{"id":187,"date":"2024-03-28T08:00:00","date_gmt":"2024-03-28T15:00:00","guid":{"rendered":"https:\/\/cm-edgetun.pages.dev\/en-us\/innovation\/blog\/2024\/03\/28\/building-a-foundation-for-ai-success-governance\/"},"modified":"2026-04-11T13:18:51","modified_gmt":"2026-04-11T20:18:51","slug":"building-a-foundation-for-ai-success-governance","status":"publish","type":"post","link":"https:\/\/cm-edgetun.pages.dev\/en-us\/microsoft-cloud\/blog\/2024\/03\/28\/building-a-foundation-for-ai-success-governance\/","title":{"rendered":"Building a foundation for AI success: Governance"},"content":{"rendered":"\n

This is the last post in our six-part blog series. See\u202f<\/em>part one<\/em><\/a>,\u202f<\/em>part two<\/em><\/a>,\u202f<\/em>part three<\/em><\/a>, <\/em>part four<\/em><\/a>, <\/em>part five<\/em><\/a>, and\u202f<\/em>download the white paper<\/em><\/a>.<\/em><\/p>\n\n\n\n

To date, this series has explored four of the five drivers of AI readiness: business strategy, technology and data strategy, AI strategy and experience, and organization and culture. Each is critical to an organization\u2019s ability to use AI to deliver value to the business, whether it\u2019s related to productivity enhancements, customer experience, revenue generation, or net-new innovation. But nothing is ultimately more important than AI governance, which includes the processes, controls, and accountability structures needed to govern data privacy, data governance, security, and responsible development and use of AI in an organization.   <\/p>\n\n\n\n

\u201cWe recognize that trust is not a given but earned through action,\u201d said Microsoft Vice Chair and President Brad Smith. \u201cThat\u2019s precisely why we are so focused on implementing our Microsoft responsible AI principles and practices\u2014not just for ourselves, but also to equip our customers and partners to do the same.\u201d <\/p>\n\n\n\n

In that spirit, we have collected a set of resources that encompass best practices for AI governance, focusing on security, privacy and data governance, and responsible AI. <\/p>\n\n\n\n

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Building a Foundation for AI Success<\/h2>\n\n\n\n

A leader\u2019s guide to accelerate your company\u2019s success with AI<\/p>\n\n\n\n

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Security<\/h2>\n\n\n\n

Just as AI enables new opportunities, it also introduces new imperatives to manage risk, whether related specifically to AI usage, app and data protection, compliance with organizational and legal policies, or threat detection. The Microsoft Security Blog<\/a> includes a set of resources to help you modernize security operations, empower security professionals, and learn best practices to mitigate and manage risk more effectively.  <\/p>\n\n\n\n

One of the first steps you can take is to understand how AI is being used in the organization so you can make informed decisions and implement the appropriate controls. This post<\/a> lays out the primary concerns leaders have about implementing AI, as well as a set of recommendations on how to discover, protect, and govern AI usage. <\/p>\n\n\n\n

For example, you may have heard of (or already be implementing) red teaming. Red teaming, according to this post by the Microsoft AI Red Team<\/a>, \u201cbroadly refers to the practice of emulating real-world adversaries and their tools, tactics, and procedures to identify risks, uncover blind spots, validate assumptions, and improve the overall security posture of systems.\u201d The post shares additional education, guidance, and resources to help your organization apply this best practice to your AI systems. <\/p>\n\n\n\n

Microsoft\u2019s holistic approach to generative AI security considers the technology, its users, and society at large across four areas of protection: data privacy and ownership, transparency and accountability, user guidance and policy, and secure by design. For more on how Microsoft secures generative AI, download Securing AI guidance<\/a>.  <\/p>\n\n\n\n

Privacy and data governance<\/h2>\n\n\n\n

Building trust in AI requires a strong privacy and data governance foundation. As our Chief Privacy Officer Julie Brill has said, \u201cAt Microsoft we want to empower our customers to harness the full potential of new technologies like artificial intelligence, while meeting their privacy needs and expectations.\u201d Enhancing trust and protecting privacy in the AI era<\/a>, originally posted on the Microsoft on the Issues Blog, describes our approach to data privacy, focusing on topics such as data security, transparency, and data protection user controls. It also includes a set of resources to help you dig deeper into our approaches to privacy issues and share what we are learning. 
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Data governance refers to\u202fthe processes, policies, roles, metrics, and standards that enable secure, private, accurate, and usable data throughout its life cycle. It\u2019s vital to your organization\u2019s ability to manage risk, build trust, and promote successful business outcomes. It is also the foundation for data management practices that reduce the risk of data leakage or misuse of confidential or sensitive information such as business plans, financial records, trade secrets, and other business-critical assets. This post shares Microsoft\u2019s approach to data security and compliance<\/a> so you can learn more about how to safely and confidently adopt AI technologies and keep your most important asset\u2014your data\u2014safe. <\/p>\n\n\n\n

Responsible AI<\/h2>\n\n\n\n

\u201cDon\u2019t ask what computers can do, ask what they should do.\u201d That is the title of the chapter on AI and ethics in a book Brad Smith coauthored in 2019, and they are also the first words in Governing AI: A Blueprint for the Future<\/a>, which details Microsoft\u2019s five-point approach to help governance advance more quickly, as well as our \u201cResponsible by Design\u201d approach to building AI systems that benefit society. <\/p>\n\n\n\n

The Microsoft on the Issues Blog<\/a> includes a wealth of perspectives on responsible AI topics, including the Microsoft AI Access Principles, which detail our commitments to promote innovation and competition in the new AI economy and approaches to combating deepfakes in elections announced as part of the new Tech Accord<\/a> announced in February in Munich. <\/p>\n\n\n\n

The Responsible AI Standard<\/a> is the product of a multi-year effort to define product development requirements for responsible AI. It captures the essence of the work Microsoft has done to operationalize its responsible AI principles and offers valuable guidance to leaders and practitioners looking to apply similar approaches in their own organizations.<\/p>\n\n\n\n

You may also have heard about our AI customer commitments<\/a>, which include:  <\/p>\n\n\n\n