Responsible AI: Why it matters and how we’re infusing it into our internal AI projects at Microsoft

Like the computer itself and electricity before it, AI is a transformational technology. It’s providing never-before-seen opportunities to reimagine productivity, address major social challenges, and democratize access to technology and knowledge.

As AI reshapes how we work and live, it brings with it both transformative potential and complex challenges. Across the industry, concerns about bias, safety, and transparency are growing.

At Microsoft, we believe that realizing AI’s benefits requires a shared commitment to responsibility—one we take seriously. As a result, we aren’t just creating AI solutions. We’re taking the lead on infusing responsible AI principles into our technology and organizational practices.

Prioritizing responsible AI across Microsoft

The most impressive AI-powered capabilities in the world mean nothing if people don’t trust the technology. Microsoft and many of our customers across all industries are working to strike the right balance between innovation and responsibility.

IT leaders and CXOs aren’t just deploying AI tools. They’re also thinking of the right guardrails to implement around those tools as their organizations mature. Meanwhile, developers and deployers want to be sure they’re building and implementing AI solutions within the bounds of responsibility.

As an organization that’s mapping the frontier of AI while creating business-ready tools for our customers, Microsoft is shaping the global conversation on responsible AI. We don’t only accomplish that through policy and governance, but also by embedding responsibility into the ways we build, deploy, and scale AI.

Laying the foundation for this work is the duty of our Office of Responsible AI (ORA). This team brings policy and governance expertise to the responsible AI ecosystem at Microsoft.

“We’re on a multi-year journey born out of the need to support innovation—and do it in a way that builds trust,” says Mike Jackson, head of AI Governance, Enablement, and Legal for the Office of Responsible AI. “Along the way, we’ve continued to iterate and evolve the program through a series of building blocks.”

ORA advances AI development, deployment, and secure and trustworthy innovation through governance, legal expertise, internal practice, public policy, and guidance on sensitive uses and emerging technology. The team focuses on empowering innovation while ensuring it falls within Microsoft’s governance, compliance, and policy guardrails.

ORA also partners closely with product and engineering teams as well as other trust domains like privacy, digital safety, security, and accessibility. The team created our Microsoft Responsible AI Standard, the cornerstone of our governance framework, and ensures internal AI initiatives align with it. The Responsible AI Standard translates our six principles into actionable requirements for every AI project across Microsoft.

The six principles guiding our Microsoft Responsible AI Standard

ORA reports into the Microsoft Board of Directors and collaborates with stakeholders and teams across the company to operationalize these principles, implementing policies and practices that apply to AI applications. They determined that every AI initiative should undergo an impact assessment to ensure it aligns with the standard.

If ORA is our compass for responsible AI, our companywide Responsible AI Council has its hands on the steering wheel.

The council, led by Chief Technology Officer Kevin Scott and Vice Chair and President Brad Smith, was formed at the senior leadership level as a forum and source of representation across research, policy, and engineering. It provides leadership, strategic guidance, and executive support and sponsorship to advance strategic objectives around innovation and responsible AI.

Under the council’s guidance, responsible AI CVPs, division leaders, and a network of responsible AI champions across the company operationalize the implementation of our Responsible AI Standard and compliance with our policies.

The structure of these teams is straightforward.

Every division has a designated CVP and division lead to steer the work and connect their team to the overarching Responsible AI Council. Within those divisions, each organization has a lead responsible AI champion or a set of co-leads to steer their team of champions. Those champions act as subject matter experts, reviewers for the impact assessment process, and points of contact for the teams developing AI initiatives.

Implementing AI governance within Microsoft’s IT organization

As members of the company’s IT organization, Microsoft Digital’s responsible AI division lead and champion team have a special role to play. They helped develop a critical internal workflow tool, which has now become a mandatory part of our responsible AI assessment process.

“The key is to ensure full alignment of responsible AI practices with ORA,” says Naval Tripathi, principal engineering manager and co-lead for Microsoft Digital’s Responsible AI Team. “ORA has established clear principles and a step-by-step assessment framework and tool. Our responsibility is to rigorously follow this process and ensure compliance across our products and initiatives.”

This tool logs every project, guides AI developers through initial impact assessments and final reviews, and facilitates those workflows for champions. By streamlining the process through a unified portal, the tool increases efficiency and minimizes errors that can arise from manual processes. It also encourages teams to make responsible AI part of the software development lifecycle (SDL) itself, not a hurdle or an afterthought.

“As organizations develop a diverse ecosystem of AI agents, often created by multiple engineering teams, it becomes essential to establish a standardized evaluation process,” says Thomas Po, a senior product manager working on Campus Services agents. “This ensures every agent adheres to enterprise-level standards before we deploy and distribute it to end users. That makes it more manageable in the long term, and having it all in one tool gives us more transparency.”

Our unified internal workflow looks like this:

• Project initiation and system registration: During the design phase for an AI initiative, the engineering team accesses the portal and registers a new AI system. From there, they fill out fields with crucial information, including a title, description, the developer team’s division, whether the project will include internal or external resources, the relevant champion who should review their initiative, and other details. Within this initial form, different scenarios will trigger different review parameters and requirements, for example, when a team intends to publish a tool externally or engage with sensitive use cases.
• Release assessment: After the system registration is complete, the team initiates the release assessment, a much more thorough review designed to ensure the AI-powered solution is ready to go live. At this point, the engineering team needs to provide detailed documentation. That includes the volume and kinds of data the system will use, potential harms and mitigations, and more. A release assessment includes experts in our Office of Responsible AI, Security, Privacy, and other teams, who review sensitive use cases or initiatives that include generative AI.

If the project clears all the requirements and reviews, it’s ready to go live. Crucially, we don’t think of these stages as a set of hurdles teams need to clear to complete their projects. Instead, the process guides engineering teams through the design elements they need to consider and provides opportunities for feedback from subject matter experts.

“The tool captures all the requirements from ORA and incorporates them into a developer-friendly workflow,” says Padmanabha Reddy Madhu, senior product manager and responsible AI champion for Employee Productivity Engineering within Microsoft Digital. “It’s also a great way to pull AI champions into the design phase so we can support our colleagues’ work.”

With more than 80 AI projects currently underway across Microsoft Digital, logging and streamlining are essential. Teams are working on all kinds of ways to boost enterprise processes and employee experiences, like the following examples from Campus Services that users can access through our Employee Self-Service Agent:

• A facilities agent helps employees take action when they discover an issue at one of our buildings, like a burnt-out light, a spill, or physical damage. The agent creates a ticket to alert a Facilities team so they can resolve it and allows the submitter to follow up on progress.
• A campus event agent makes onsite gatherings like talks and Microsoft Garage build-a-thons more discoverable through simple queries. Using this agent, employees can more easily discover and plan around events that interest them, adding value to the in-person experience and incentivizing community.
• A dining agent addresses the challenges of multiple on-campus restaurants featuring menu options that shift daily. Employees can use natural language queries like “Where can I get teriyaki today?” The agent does the rest. This kind of agent can be especially helpful for employees with allergies or dietary restrictions, providing a boost to accessibility for the on-campus dining experience.

Our policies and practices have embedded a culture of responsibility and trust into our internal AI development processes. With that trust comes the confidence to experiment.

“When we started out, engineers weren’t really sure what to do with AI and how to do it responsibly, so the default was to restrain their own momentum,” says Monika Gupta, partner general manager leading the Employee Productivity Engineering team for Microsoft Digital. “Now they know we have responsible AI built into our practices and our technology as part of an organic process that grows from a root of culture, so they trust the solutions more.”

Far from thinking of responsible AI assessments as an administrative or policy burden that creates additional work, teams now recognize their benefits. They look at the process as an extra set of eyes from a trusted partner. By minimizing legal and compliance risks through our Responsible AI Council’s expertise, our teams save time and stress, and we avoid problems like delayed releases or rollbacks.

Lessons learned: Embedding responsible AI into our development efforts

Throughout this process, we’ve learned lessons that will be helpful for other organizations just beginning their AI journeys:

• We empowered early adopters and enthusiasts as responsible AI champions. They act as anchors and resources for developers who use AI, so we made sure they had the knowledge and training they needed to unlock downstream value.
• Culture has been crucial to our success, especially our growth mindset and our focus on trust. Emphasizing these aspects of our company culture helped us embed responsible AI into core SDL processes and naturalize it on our engineering teams.
• Processes are one thing, and tooling is another. If your responsible AI assessment workflow isn’t attuned to your needs, simply building a review portal tool won’t get you the rest of the way. First, we thought about the process we needed to put in place to solidify responsible AI practices and support our teams’ work. Then we built a tool that supports those workflows as easily and seamlessly as possible.
• Accuracy is reliant on data, and data has a tendency to reflect the biases of the humans who organize it. It’s necessary to correct bias actively through introspection and testing.

“What we’re doing is entirely novel in the tech world,” says Jamian Smith, principal product manager and co-lead for Microsoft Digital’s Responsible AI Team. “Microsoft is really the lead learner here, and we have a passion for corporate citizenship that we’re embedding in our tools.”

As your organization begins to experiment with its own AI projects, take these concrete steps to infuse responsibility into the solutions you create:

1. Establish a strong foundation based on core principles and standards that align with your organizational culture. The Microsoft Responsible AI Standard is a great place to start because it reflects our experience and the expertise we’ve built as AI technology leaders and providers.
2. Seek out the activators across your organization: people with a passion for AI, security, transparency, and other challenge areas, along with a willingness to learn and the ability to lead. Think about how to place them in both centralized and distributed positions.
3. With the rapidly evolving regulatory climate around AI, it’s crucial to have a broad understanding of compliance and continue to follow its developments. Involve dedicated regulatory, compliance, and legal professionals in researching and monitoring global standards while communicating that information to your organization, particularly through training and updates that help teams adapt new regulations into their core processes.
4. Create a process for responsible AI assessment. Consider ways to break it into stages that propel projects forward rather than hindering them. Enlist the right people to assess projects, and consider tooling that streamlines actions for both creators and assessors. Our AI Impact Assessment Guide can help you get started.
5. Benefit from pioneers in the space, including our experts at Microsoft. Our journey has produced ready-to-use resources that can accelerate your progress. Examples include our Responsible AI Toolbox for GitHub, hands-on tools for building effective human-AI experiences, and our AI Impact Assessment Template.

Building your capacity to create AI tools responsibly won’t happen without careful planning and strategy. As part of that process, embed responsible AI into your development workflows by emulating the practices we’ve pioneered at Microsoft.

“It’s not about how fast you can move, but how prepared you are,” Tripathi says. “Responsible AI processes might seem like speed bumps, but ultimately they’re accelerators.”

By prioritizing responsible AI, businesses of all kinds, all over the world, can ensure that the AI revolution is a truly human movement.