial transformation appeared first on Microsoft AI Blogs.

In the case of AI, it is absolutely true that the industry is moving incredibly fast and evolving quickly. It’s also true that hundreds of thousands of customers are using Microsoft AI technology today and, by making early bets on the platform, are seeing big benefits now and future-proofing their ability to benefit from the next big wave of AI improvements.

Microsoft Ignite is our annual event that spotlights the updates and creations that enable customers, partners and developers to unleash the full potential of Microsoft’s technology and change the way we approach work.

This year, we are announcing about 80 new products and features, including new capabilities in Microsoft 365 Copilot, additions to the Copilot + AI stack and new Copilot+ devices offerings. Underpinning each of these innovations is our commitment to security. Since launching our Secure Future Initiative (SFI) one year ago, we have made security the No. 1 job of every employee at Microsoft, dedicated 34,000 engineers to this focus and, at Ignite, we will announce innovations that are rooted in our SFI principles: secure by design, secure by default and secure operations.

More than 200,000 people have registered to join us for this year’s Ignite, with more than 14,000 attendees at our in-person events in Chicago. Attendees can choose from more than 800 sessions, demos and expert-led labs from Microsoft and our partners. Most of the Ignite content will be available on demand for those who can’t attend the live event.

Copilot momentum

Microsoft 365 Copilot is your AI assistant for work, and we have seen the momentum grow as more organizations are moving to Copilot and deploying it to great success. All up, nearly 70% of the Fortune 500 now use Microsoft 365 Copilot.

That echoes an industry trend: A recent IDC study showed that generative AI is on the rise, with 75% adoption among companies surveyed in 2024. In addition, for every $1 invested, companies are realizing a return of $3.70, and leaders are saying they are realizing as much as a $10 return, according to the study.

The investments that Microsoft has made in Copilot are paying dividends for our customers.

We recently highlighted some of the more than 200 customer stories of accelerated AI Transformation, with Copilot helping many of them spark innovation and transform their organization for the better. Several examples include:

• Intelligent power management company Eaton leveraged Microsoft 365 Copilot to help streamline and automate operations, improve data access, centralize knowledge and empower teams to focus on higher-value tasks. One immediate challenge addressed through Copilot focused on the manual, time-consuming documentation process in Eaton’s Finance operations. Copilot helped Eaton document over 9,000 standard operating procedures (SOPs), resulting in an 83% time savings for each SOP.
• Consulting firm McKinsey & Company is creating an agent to speed up the client onboarding process. The pilot showed lead time could be reduced by 90% and administrative work reduced by 30%. The agent automates complex processes, such as identifying the right expert capabilities and staffing teams and acts as a single place where colleagues can ask questions and request follow-ups. By streamlining tasks and reducing manual inputs, this agent could potentially save consultants many hours, allowing them to spend more time with clients.

Boosting productivity with Microsoft 365 Copilot

Microsoft is continuing to supercharge productivity with new capabilities in Microsoft 365 Copilot designed to help simplify the workday.

Copilot Actions, now in private preview, enable anyone to automate everyday tasks with simple, fill-in-the-blank prompts, whether it’s getting a daily summary of meeting actions in Microsoft Teams, compiling weekly reports or getting an email upon return from vacation that summarizes missed meetings, chats and emails.

Anyone can easily set up Actions right in their Microsoft 365 app, allowing users to focus on more impactful work, save time and boost productivity.

New agents in Microsoft 365 are designed to help scale individual impact and transform business process. At Ignite we will introduce:

• Agents in SharePoint: These natural language AI assistants are grounded on relevant SharePoint sites, files and folders to make it easy to find answers from that content, and to make quicker decisions as a result. Now generally available, every SharePoint site will include an agent tailored to its content. Users can also create customized agents scoped to select SharePoint files, folders or sites with as little as one click.
• Interpreter: This agent in Teams helps users overcome language barriers by enabling real-time, speech-to-speech interpretation in meetings. Available in public preview in early 2025, meeting participants will also have the option to have the agent simulate their personal voice.
• The Employee Self-Service Agent: An agent available in private preview in Business Chat expedites answers for the most common policy-related questions and simplifies action-taking on key HR and IT-related tasks — like helping employees understand their benefits or request a new laptop. It can be customized in Copilot Studio to meet an organization’s unique needs.
• Other agents in public preview take real-time meeting notes in Teams and automate project management from start to finish in Planner.

Copilot + AI Stack

The Copilot stack empowers users to build more ambitious products by leveraging advanced technology at each layer of the stack. To create a unified experience where customers can design, customize and manage AI applications and agents, we are introducing Azure AI Foundry, which gives customers access to all existing Azure AI services and tooling, plus new capabilities like:

• Azure AI Foundry SDK, now available in preview, provides a unified toolchain for designing, customizing and managing AI apps and agents with enterprise-grade control and customization. With tools that help organizations responsibly scale their applications, Foundry also provides 25 prebuilt app templates and a simplified coding experience they can access from familiar tools like GitHub, Visual Studio and Copilot Studio.
• Azure AI Foundry portal (formerly Azure AI Studio), now available in preview, is a comprehensive visual user interface to help developers discover AI models, services and tools. With a new management center experience that brings essential subscription information into a single dashboard, the portal also helps IT admins, operations and compliance teams manage AI applications at scale.
• Azure AI Agent Service, coming soon to preview, will enable professional developers to orchestrate, deploy and scale enterprise-ready agents to automate business processes.

We also continue to back up our Trustworthy AI commitments with new tools. Today we’re announcing AI reports and risk and safety evaluations for images to help organizations ensure AI applications are safe and compliant. AI reports will help organizations improve observability, collaboration and governance for AI apps and fine-tuned models, while evaluations for image content will help customers assess the frequency and severity of harmful content in their app’s AI-generated outputs.

Copilot+ devices

As organizations move more workloads to the cloud to enhance security and flexibility, Microsoft is expanding its Cloud PC solution by introducing the first in a new class of devices purpose-built to connect securely to Windows 365 in seconds.

Windows 365 Link is the simple, secure, purpose-built device for Windows 365. It is in preview now and will become generally available for purchase starting in April 2025 in select markets with an MSRP of $349, allowing users to work securely in a familiar Windows desktop in the Microsoft Cloud with responsive, high-fidelity experiences.

Windows 365 Link is secure by design. The device has no local data, no local apps and admin-less users so corporate data stays protected within the Microsoft Cloud.

Other new capabilities for Copilot+ PCs for commercial customers include harnessing the power of inbuilt native processing units (NPUs) to deliver local AI. With improved Windows Search, and the new Recall experience (preview), finding what you need on your PC is easier than ever by just describing what you are looking for. These features are releasing first to our Windows Insider community on Copilot+ PCs before rolling out more broadly to our customers.

BlackRock momentum

Four years ago, BlackRock, one of the world’s pre-eminent asset management firms, formed a strategic alliance with Microsoft to move its Aladdin platform to Microsoft Azure. With this foundation on Azure, BlackRock rolled out generative AI tools for global clients with Aladdin Copilot. Through generative AI, Aladdin Copilot serves to strengthen the connective tissue across the platform, leveraging Microsoft technology to help users receive answers instantly to unlock new efficiencies and discover important business insights even faster. Aladdin Copilot makes BlackRock’s Aladdin platform even more intelligent and responsive. That results in enhanced productivity, enables scale and keeps users more informed.

BlackRock’s move to Azure and launch of Aladdin Copilot are just two of the many ongoing milestones in a long-term partnership that also includes an enterprise-wide deal for 24,000 seats of Microsoft 365 Copilot. Today, about 60% of BlackRock’s Copilot user population is leveraging Copilot on a weekly basis. Additionally, BlackRock also recently made the choice to move its on-prem CRM solution to the cloud with Dynamics 365, citing its native integration with Teams and Outlook as one of its primary decision-making factors.

Strength in security

We know that the threat landscape is rapidly evolving, and it’s imperative that we stay ahead of bad actors. At Microsoft we believe that security is a team sport, and we are stronger when we partner as a security community to share information, collaborate and stop bad actors.

In that spirit, and as part of our Secure Future Initiative (SFI), at Ignite we are announcing the largest public security research event in history: the Zero Day Quest. This event, which focuses on AI and cloud security, will offer the largest award pool in the industry at $4 million, in addition to our existing $16 million annual bounty program. This competition aims to attract the world’s best security minds to tackle high-impact scenarios critical to our customers’ security, with award multipliers, starting today.

As the threat landscape has changed, we have seen rapid evolution in the way attackers exploit weaknesses within systems — particularly by navigating graph relationships between identities, files and devices to uncover attack paths. Attackers thinking in graphs cause wider damage from the first point of intrusion. Traditional security products, with limited visibility into these graph relationships, are often better suited to protect specific devices or mediums — like laptops or inboxes — rather than the full scope of potential attack surface.

Today’s Microsoft Security Exposure Management launch is a pivotal step in transforming cybersecurity with savvy data and AI-based strategies. The power of incorporating Microsoft graph data, in context with data from customers’ other third-party security tools, creates a powerful single pane of glass to visualize attack paths before threat actors do. With computing power and cloud-scale performance to distill powerful real-time mapping of assets and evolving risks, Exposure Management assists security teams in preventing intrusions and provides IT, operations and risk leaders with real-time data to support cyber risk decision-making.

This is only a small section of the many exciting features and updates we will be announcing at Ignite. As a reminder, you can view keynote sessions from Microsoft executives including Satya Nadella, Rajesh Jha, Scott Guthrie, Charlie Bell and Vasu Jakkal, live or on-demand.

Plus, you can get more on all these announcements by exploring the Book of News, the official compendium of all today’s news.

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Today, we’re announcing adapted AI models, expanding our industry capabilities and enabling organizations to address their unique needs more accurately and effectively. In collaboration with industry partner experts like Bayer, Cerence, Rockwell Automation, Saifr, Siemens Digital Industries Software, Sight Machine and more, we’re making these fine-tuned models, pre-trained using industry-specific data, available to address customers’ top use cases.

Underpinning these adapted AI models is the Microsoft Cloud, our platform for industry innovation. By integrating the Microsoft Cloud with our industry-specific capabilities and a robust ecosystem of partners, we provide a secure approach to advancing innovation across industries. This collaboration allows us to create extensive scenarios for customers globally, with embedded AI capabilities — from industry data solutions in Microsoft Fabric to AI agents in Microsoft Copilot Studio to AI models in Azure AI Studio — that enable industries to realize their full potential.

Introducing adapted AI models for industry

We’re pleased to introduce these new partner-enabled models from leading organizations that are leveraging the power of Microsoft’s Phi family of small language models (SLMs). These models will be available through the Azure AI model catalog, where customers can access a wide range of AI models to build custom AI solutions in Azure AI Studio, or directly from our partners. The models available in the Azure AI model catalog can also be used to configure agents in Microsoft Copilot Studio, a platform that allows customers to create, customize and deploy AI-powered agents, which can be applied to an industry’s top use cases to address its most pressing needs.

• Bayer, a global enterprise with core competencies in the life science fields of healthcare and agriculture, will make E.L.Y. Crop Protection available in the Azure AI model catalog. A specialized SLM, it is designed to enhance crop protection sustainable use, application, compliance and knowledge within the agriculture sector. Built on Bayer’s agricultural intelligence, and trained on thousands of real-world questions on Bayer crop protection labels, the model provides ag entities, their partners and developers a valuable tool to tailor solutions for specific food and agricultural needs. The model stands out due to its commitment to responsible AI standards, scalability to farm operations of all types and sizes and customization capabilities that allow organizations to adapt the model to regional and crop-specific requirements.
• Cerence, which creates intuitive, seamless and AI-powered user experiences for the world’s leading automakers, is enhancing its in-vehicle digital assistant technology with fine-tuned SLMs within the vehicle’s hardware. CaLLM™ Edge, an automotive-specific, embedded SLM, will be available in the Azure AI model catalog. It can be used for in-car controls, such as adjusting air conditioning systems, and scenarios that involve limited or no cloud connectivity, enabling drivers to access the rich, responsive experiences they’ve come to expect from cloud-based large language models (LLMs), no matter where they are.
• Rockwell Automation, a global leader in industrial automation and digital transformation, will provide industrial AI expertise via the Azure AI model catalog. The FT Optix Food & Beverage model brings the benefits of industry-specific capabilities to frontline workers in manufacturing, supporting asset troubleshooting in the food and beverage domain. The model provides timely recommendations, explanations and knowledge about specific manufacturing processes, machines and inputs to factory floor workers and engineers.
• Saifr, a RegTech within Fidelity Investments’ innovation incubator, Fidelity Labs, will introduce four new models in the Azure AI model catalog, empowering financial institutions to better manage regulatory compliance of broker-dealer communications and investment adviser advertising. The models can highlight potential regulatory compliance risks in text (Retail Marketing Compliance model) and images (Image Detection model); explain why something was flagged (Risk Interpretation model); and suggest alternative language that might be more compliant (Language Suggestion model). Together, these models can enhance regulatory compliance by acting as an extra set of review eyes and boost efficiency by speeding up review turnarounds and time to market.
• Siemens Digital Industries Software, which helps organizations of all sizes digitally transform using software, hardware and services from the Siemens Xcelerator business platform, is introducing a new copilot for NX X software, which leverages an adapted AI model that enables users to ask natural language questions, access detailed technical insights and streamline complex design tasks for faster and smarter product development. The copilot will provide CAD designers with AI-driven recommendations and best practices to optimize the design process within the NX X experience, helping engineers implement best practices faster to ensure expected quality from design to production. The NX X copilot will be available in the Azure Marketplace and other channels.
• Sight Machine, a leader in data-driven manufacturing and industrial AI, will release Factory Namespace Manager to the Azure AI model catalog. The model analyzes existing factory data, learns the patterns and rules behind the naming conventions and then automatically translates these data field names into standardized corporate formats. This translation makes the universe of plant data in the manufacturing enterprise AI-ready, enabling manufacturers to optimize production and energy use in plants, balance production with supply chain logistics and demand and integrate factory data with enterprise data systems for end-to-end optimization. The bottling company Swire Coca-Cola USA plans to use Factory Namespace Manager to efficiently map its extensive PLC and plant floor data into its corporate data namespace.

We also encourage innovation in the open-source ecosystem and are offering five open-source Hugging Face models that are fine-tuned for summarization and sentiment analysis of financial data.

Additionally, last month we announced new healthcare AI models in Azure AI Studio. These state-of-the-art multimodal medical imaging foundation models, created in partnership with organizations like Providence and Paige.ai, empower healthcare organizations to integrate and analyze a variety of data types, leveraging intelligence in modalities other than text in specialties like ophthalmology, pathology, radiology and cardiology.

Accelerating transformation with industry agents

Microsoft also offers AI agents that are purpose-built for industry scenarios. Available in Copilot Studio, these agents can be configured to support organizations’ industry-specific needs. For example, retailers can use the Store Operations Agent to support retail store associates and the Personalized Shopping Agent to enhance customers’ shopping experiences. Manufacturers can use the Factory Operations Agent to enhance production efficiency and reduce downtime by enabling engineers and frontline workers to quickly identify and troubleshoot issues.

All this AI innovation wouldn’t be possible without a solid data estate, because AI is only as good as the data it’s built upon. By ensuring data is accurate, accessible and well integrated, organizations can unlock deeper insights and drive more effective decision-making with AI. Microsoft Fabric, a data platform built for the era of AI, helps unify disparate data sources and prepares data for advanced analytics and AI modeling. It offers industry data solutions that address each organization’s unique needs and allows them to discover, deploy and do more with AI.

At the forefront of addressing industry needs securely

At the core of our AI strategy is a commitment to trustworthy AI. This commitment encompasses safety, security and privacy, ensuring that AI solutions are built with the highest standards of integrity and responsibility. Trustworthy AI is foundational to everything we do, from how we work with customers to the capabilities we build into our products.

At Microsoft, we combine industry AI experience, insights and capabilities with a deep understanding of customer challenges and objectives. Along with a trusted ecosystem of experienced partners, we unlock the full potential of AI for each industry and business. Our goal is not just to offer or implement AI tools but to help customers succeed by embedding AI into the very core of what each industry does.

AI transformation is here, and Microsoft is at the forefront of this revolution. As we continue to navigate this new era of innovation, it’s clear that AI will play a pivotal role in shaping the future of business across all industries and that Microsoft will continue to lead the way. To learn more about how customers in a variety of industries are transforming with AI, visit How real-world businesses are transforming with AI.

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