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 The Microsoft Cloud Blog.

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-powered 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 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 The Microsoft Cloud Blog.

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 The Microsoft Cloud Blog.

What is a Frontier Firm?

Microsoft defines a Frontier Firm as a human-led but AI-operated organization that integrates AI agents as core team members—enabling rapid scaling, agile operations, and enhanced productivity through hybrid human-agent collaboration and on-demand intelligence.

Microsoft identifies four key pillars of AI transformation:

1. Enrich employee experiences: Empower people with AI tools that remove friction and unlock creativity.
2. Reinvent customer engagement: Deliver transparency, personalization, and trust at scale.
3. Reshape business processes: Automate and optimize operations for speed, safety, and sustainability.
4. Bend the curve on innovation: Move beyond pilots to bold, repeatable frameworks that accelerate transformation.

Microsoft mining and metals customers Ma’aden, Petrosea, and Outokumpu bring these pillars to life and drive efficiency, productivity, cost reduction, safety, and sustainability. I’ll talk more about each one below.

From reactive to proactive: How AI and agents transform mining operations

Frontier Firms are deploying AI and agents across the mining value chain—not just to automate tasks, but to enable supervised autonomous systems that can monitor, reason, and act. AI-powered innovations are already delivering measurable results. For example, BHP and Microsoft have partnered to use advanced AI and machine learning technologies to enhance copper recovery at the world’s largest copper mine. AI-powered systems adapt in real-time to more variability. This optimizes recovery rates, improves throughput, and grade control. It also reduces downtime, waste, water usage, energy consumption, and costs.

With AI and agents, mining companies are not only addressing today’s challenges but are also building resilience and agility for the future—empowering their workforce, optimizing operations, and accelerating progress toward sustainability and growth.

The Frontier Firm in action: Empowering people with Microsoft Copilot and agents

Ma’aden, a leading mining and metals company, aimed to transform into a Frontier Firm by using digital innovation and AI to stay competitive in a resource-intensive industry while supporting sustainability and growth.

The company faced pressure to modernize operations without disrupting workforce roles—balancing efficiency gains with its commitment to empower employees rather than replace them and ensuring adoption of AI tools aligned with cultural and operational needs.

Ma’aden deployed Microsoft 365 Copilot and agentic AI capabilities across workflows—integrating generative AI into collaboration and decision-making. The focus was on augmenting human expertise, enabling employees to automate routine tasks, and free time for strategic thinking.

The transformation improved productivity, saved time, and enriched employee experiences—positioning Ma’aden as a Frontier Firm in mining. Employees reported higher engagement and confidence, as AI functioned as a trusted assistant, not a substitute—driving faster decisions, better collaboration, and sustainable growth.

“We intentionally gave Copilot to early adopters—people who are excited about technology—because they would act as change agents for the rest of their teams.”

—Khalid AlMutairi, Vice President, IT at Ma’aden

Turning obstacles into intelligent opportunities

Petrosea, a leading Indonesian mining and energy services firm, faced intense price wars and operational inefficiencies. To sustain growth and environmental, social, and governance (ESG) commitments, it needed to differentiate beyond cost and embrace innovation.

Legacy batch processes and limited data access hindered real-time decision-making. Remote sites and rising sustainability requirements amplified complexity, requiring a shift to advanced digital capabilities for competitive resilience.

Petrosea launched its 3D strategy: diversification, digitalization, and decarbonization—deploying the Minerva Digital Platform on Microsoft Azure, integrating Internet of Things (IoT) sensors, predictive analytics, and digital twins. It adopted Microsoft Azure OpenAI, Copilot Stack, automation agents, and advanced security.

The company achieved a 15% increase in productivity, a 9% reduction in operational costs, improved safety, and was selected by the World Economic Forum to join its Global Lighthouse Network. Petrosea transformed adversity into innovation, building competitive differentiation as a Frontier Firm through AI-powered workflows.

The integration of IoT sensors, predictive maintenance, and a Remote Operations Center reshaped their business processes—shifting from manual, site-based oversight to centralized, data-driven control that improved efficiency and safety.

“All these innovations led to a 9% reduction in operation costs, decrease in incidents, and enhanced safety measures with real-time corrective actions.”

—Krishna Nawacandra, Digital Project Manager, Petrosea

AI-powered sustainability as strategy

Outokumpu, a global stainless-steel leader, faced mounting pressure to meet ambitious climate targets and comply with Corporate Sustainability Reporting Directive (CSRD) reporting while embedding sustainability into its core strategy. Steel accounts for 10% of global greenhouse gas (GHG) emissions, making decarbonization critical.

Manual, fragmented sustainability reporting hindered transparency and efficiency. Outokumpu needed a unified, intelligent data approach to accelerate green value creation and explore AI-powered ESG innovations for competitive advantage.

Outokumpu partnered with Microsoft to deploy the Intelligent Data Platform, Microsoft Fabric, and Sustainability Manager—automating environmental data processes, enabling advanced analytics, and training leaders through the AI data-driven green value creation program.

Outokumpu achieved up to 75% lower carbon footprint versus industry average, launched Circle Green® stainless steel with 93% lower carbon footprint, and helps customers cut 10 million tons of CO₂ annually. Data and AI now fuel new business models, cost savings, and sustainable growth.

By using Microsoft Intelligent Data Platform and AI capabilities, Outokumpu is not just improving sustainability reporting—it is bending the curve on innovation by accelerating the development of new low-emission products and unlocking green business models that deliver both environmental and commercial impact.

“We have set a very clear goal for ourselves. We want to achieve something remarkable.”

—Heidi Peltonen, Vice President of Sustainability at Outokumpu

Advancing the Frontier for mining organizations

Across these three customer stories, a common thread emerges: transformation is not accidental—it is intentional. Frontier Firms combine human ambition with AI, Copilot, and agents to create scalable impact. Ma’aden reimagined productivity, while Petrosea transformed adversity into innovation, and Outokumpu turned data into a strategic asset.

What sets these leaders apart is discipline: they do not stop at adoption. They measure outcomes, codify frameworks, and scale with intent. Technology is a purpose multiplier, enabling safer operations, faster innovation, and sustainable growth.

As Frontier Firms continue to redefine what’s possible in mining, the horizon is filled with opportunities for AI-powered solutions—from predictive maintenance and autonomous operations to intelligent exploration, workflow automation, and sustainability platforms—each poised to unlock new levels of efficiency, safety, and innovation across the industry. The Microsoft GenAI for Energy Permitting Solution Accelerator applied to mining represents a promising step for Frontier Firms seeking to transform permitting from a bottleneck into a strategic advantage. Built on the Microsoft Cloud, the accelerator aims to help mining companies accelerate permitting timelines, improve compliance confidence, and enhance transparency with regulators and communities.

With these and other innovative solutions, the future belongs to Frontier Firms. Are you ready?

Discover solutions

Using Copilot in energy and resources

Explore the possibilities of AI transformation

Learn more

• Visit Microsoft for energy and resources and Microsoft for the mining industry.
• Explore Azure Arc.
• Learn more about Microsoft Security for enterprise.
• Discover over 1,000 AI customer use cases in the blog AI-powered success—with more than 1,000 stories of customer transformation and innovation.
• Read the latest International Energy Agency’s World Energy Outlook 2025.

The post Transforming mining: How Frontier Firms lead with AI and agentic innovation appeared first on The Microsoft Cloud Blog.

Optimizing supply chains: Visibility, risk, and technology

Supply chains have been thrust into the spotlight today more than ever, so it’s no surprise that conversations around how to optimize, improve, and reduce complexity in supply chains are now a top boardroom conversation. Supply chain leaders face both opportunities and challenges, and are primarily focused on key levers to optimize such as: 

• Gain more visibility across value chains to identify potential risks and develop mitigating strategies.
• Drive cost optimization and efficiency improvements to address rising transportation, warehousing, and material costs.
• Improve worker experience and utilize automation to compensate for talent shortages.
• Become more proactive through data-driven decision making and get in front of potential supply chain issues.
• Identify patterns in customer demand to ensure optimal service levels, cost savings, and profitability.  

Supply chain disruptions, triggered by events like natural disasters, geopolitical tensions, and economic volatility, however exposed vulnerabilities in global networks, highlighting the critical need for enhanced supply chain visibility. Businesses must track and monitor materials and products in real-time to identify and mitigate potential risks effectively. The adoption of advanced technologies, such as AI and near-time sensor data, has enabled comprehensive visibility into supply chain operations. 

However, visibility alone is insufficient without accurate risk quantification. By assessing the likelihood and impact of disruptive events, companies can prioritize mitigation strategies, allocate resources efficiently, and make informed decisions to enhance resilience. Predictive analytics, scenario planning, simulation, and risk assessment models play crucial roles in evaluating financial, operational, and strategic implications, and can aid in a proactive posture to reduce impact and shocks to the system. Consequently, the drive for greater supply chain visibility has underscored the importance of risk quantification, enabling businesses to build robust and adaptable supply chains capable of withstanding unforeseen challenges. 

Supply chain depends on data chains 

The supply chain heavily relies on the data chain because data is central to coordinating, optimizing, and managing all processes within the supply chain. Accurate and real-time data allows for effective demand forecasting, ensuring that production meets customer needs without excess inventory. Data enables real-time tracking of goods and materials, enhancing visibility and transparency throughout the supply chain. This visibility helps identify and resolve bottlenecks and disruptions promptly. 

Data also supports supplier management by providing insights into supplier performance and reliability, enabling informed decision-making. Additionally, data analytics can optimize logistics and transportation, reducing costs and improving delivery times. Quality control processes benefit from data-driven insights, ensuring that products meet standards and reduce waste. 

To be successful, organizations must adopt a comprehensive approach, combining intelligent solutions to break down data silos to create a robust and well sorted out data estate. This unlocks numerous opportunities by leveraging comprehensive and well-managed data to drive strategic initiatives and innovation and is a critical step in moving forward with AI. Several key components need to be in place for this to happen: 

• Business sponsorship: Strong leadership and business sponsorship are crucial for prioritizing data-driven initiatives, securing necessary resources, and aligning data strategies with organizational goals. This ensures that data projects receive the support needed for successful implementation and integration across all business units.
• Customer focus: A robust data estate enables deep customer insights through advanced analytics, helping businesses understand customer behaviors, preferences, and needs. This knowledge allows for personalized marketing, improved customer service, and the development of products and services that better meet customer demands—enhancing customer satisfaction and loyalty.
• Process maturity: Mature processes ensure consistent data quality, governance, and security, which are essential for reliable data analytics. Process maturity also facilitates efficient data integration from various sources, enabling comprehensive analysis and more informed decision-making.
• Organizational change management: Successfully leveraging a robust data estate requires effective organizational change management. This includes training employees, fostering a data-driven culture, and managing resistance to change. By ensuring that staff are skilled in data use and understand its value, organizations can maximize the benefits of their data initiatives.
• Value proposition: A well-managed data estate provides a clear value proposition by driving efficiency, reducing costs, and uncovering new revenue opportunities. It supports innovation, enhances competitive advantage, and improves strategic planning—ultimately contributing to improved profitability and shareholder value. 

AI can further enhance this process by providing insights from a multitude of data sources and variables to aid decision making for supply chain planners and operations teams. AI can also optimize inventory management, warehouse operations, route planning, and resource allocation to improve efficiency and reduce costs. AI evaluates supplier performance, supports decision-making with actionable insights, and simulates scenarios for robust contingency planning. IDC predicts that by 2027, 50% of global organizations will deploy a GenAI-powered platform that combines these disparate data sources.¹ By integrating, AI ensures transparency and traceability, detecting anomalies and ensuring compliance. Enhanced collaboration platforms improve communication among stakeholders, while AI-powered demand forecasting aligns supply chain strategies with market trends, ultimately improving adaptability and efficiency in the face of disruptions.  

In summary, data is the backbone of the supply chain, driving efficiency, reducing risks, and enabling informed decision-making across all stages, from procurement and production to logistics and customer delivery. This central role of data ensures a responsive, agile, and resilient supply chain and is a critical step to prepare for a successful rollout AI. 

Supply chain focus area 

A comprehensive resilient supply chain strategy must include visibility and risk management, forecasting and planning, and warehousing and fulfilment as key focus areas. 

• Visibility and risk management: Supply chain visibility is crucial for tracking goods in real-time, ensuring timely delivery, and maintaining customer trust. It also aids in risk management by identifying bottlenecks and potential disruptions, enabling proactive measures to mitigate losses.
• Forecasting and planning: Accurate forecasting and planning can optimize inventory levels, reduce holding costs, and prevent stockouts or overstocking. It involves analyzing historical data and market trends to predict future demand, facilitating efficient resource allocation.
• Warehousing and fulfilment: Efficient warehousing and fulfilment processes ensure that goods are stored properly, and orders are fulfilled accurately and promptly. This enhances customer satisfaction and loyalty. 

While these areas are critical, it is important not to “boil the ocean” by trying to do everything at once. Instead, businesses should prioritize based on their specific needs and capabilities. Implementing changes incrementally can lead to sustainable improvements without overwhelming the organization. In this way, a balanced and focused approach can significantly enhance supply chain performance and competitiveness. 

Within these key focus areas, Microsoft’s suite of services and capabilities play a pivotal role in driving a resilient supply chain: 

• Platform services: Microsoft Azure provides a robust and scalable platform for deploying supply chain applications. It offers flexibility, reliability, and global reach, enabling businesses to operate and innovate at scale.
• Data platforms: Microsoft data platforms like Azure SQL Database and Azure Cosmos DB provide the backbone for storing and managing supply chain data. They offer real-time analytics, enabling businesses to make data-driven decisions.
• Security: Microsoft security solutions protect sensitive supply chain data from threats. Tools like Microsoft Sentinel and Microsoft Defender for Cloud provide advanced threat insight and protection, ensuring the integrity and confidentiality of data.
• Business applications: Microsoft Dynamics 365 Supply Chain Management integrates and streamlines all aspects of the supply chain. It offers modules for planning, production, inventory management, and logistics—driving efficiency and effectiveness.
• Analytics: Microsoft Fabric is an end-to-end data and analytics platform that includes real-time analytics capabilities. OneLake is a unified logical data lake that centralizes and simplifies data management, with multiple analytical engines and workspaces. Fabric enables organizations to process and analyze data for timely insights and decision-making. Supply Chain and logistics are data intensive processes, therefore, it is important to integrate data from other ecosystems such as customers’ existing enterprise systems, connected assets, external sources, partner data, and so forth. It is important to integrate existing data systems, such as connected assets as well as existing systems.
• AI capabilities: Microsoft AI capabilities can transform supply chain operations. AI can enhance demand forecasting, automate warehouse operations, and provide predictive maintenance for logistics. Azure AI Foundry provides critical functionality to design, customize, and manage AI apps and agents at scale. Microsoft Copilot Studio facilitates the creation of custom AI agents to support their work.
• Partner ecosystem: The Microsoft partner ecosystem continues to play a critical role in enabling customer supply chain resiliency and agility. A rich supply chain partner ecosystem includes advisors and implementers and you can find your partner at our Partner center. 

By integrating these elements, Microsoft empowers businesses to build a more resilient, efficient, and intelligent supply chain. It enables customers like C.H. Robinsons to anticipate and respond to disruptions, optimize operations like ABB, and deliver superior customer service through AI, thereby gaining a competitive edge in the market like Dow.

Microsoft products, platforms, and services are designed to integrate seamlessly with existing technology landscapes. They offer interoperability and compatibility, allowing businesses to use their current investments while benefiting from Microsoft’s advanced capabilities. This approach avoids the need for costly and disruptive “rip and replace” strategies. 

Furthermore, Microsoft’s commitment to open standards and cross-platform compatibility means its solutions can work alongside competitor’s products. This flexibility allows businesses to build a best-of-breed technology ecosystem that aligns with their unique needs and objectives. Thus, Microsoft enables businesses to evolve their technology landscapes in a gradual, sustainable manner, maximizing ROI and minimizing disruption. 

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Customers can work directly with Microsoft Industry Solutions teams on custom projects that offer a short go-to-market time. Whether you choose ready-to-deploy partner solutions or bespoke projects with Microsoft partners or Microsoft Industry Solutions, we provide the expertise and support to ensure your success.

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¹ IDC FutureScape: Worldwide Supply Chain 2025 Predictions, doc # US52640524, October 2024.

The post Creating a resilient supply chain using connected data chains appeared first on The Microsoft Cloud Blog.

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 The Microsoft Cloud Blog.

The proliferation of distributed energy resources (DERs)—small-scale units of power generation and storage that operate locally and are connected to larger grids at the distribution level—is also leading power providers to rethink how they operate. DERs could dramatically reduce the need for centralized power generation, but they could also push traditional operational technology (OT) environments to their limits and create heightened need for security.  

A modern, flexible, and secure grid with unified information technology (IT) and OT will become increasingly important for grid operators as consumers add solar panels, electric vehicles, or battery storage and seek to connect to the grid. In fact, a recent survey conducted by Guidehouse shows that 61% of utilities executives believe that utility infrastructure investments should prioritize increased flexibility to improve energy system resilience². AI has the potential to boost resilience by helping providers forecast and manage load demand, maintain power balance, enhance security, support predictive analytics and maintenance, and optimize workforce management and dispatch, among many other use cases. 

Power and utilities companies aren’t alone in recognizing the benefits of AI. A recent study on AI adoption shows that over the next three years, 92% of companies will increase their AI investments, particularly in generative AI; yet only 1% consider their AI deployment to be “mature,”³ indicating there’s still tremendous opportunity to drive continued AI transformation for improved business outcomes. Critically, employees are ready for this change. In fact, three times more employees are using generative AI for 30% or more of their work than their leaders imagine.⁴ It’s a sign that for many companies, the AI transformation is already underway, and teams are eager to unlock new levels of creative potential and productivity.  

An adaptive cloud approach helps streamline operations and provide critical power service 

Through comprehensive cloud, data, and AI offerings, Microsoft and its global partner ecosystem support power and utility providers as they digitally transform and drive sustainable business growth while meeting customer demand. The adaptive cloud approach seamlessly integrates IT and OT, bringing together on-premises control systems and edge intelligence with cloud-scale analytics. This lays the foundation for unlocking the power of their data, further allowing them to utilize AI to meet increasing energy demand and solve their most complex challenges.  

Take Uniper, for example. As the world’s largest power generation company, Uniper needed a solution to help standardize IT and OT so it could manage all applications in a uniform manner. An adaptive cloud strategy helped standardize IT and OT environments, launch new services faster, and optimize performance.  

Emirates Global Aluminum (EGA) has another adaptive cloud success story. EGA’s on-premises environment couldn’t deliver the level of flexibility needed to manage data-intensive operations with scalable computing infrastructure. A hybrid approach allowed them to move part of their server base to the Microsoft Azure public cloud and another part to run hybrid at the edge with Azure Local. This helped optimize latency, support advanced AI and automation solutions, and offer sustaining commercial savings by applying intelligence at the edge.  

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

Sharing success stories and insights at DISTRIBUTECH  

In an era where the imperative for clean, reliable, and accessible energy has never been greater, Microsoft relies on the knowledge and innovative potential of its partners and customers to help spearhead progress. The success stories mentioned above are made possible through the collective efforts of a complete partner and customer energy ecosystem. The company looks forward to connecting with this ecosystem at important energy industry events like the upcoming DISTRIBUTECH International 2025 conference, where it’ll share the latest in AI-powered insights at the annual energy transmission and distribution event. Held in Dallas, Texas from March 24 to 27, 2025, this year’s event promises engaging speaking sessions, exhibitions, and demos across trending topics like energy storage, transportation electrification, distributed energy resource management, and, of course, the latest on AI.  

Microsoft will join its energy partners and customers on stage and at the Microsoft booth as it highlights its work to accelerate the energy transition and address some of the biggest challenges across the power and utilities sector. It’ll speak to some of these challenges at its thought leadership sessions throughout the week, as well as highlight the opportunities to utilize cloud and AI capabilities to tackle them. These conversations couldn’t be timelier, as issues like cybersecurity and threat recovery impact power and utilities providers around the world every day. To that end, Microsoft Energy and Resources leaders will participate in keynote sessions on topics like cybersecurity in the power and utilities sector. They’ll dive into the evolving threat landscape, the intersection of regulation and innovation, and the key measures utilities can take to safeguard critical infrastructure. Microsoft will also take part in a keynote session on transforming power and utilities with AI, where the conversation will revolve around the ways in which AI-powered solutions are revolutionizing utility operations.  

Highlighting Microsoft’s partner ecosystem 

Microsoft will join several energy and technology partners at DISTRIBUTECH to further the discussion on global collaboration and partnership as critical aspects of the energy transition. It will serve as a guest speaker for Schneider Electric’s Knowledge Hub session on grid technologies, diving into the ways that AI and digital transformation are revolutionizing grid operations and management. The occasion marks another milestone in the deep Microsoft partnership with Schneider Electric as we collaborate with the company on the release of its new digital grid solution. Powered by Azure and AI, the new solution is designed to equip utilities with the digital tools to navigate modern energy challenges and support more resilient energy infrastructure. 

Microsoft is also working with longtime partner Itron to empower utility companies with data and intelligent analytics. Itron is integrating Microsoft Copilot technology into its Intelligent Edge Operating System (IEOS), a global data platform running on Azure, to help utilities to use natural language queries to more easily access essential data and insights to accelerate decision making, support innovation, and streamline repetitive tasks. By utilizing Microsoft AI solutions, Itron helps its customers transform complex data interactions into simple, intuitive processes, significantly boosting operational efficiency. 

In addition, Microsoft is collaborating with Siemens Energy’s Industrial Cyber and Digital Trust teams within Digital Solutions to enhance cybersecurity in the energy sector. By integrating Microsoft’s leading cybersecurity capabilities with Siemens Energy’s advanced solutions in the gas turbine business, we are strengthening resilience against evolving threats. This partnership underscores our shared commitment to securing critical infrastructure and driving digital trust across the industry. 

Microsoft also recently announced a collaboration with EPRI (Electric Power Research Institute) through the Open Power AI Consortium to advance AI innovation in the electric sector. This partnership focuses on developing industry-specific AI and generative AI use cases, creating responsible deployment frameworks, and establishing an AI sandbox on Azure for testing and refinement. By fostering collaboration among utilities and key stakeholders, we aim to drive continuous improvement, knowledge sharing, and real-world impact across critical infrastructure. 

Microsoft will co-host a breakfast roundtable with Accenture along with our other energy ecosystem partners AVEVA, IFS, Itron, and Schneider Electric to discuss the keys to unlocking return on investment (ROI) and overcoming barriers to scale AI and digital technologies. Together with utility customers, they will discuss data challenges, regulatory issues, and organizational barriers that utilities face in their data transformation journeys.

Microsoft hopes to see many of you at DISTRIBUTECH 2025 as they share energy success stories and learn how others are driving positive change for a new energy future.  

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.  
• Watch this webinar about AI-powered forecasting in power and utilities with Microsoft Energy and Resources leader Hanna Grene and Amperon Chief Revenue Officer Alex Robart 
• Check out this webinar on how AI solves real utility challenges, featuring Microsoft’s Laurent Boinot 

Sources:

¹ 2025 Power and Utilities Industry Outlook, Deloitte, December 2024. 

² The Power Industry: Presently and Projected, Guidehouse, July 2024. 

^3,4 Superagency in the workplace: Empowering people to unlock AI’s full potential, McKinsey & Company, January 2025. 

The post Transformation in power and utilities with the Microsoft Cloud and AI  appeared first on The Microsoft Cloud Blog.

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 The Microsoft Cloud Blog.

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 The Microsoft Cloud Blog.

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.

Explore ESG readiness for other industries

• Retail and consumer goods: Unlocking business value with data-driven sustainability for retail and consumer goods
• Financial services: ESG data readiness drives value for financial services firms

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