AI at scale: How we’re transforming our enterprise IT operations at Microsoft

Running an IT operation at a global scale is a daunting task, even for Microsoft. Comprised of millions of connected devices and virtual networks, our complex IT infrastructure places high demands on our staff and resources worldwide.

That’s where the promise of AI transformation comes in.

We at Microsoft Digital, the company’s IT organization, have developed and implemented a diverse portfolio of agentic, AI-driven capabilities that are now embedded directly in our day-to-day IT operations. These agentic systems—AI solutions that can reason across data, recommend actions, and, in some cases, execute workflows with human oversight—turn telemetry and insights into action, making our IT infrastructure and processes more resilient, auditable, and proactive.

“We’ve crossed an important threshold in the evolution of AI for IT. We’re now using the capabilities these technologies provide to transform all our core IT services, making everything we do on that side more efficient and secure.”

Brian Fielder, vice president, Microsoft Digital

While your organization’s IT infrastructure may not match our size or complexity, we believe any company can benefit from the AI-driven innovations that we’ve implemented in recent years.

We focus our AI investments across three core areas:

• Network management and infrastructure
• Tenant and device management
• Employee and engineering productivity

We’re also using AI across our IT systems to increase security, both as a standalone initiative and an integrated priority. This principle is baked into all our compliance, vulnerability response, and governance scenarios.

“We’ve crossed an important threshold in the evolution of AI for IT,” says Brian Fielder, vice president of Microsoft Digital. “We’re now using the capabilities these technologies provide to transform all our core IT services, making everything we do on that side more efficient and secure.”

Enterprise IT maturity

This article is part of series on Enterprise IT maturity in the era of agents. We recommend reading all four of these articles to gain a comprehensive view of how your organization can transform with the help of AI and become a Frontier Firm.

1. Becoming a Frontier Firm: Our IT playbook for the AI era
2. Enterprise AI maturity in five steps: Our guide for IT leaders
3. The agentic future: How we’re becoming an AI-first Frontier Firm at Microsoft
4. AI at scale: How we’re transforming our enterprise IT operations at Microsoft (this story)

Pillar One: AI in network management and infrastructure

We have applied AI throughout our global network and IT infrastructure, enabling us to keep up with the ever-increasing demands for capacity and services while reducing disruptions and incidents.

The different innovations we’ve made that fall under this pillar demonstrate the breadth of the opportunity to reimagine IT services with AI.

Supporting enterprise IT at Microsoft: Our three pillars

The impact of AI technologies on enterprise IT operations at Microsoft can be divided into three main areas: network management, tenant and device management, and employee and engineering productivity.

AIOps: Transforming network management with operational excellence

AIOps, or Artificial Intelligence for IT Operations, involves the application of machine learning, big data analytics, and automation to streamline and improve IT operations processes. In Microsoft Digital, we use AIOps to help us to manage our complex global IT infrastructure.

Our AIOps solution leverages sophisticated data insights to detect and remediate network issues before they become impactful. We use our internally developed AIOps tools to turn raw signals and institutional know-how into guided actions that have led to major time and cost savings.

AIOps benefits include:

• Enhanced productivity: AIOps reduces cognitive load by automating routine tasks, allowing teams to focus on more strategic activities.
• Proactive issue resolution: AIOps executes automatic troubleshooting and remediation, minimizing downtime and reducing incident impact.
• Improved decision-making: AIOps leverages advanced analytics and machine learning to provide actionable insights, which enhances our decision-making capabilities.

The impact of our AIOps work is huge: thousands of hours of engineering time saved and a significant reduction in total disruption time for employees across the company’s global workforce.

NiC: A network engineer’s companion

Our Network Infrastructure Copilot (NiC) serves as an everyday companion for our network engineers and field IT professionals. With NiC, our IT pros can use natural-language queries to gain quick, accurate insights into network health, configuration states, documentation, troubleshooting resources, and live device data—all in one place.

Some of the typical use cases for NiC include:

• Summarizing syslogs for specific devices
• Recommending circuit upgrades
• Checking deployment status
• Listing devices missing required controls (such as AuditD)

In aggregate, NiC streamlines network device lifecycle management and operation, delivering significant time savings while improving the consistency of operational decisions.

Vuln.AI: Proactively keeping our systems safe

Leaving just a single connected device unpatched could put our entire enterprise at risk. That’s why we developed Vuln.AI (Vulnerability Management Copilot), our intelligent agentic system that has transformed the way we identify, prioritize, and resolve these vulnerabilities across our enterprise network.

Vuln.AI coordinates two agents that enable our network engineers to gather, analyze, and respond to vulnerabilities proactively using AI insights. The research agent maps the vulnerability to the Microsoft infrastructure, significantly increasing accuracy and reducing manual effort and time involved. It then feeds this information to an interactive AI agent, which becomes a gateway for a security engineer or device owner to interface with the data, ask detailed questions, and gather the required information.

Thanks to Vuln.AI, we’ve been able to accelerate infrastructure compliance, reduce exposure windows, streamline security operations, improve endpoint hygiene, and lower operational risk. Our data show thousands of hours of engineering time saved and meaningful improvement in the accuracy of impacted-device identification.

MyWorkspace AI Assistant: Scaling support to meet demand

Engineering disciplines across Microsoft rely on production-like Azure lab environments for testing Windows updates, investigating incidents, and building customer demos. We created the MyWorkspace AI Assistant to enable the rapid creation and management of these lab environments in the face of increasing user demands across our operations. This tool uses AI to help speed tasks such as the development and testing of Windows updates, investigating security incidents, and creating prototypes for customer demos.

Time is a critical component for all lab scenarios, whether it be resolving a customer support issue or testing a Windows Update ahead of a patch release. Our goal is to reduce “Customer Pain Time” (CPT), which measures the amount of time it takes to solve a customer’s problem. Every hour saved in the support process represents a multi-hour reduction in customer pain.

Our most recent data shows that My Workspace AI Assistant reduced tickets submitted to our Tier 1 teams by 50% and saved 500 hours by leveraging support chats, configuration guides, and other artifacts In addition, new user onboarding training tickets were reduced by 90%, and individual support interaction time was reduced from an average of 20 minutes to 30 seconds.

Pillar Two: Tenant and device management

One of the most complicated dimensions of managing IT services at Microsoft is our tenant. This refers to the internal instance of all our cloud services, including Teams channels, SharePoint sites, Power BI workspaces, apps, and email accounts, as well as the millions of devices used by our global workforce.

In Microsoft Digital, we’ve developed a number of AI-powered tools and solutions to help us manage this gigantic management challenge.

Digital asset management with AI: Governing the tenant

Microsoft empowers our employees to create assets—apps, groups, sites, Power Platform environments, Power BI workspaces—at self-service speed, and our governance must match that pace. Our Digital Asset Management Copilot is a multi-agent solution that surfaces risk and policy violations, recommends fixes, and enables self-service remediation.

Our employees can access a Copilot-like experience to self-manage their assets and ensure app compliance accountability. The agent surfaces insights and recommendations related to asset compliance like oversharing of sensitive documents, highlights tenant assets that pose a security risk, offers remediation mechanisms, and can execute compliance tasks with end-user or admin validation.

The benefits include a more secure enterprise tenant and an embedded culture of compliance: Simplify compliance responsibilities, making them intuitive and seamless for our employees. Success is gauged through end user NSAT scores from our compliance solutions.

The scope of this tool spans more than 1.5 million digital assets in the tenant. The benefits include a more secure enterprise tenant and an embedded culture of compliance. With the help of the Digital Asset Management Copilot, we aim to reach our overall goal of 90% compliance with policies covering ownership, labeling, oversharing, and periodic attestation across the tenant.

Works councils and tenant trust reviews: Optimizing tenant onboarding

In the past, fragmented and manual processes around works councils and tenant trust reviews consultations in the European Economic Area  could result in delays to our product launches by as much as four to six months. Our AI-driven optimization program streamlines the end-to-end process, improving submission quality and routing and providing other efficiency recommendations.

The result of these efforts is significant: We’ve managed to reduce the average works councils and tenant trust review cycle times from 133 days to 40—about a 70% improvement—while strengthening trust and transparency across roughly 17 European Economic Area countries.

Enterprise Vulnerability Management: Reducing risk to our device fleet

Our extensive companywide Windows device fleet is exposed to vulnerabilities for extended periods after remediations (patches) are applied, increasing the risk of security breaches and operational inefficiencies. Relying on manual processes can lead to slow response times.

Enterprise Vulnerability Management (EVM) is a multi-phase strategy that uses AI technology in combination with Microsoft first-party vulnerability management solutions to proactively secure and maintain the fleet. While Vuln.AI helps us keep our enterprise infrastructure safe and secure, EVM does the same for our fleet of Windows devices.

EVM minimizes risk and reduces manual effort by integrating advanced detection, automated remediation, and compliance acceleration, minimizing risk and manual effort. This holistic approach ensures our devices stay secure and compliant with minimal IT intervention, delivering resilient, self-healing endpoints across the enterprise.

AI-driven EVM delivers measurable impact across our security, compliance, and IT efficiency. Our goal is to reach 95% compliance within a week of a major patching event while reducing operational overhead and enhancing enterprise resilience.

IntelLicense: Our AI-driven license optimization and audit readiness

Managing a software estate the size of ours—including 28 disconnected systems, 400,000 software assets, and more than 800 suppliers—requires license intelligence. IntelLicense is a set of advanced, AI-driven solutions we’ve developed to help us revolutionize our software discovery and acquisition processes.

These solutions optimize our software asset management throughout the enterprise software lifecycle, reducing fragmented data, lowering audit risk, and accelerating decision-making. These changes have delivered substantial cost savings and efficiency improvements. One standout example: Our external vendor audits that previously took an average of 154 days are targeted to drop to about 15 minutes, thanks to IntelLicense changes.

myDevice AI: Transforming our IT asset management

Ensuring the security of our physical assets requires a unified and accurate inventory. Fragmented IT asset data leads to inconsistent policies and exposes vulnerabilities, making it difficult for security teams to quickly isolate threats and limit potential impact.

The myDevice AI Agent advances an AI-native approach to IT asset management across our IT tenant. The agent automates our high-volume employee requests, clarifies inventory, and streamlines our procurement. While this is occurring, the agent’s recommendation engine matches devices to our users’ needs to improve satisfaction and security.

Early results from myDevice AI include an approximately 50% reduction in time and costs in asset management (eliminating thousands of hours in manual processes annually), as well as improved security and a more personalized device-procurement experience for employees. In time, we will broaden this impact as agentic workflows expand to include labs, printers, conference rooms, and Internet of Things devices.

Pillar Three: Our employee and engineering productivity

Building the software and systems needed to power Information Technology at Microsoft is a time-intensive job. Our engineers have been hard at work building AI-powered solutions that make building and maintaining those systems more efficient and streamlined, answering the question, “How can we apply AI to make this more efficient?”

Here are a few of the solutions we’ve found to help cut down the time and effort involved in some of the routine, day-to-day IT procedures that help keep our systems running smoothly.

ADO Copilot: AI with Azure DevOps

ADO Copilot empowers all our developers and product managers by providing instant, AI-driven insights and automation within Azure DevOps (ADO). This AI-driven assistant seamlessly integrates into ADO and acts as a “trusted copilot” with natural-language capabilities that automate workflows; enhance productivity, compliance, and velocity; and amplify decision-making across the planning, building, and deployment phases.

This agentic solution reduces the time we spend searching for information, managing permissions, planning sprints, summarizing KPIs, and resolving engineering friction points. It enables our engineering teams to move from planning to execution faster and with greater quality and consistency.

The early results from our use of this tool show extensive time savings, which projected over a full year would mean 73,000 fewer hours of engineering time required for the same output.  We’ve also seen greater developer satisfaction and faster movement from planning to execution.

ADO Work Item Assistant: Automating our ADO processes

Building consistent, high-quality ADO work items manually can be time-consuming and prone to errors. Our ADO Work Item Assistant is a generative AI-powered tool that streamlines the creation and understanding of Azure DevOps work items, including features, user stories, tasks, bugs, and custom item types.

The benefits of our assistant include:

• Greater efficiency: The potential to cut the amount of time it takes to craft an ADO feature or user story in half (50%).
• Project delivery enhancement: A streamlined approach mitigates errors and inconsistencies.

By leveraging the power of AI within Azure DevOps, we can significantly simplify and accelerate the work-item authoring process for our product management and engineering teams, improving quality and reducing workload.

Automation hub and catalog: Solving task fragmentation

Large enterprises face major productivity challenges stemming from scattered information, fragmented systems, and reliance on numerous disconnected apps. This fragmentation leads to increased meetings, duplicative effort, and significant time spent on lower-level tasks.

Automation Hub/Automation Catalog is our customizable Teams app—built on Power Platform and Power Catalog—that addresses this challenge by applying AI-powered automation solutions that integrate seamlessly with your existing systems. Common automations include a daily consolidated task list, cancelled-meeting alerts, flags for important emails, and nudges on unanswered messages. The app streamlines workflows and jump-starts productivity gains, enabling you to enhance operational efficiency while maximizing your ROI.

The future of AI in IT

As enthusiastic as we are about our progress so far, we’re even more excited about the great potential that AI agents show in terms of lowered costs, time saved, and boosted productivity across our IT operations.

“The advent of AI agents is the next big step in AI-powered innovation. We are actively working towards our vision of deploying, governing, and managing a fleet of agents across our IT organization, pushing Microsoft to the boundaries of the AI Frontier.”

Monika Gupta, partner group engineering manager, Microsoft Digital

We’re anticipating that these solutions will continue to scale up as we further optimize and standardize large language models and agent patterns in our engineering organizations. Multi-agent orchestration will make an impact on governance and vulnerability response, and autonomous actions will become more common in everyday IT workflows. Measurement rigor will continue to sharpen, ensuring that value is tracked and amplified as AI tools and technologies proliferate across the enterprise.

“As exciting as it’s been to see the many practical applications of AI across our IT portfolio the last two years, 2026 is shaping up to be even more exciting,” says Monika Gupta, partner group engineering manager in Microsoft Digital. “The advent of AI agents is the next big step in AI-powered innovation. We are actively working towards our vision of deploying, governing, and managing a fleet of agents across our IT organization, pushing Microsoft to the boundaries of the AI Frontier.”