[{"data":1,"prerenderedAt":63},["ShallowReactive",2],{"page-config-/news/data-governance-in-the-ai-era-10-shifts-redefining-data-institutions-and-practice":3,"news-post-data-governance-in-the-ai-era-10-shifts-redefining-data-institutions-and-practice":38},{"id":4,"title":5,"body":6,"description":10,"extension":13,"hero":14,"meta":32,"navigation":15,"path":33,"sections":34,"seo":35,"stem":36,"__hash__":37},"pages/pages/news.md","News",{"type":7,"value":8,"toc":9},"minimark",[],{"title":10,"searchDepth":11,"depth":11,"links":12},"",2,[],"md",{"showHero":15,"title":16,"badge":17,"description":18,"image":19,"imageCredit":20,"backgroundImage":21,"links":22},true,"Recent News & Updates","Latest Posts","Stay updated with the latest news, events, interviews, and videos from our community.","/images/news.webp","Sebastian Pfütze","/images/news-hero-bg.png",[23,28],{"label":24,"to":25,"target":26,"type":27},"Subscribe","https://mailchi.mp/4337f0e3e319/9262kjy9ck","_blank","primary",{"label":29,"to":30,"type":31},"Contact Us","/contact","secondary",{},"/pages/news",null,{"title":5,"description":10},"pages/news","RH8LB8jvO_3y-r_SCCELEeG-ZVvaq9CqOUgvw53iVMY",{"id":39,"title":40,"author":41,"body":42,"category":53,"date":43,"description":46,"duration":34,"endTime":34,"extendedContent":34,"extension":55,"featured":56,"heading":45,"image":54,"location":34,"locationType":34,"mainContent":47,"meta":57,"navigation":15,"path":58,"registrationLink":34,"seo":59,"slug":44,"startTime":34,"stem":60,"tags":61,"videoUrl":34,"__hash__":62},"blogposts/blogposts/data-governance-in-the-ai-era-10-shifts-redefining-data-institutions-and-practice.json","Data Governance In The Ai Era 10 Shifts Redefining Data Institutions And Practice","Stefaan G. Verhulst",{"date":43,"slug":44,"heading":45,"description":46,"mainContent":47,"author":41,"tags":48,"category":53,"image":54},"2026-04-07T12:00:00","data-governance-in-the-ai-era-10-shifts-redefining-data-institutions-and-practice","Data Governance in the AI Era: 10 Shifts Redefining Data, Institutions, and Practice ","As artificial intelligence systems rapidly evolve and start to impact nearly every sector of society, the conversation around governance has mainly focused on models (and their output): their transparency, fairness, accountability, and alignment. Yet this focus, while necessary, is incomplete. AI systems are only as reliable, equitable, and effective as the data (input) on which they are trained and operate.","\u003Cp id=\"0c17\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">As artificial intelligence systems rapidly evolve and start to impact nearly every sector of society, the conversation around governance has mainly \u003Ca class=\"z om\" href=\"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5958674\" target=\"_blank\" rel=\"noopener ugc nofollow\">focused on models (and their output):\u003C/a> their transparency, fairness, accountability, and alignment. Yet this focus, while necessary, is incomplete. AI systems are only as reliable, equitable, and effective as the data (input) on which they are trained and operate.\u003C/p>\n\u003Cp id=\"7b6e\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">\u003Cstrong class=\"my hp\">Data governance is not peripheral to AI governance — \u003C/strong>\u003Ca class=\"z om\" href=\"https://medium.com/data-policy/interwoven-realms-data-governance-as-the-bedrock-for-ai-governance-ffd56a6a4543\" rel=\"noopener\">\u003Cstrong class=\"my hp\">it is its bedrock\u003C/strong>\u003C/a>\u003Cstrong class=\"my hp\">.\u003C/strong>\u003C/p>\n\u003Cp id=\"7bb7\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">At the same time, the rise of AI is not simply placing new demands on data governance; it is fundamentally transforming it. What counts as data, how it is curated, who has a say in its use, and which institutional arrangements govern it are all being reimagined in response to AI’s capabilities and risks.\u003C/p>\n\u003Cp id=\"6d36\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">This essay examines 10 key areas or shifts where \u003Ca class=\"z om\" href=\"https://incubator.opendatapolicylab.org/files/what-is-data-governance-report.pdf\" target=\"_blank\" rel=\"noopener ugc nofollow\">data governance\u003C/a> is being reshaped—either to accommodate AI or as a direct consequence of it.\u003C/p>\n\u003Ch2 id=\"f15e\" class=\"on oo ho bb op oq or os ot ou ov ow ox oy oz pa pb pc pd pe pf pg ph pi pj pk bg\" data-selectable-paragraph=\"\">1. Redefining What Counts as Data\u003C/h2>\n\u003Cp id=\"daec\" class=\"pw-post-body-paragraph mw mx ho my b mz pl nb nc nd pm nf ng nh pn nj nk nl po nn no np pp nr ns nt hh bg\" data-selectable-paragraph=\"\">Historically, data governance focused on structured, tabular datasets—administrative records, surveys, and spreadsheets. Today, the center of gravity has shifted toward unstructured data: text, images, audio, video, and multimodal content that fuel large-scale models.\u003C/p>\n\u003Cp id=\"e38a\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">Large Language Models (LLMs) in particular rely on vast corpora often scraped from the web, raising new governance challenges around provenance, consent, copyright, and representativeness.\u003C/p>\n\u003Cp class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">\u003Cimg src=\"https://cms.thegovlab.com/assets/03995aa7-6edc-4734-8a62-5f9c89f6be59.webp?width=1100&height=682\" alt=\"1 Snlq Isl Bf Kly Bbm8 W1t6dg\">\u003C/p>\n\u003Cp id=\"f633\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">At the same time, AI is no longer just a consumer of data — it is a producer of data\u003Cstrong class=\"my hp\">.\u003C/strong> Synthetic text, images, and signals generated by AI systems are increasingly fed back into training pipelines, raising the specter of \u003Cem class=\"pr\">model collapse\u003C/em> and necessitating governance frameworks for machine-generated data itself.\u003C/p>\n\u003Ch2 id=\"ce02\" class=\"on oo ho bb op oq or os ot ou ov ow ox oy oz pa pb pc pd pe pf pg ph pi pj pk bg\" data-selectable-paragraph=\"\">2. From FAIR to FAIR-R\u003C/h2>\n\u003Cp id=\"947d\" class=\"pw-post-body-paragraph mw mx ho my b mz pl nb nc nd pm nf ng nh pn nj nk nl po nn no np pp nr ns nt hh bg\" data-selectable-paragraph=\"\">The FAIR principles — Findable, Accessible, Interoperable, Reusable — have long guided data stewardship and remain fundamental to enabling responsible access to data for reuse. But AI systems require more.\u003C/p>\n\u003Cp id=\"ae5b\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">We are witnessing the need to extend \u003Ca class=\"z om\" href=\"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5164337\" target=\"_blank\" rel=\"noopener ugc nofollow\">FAIR to FAIR-R\u003C/a> (Ready-for-AI) to include the following:\u003C/p>\n\u003Cul class=\"\">\n\u003Cli id=\"2d0f\" class=\"mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Structured metadata for machine interpretability;\u003C/li>\n\u003Cli id=\"a2e0\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Better documentation of lineage and provenance;\u003C/li>\n\u003Cli id=\"170c\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Bias and representativeness assessments;\u003C/li>\n\u003Cli id=\"6233\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Alignment with responsible AI practices.\u003C/li>\n\u003C/ul>\n\u003Cp id=\"c9e3\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">In short, data must now be not only reusable but also \u003Ca class=\"z om\" href=\"http://v/\" target=\"_blank\" rel=\"noopener ugc nofollow\">reusable by machines\u003C/a> in ways that are safe, auditable, and aligned with societal values.\u003C/p>\n\u003Ch2 id=\"1c39\" class=\"on oo ho bb op oq or os ot ou ov ow ox oy oz pa pb pc pd pe pf pg ph pi pj pk bg\" data-selectable-paragraph=\"\">3. The Rise of Context as Infrastructure\u003C/h2>\n\u003Cp id=\"f88c\" class=\"pw-post-body-paragraph mw mx ho my b mz pl nb nc nd pm nf ng nh pn nj nk nl po nn no np pp nr ns nt hh bg\" data-selectable-paragraph=\"\">Data without context is increasingly unusable in AI systems. Models require not just raw inputs but structured information about meaning, relationships, and intended use.\u003C/p>\n\u003Cp id=\"e065\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">This has led to the development of new protocols such as \u003Ca class=\"z om\" href=\"https://www.anthropic.com/news/model-context-protocol\" target=\"_blank\" rel=\"noopener ugc nofollow\">Model Context Protocol (MCP),\u003C/a> which aims to standardize how context—such as tools, memory, and environmental information—is structured and transmitted to AI systems alongside data.\u003C/p>\n\u003Cp id=\"bddb\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">Context is becoming a form of infrastructure — governed, curated, and standardized — shaping \u003Ca class=\"z om\" href=\"https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents\" target=\"_blank\" rel=\"noopener ugc nofollow\">how AI systems \u003C/a>interpret and act upon data.\u003C/p>\n\u003Ch2 id=\"3af1\" class=\"on oo ho bb op oq or os ot ou ov ow ox oy oz pa pb pc pd pe pf pg ph pi pj pk bg\" data-selectable-paragraph=\"\">4. From Data Stewardship to Strategic Data Stewardship\u003C/h2>\n\u003Cp id=\"0eb7\" class=\"pw-post-body-paragraph mw mx ho my b mz pl nb nc nd pm nf ng nh pn nj nk nl po nn no np pp nr ns nt hh bg\" data-selectable-paragraph=\"\">Traditional data stewardship focused on compliance, management, and quality control. In the age of AI, this is insufficient.\u003C/p>\n\u003Cp id=\"4e3c\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">There is a growing need for \u003Ca class=\"z om\" href=\"https://arxiv.org/abs/2601.06687\" target=\"_blank\" rel=\"noopener ugc nofollow\">strategic data stewardship\u003C/a> — a proactive, purpose-driven approach that:\u003C/p>\n\u003Cul class=\"\">\n\u003Cli id=\"4ae4\" class=\"mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Aligns data use with public value\u003C/li>\n\u003Cli id=\"2440\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Anticipates downstream AI applications\u003C/li>\n\u003Cli id=\"010b\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Brokers relationships across sectors\u003C/li>\n\u003Cli id=\"43cd\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Enables responsible reuse at scale\u003C/li>\n\u003C/ul>\n\u003Cp id=\"82fb\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">The role of the data steward is evolving from custodian to orchestrator of data ecosystems.\u003C/p>\n\u003Ch2 id=\"98cf\" class=\"on oo ho bb op oq or os ot ou ov ow ox oy oz pa pb pc pd pe pf pg ph pi pj pk bg\" data-selectable-paragraph=\"\">5. New Licensing Regimes for the AI Era\u003C/h2>\n\u003Cp id=\"1182\" class=\"pw-post-body-paragraph mw mx ho my b mz pl nb nc nd pm nf ng nh pn nj nk nl po nn no np pp nr ns nt hh bg\" data-selectable-paragraph=\"\">Existing data licensing frameworks—such as \u003Ca class=\"z om\" href=\"https://creativecommons.org/\" target=\"_blank\" rel=\"noopener ugc nofollow\">Creative Commons\u003C/a>—were not designed with AI training in mind.\u003C/p>\n\u003Cp id=\"d525\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">In response, \u003Ca class=\"z om\" href=\"https://datalicenses.org/\" target=\"_blank\" rel=\"noopener ugc nofollow\">new approaches are emerging\u003C/a>, including AI-specific licenses and signaling mechanisms (e.g., “\u003Ca class=\"z om\" href=\"https://creativecommons.org/ai-and-the-commons/cc-signals/\" target=\"_blank\" rel=\"noopener ugc nofollow\">cc-signal\u003C/a>”) that indicate whether and how data can be used for model training.\u003C/p>\n\u003Cp id=\"1b13\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">These developments reflect a broader transition: from static permissioning toward signalling of preferences and more dynamic, machine-readable governance of data rights.\u003C/p>\n\u003Ch2 id=\"48d9\" class=\"on oo ho bb op oq or os ot ou ov ow ox oy oz pa pb pc pd pe pf pg ph pi pj pk bg\" data-selectable-paragraph=\"\">6. Social License and Participatory Governance\u003C/h2>\n\u003Cp id=\"3f32\" class=\"pw-post-body-paragraph mw mx ho my b mz pl nb nc nd pm nf ng nh pn nj nk nl po nn no np pp nr ns nt hh bg\" data-selectable-paragraph=\"\">Legal compliance and \u003Ca class=\"z om\" href=\"http://v/\" target=\"_blank\" rel=\"noopener ugc nofollow\">acquiring consent \u003C/a>alone are no longer sufficient to legitimize data use in AI systems. Public trust increasingly depends on broader notions of \u003Ca class=\"z om\" href=\"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5255677\" target=\"_blank\" rel=\"noopener ugc nofollow\">social license.\u003C/a>\u003C/p>\n\u003Cp id=\"cba3\" class=\"pw-post-body-paragraph mw mx ho my b mz nb nc nd nf ng nh nj nk nl nn no np nr ns to nt hh bg\" data-selectable-paragraph=\"\">We are seeing the rise of participatory mechanisms—citizen assemblies, stakeholder consultations, community governance models—that allow affected groups to shape decisions about how their data is used.\u003C/p>\n\u003Cp id=\"be5e\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">This marks a shift from consent as a transaction to agency as a process.\u003C/p>\n\u003Ch2 id=\"50c1\" class=\"on oo ho bb op oq or os ot ou ov ow ox oy oz pa pb pc pd pe pf pg ph pi pj pk bg\" data-selectable-paragraph=\"\">7. New Institutional Forms: Data Commons and Beyond\u003C/h2>\n\u003Cp id=\"d145\" class=\"pw-post-body-paragraph mw mx ho my b mz pl nb nc nd pm nf ng nh pn nj nk nl po nn no np pp nr ns nt hh bg\" data-selectable-paragraph=\"\">To counter risks of data extraction and concentration, \u003Ca class=\"z om\" href=\"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6364718\" target=\"_blank\" rel=\"noopener ugc nofollow\">new institutional arrangements\u003C/a> are emerging, including \u003Ca class=\"z om\" href=\"https://www.linkedin.com/pulse/data-commons-missing-infrastructure-public-interest-verhulst-phd-k8eec/\" target=\"_blank\" rel=\"noopener ugc nofollow\">data commons\u003C/a>, cooperatives, and trusts.\u003C/p>\n\u003Cp id=\"519e\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">These models aim to:\u003C/p>\n\u003Cul class=\"\">\n\u003Cli id=\"7732\" class=\"mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Embed collective governance;\u003C/li>\n\u003Cli id=\"c4c3\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Align data use with community preferences and shared goals;\u003C/li>\n\u003Cli id=\"f47e\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Redistribute value generated from data.\u003C/li>\n\u003C/ul>\n\u003Cp>\u003Cimg src=\"https://cms.thegovlab.com/assets/a3cbc405-8be0-4169-8844-5b670ef34966.webp?width=1100&height=657\" alt=\"1 Jx Zn2al a Txa Poz C4yd B4tg\">\u003C/p>\n\u003Cp id=\"0dcb\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">In the AI context, such arrangements are critical to ensuring that data is not merely extracted but mobilized for collective agency and public benefit.\u003C/p>\n\u003Ch2 id=\"0b90\" class=\"on oo ho bb op oq or os ot ou ov ow ox oy oz pa pb pc pd pe pf pg ph pi pj pk bg\" data-selectable-paragraph=\"\">8. Synthetic Data as a Governance Tool\u003C/h2>\n\u003Cp id=\"aaf2\" class=\"pw-post-body-paragraph mw mx ho my b mz pl nb nc nd pm nf ng nh pn nj nk nl po nn no np pp nr ns nt hh bg\" data-selectable-paragraph=\"\">Synthetic data—artificially generated datasets that mimic real-world patterns—has gained traction as a way to address privacy, access, and scarcity challenges.\u003C/p>\n\u003Cp id=\"5f0c\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">\u003Ca class=\"z om\" href=\"https://arxiv.org/abs/2602.03791\" target=\"_blank\" rel=\"noopener ugc nofollow\">When done responsibly\u003C/a>, its governance implications include:\u003C/p>\n\u003Cul class=\"\">\n\u003Cli id=\"284c\" class=\"mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">It can enable safe data sharing without exposing sensitive information;\u003C/li>\n\u003Cli id=\"d6dd\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">It can fill gaps in underrepresented datasets;\u003C/li>\n\u003Cli id=\"e0bc\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">It raises questions about fidelity, bias amplification, and misuse.\u003C/li>\n\u003C/ul>\n\u003Cp id=\"52c4\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">As such, synthetic data is not just a technical solution — it is a new object of governance in its own right.\u003C/p>\n\u003Ch2 id=\"3454\" class=\"on oo ho bb op oq or os ot ou ov ow ox oy oz pa pb pc pd pe pf pg ph pi pj pk bg\" data-selectable-paragraph=\"\">9. AI for Data Governance\u003C/h2>\n\u003Cp id=\"b383\" class=\"pw-post-body-paragraph mw mx ho my b mz pl nb nc nd pm nf ng nh pn nj nk nl po nn no np pp nr ns nt hh bg\" data-selectable-paragraph=\"\">AI is not only governed by data governance — it is increasingly used to perform data governance. Applications include:\u003C/p>\n\u003Cul class=\"\">\n\u003Cli id=\"de71\" class=\"mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">\u003Ca class=\"z om\" href=\"https://blogs.worldbank.org/en/opendata/beyond-keywords--ai-driven-approaches-to-improve-data-discoverab0\" target=\"_blank\" rel=\"noopener ugc nofollow\">Automated data discovery and classification\u003C/a>;\u003C/li>\n\u003Cli id=\"712e\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">\u003Ca class=\"z om\" href=\"https://medium.com/glassdoor-engineering/data-quality-at-petabyte-scale-building-trust-in-the-data-lifecycle-7052361307a4\" rel=\"noopener\">Quality assessment and anomaly detection\u003C/a>;\u003C/li>\n\u003Cli id=\"dd7d\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Monitoring compliance and usage patterns;\u003C/li>\n\u003Cli id=\"7e89\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Auditing datasets and models for bias and risk.\u003C/li>\n\u003C/ul>\n\u003Cp id=\"b02a\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">This introduces both efficiencies and new risks, as governance itself becomes partially automated.\u003C/p>\n\u003Ch2 id=\"0428\" class=\"on oo ho bb op oq or os ot ou ov ow ox oy oz pa pb pc pd pe pf pg ph pi pj pk bg\" data-selectable-paragraph=\"\">10. The Emergence of AI Agents in Data Governance\u003C/h2>\n\u003Cp id=\"3b8b\" class=\"pw-post-body-paragraph mw mx ho my b mz pl nb nc nd pm nf ng nh pn nj nk nl po nn no np pp nr ns nt hh bg\" data-selectable-paragraph=\"\">Finally, the rise of AI agents — systems capable of autonomous, multi-step decision-making — signals a new frontier as it relates to data management and governance. \u003Ca class=\"z om\" href=\"https://www.forbes.com/councils/forbestechcouncil/2026/02/02/ai-ready-data-a-paradigm-shift-from-traditional-data-governance-to-agent-driven-intelligent-enablement/\" target=\"_blank\" rel=\"noopener ugc nofollow\">These agents\u003C/a> have been used to:\u003C/p>\n\u003Cul class=\"\">\n\u003Cli id=\"f32e\" class=\"mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Negotiate data access\u003C/li>\n\u003Cli id=\"e037\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Enforce governance rules\u003C/li>\n\u003Cli id=\"62b1\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Manage data pipelines dynamically\u003C/li>\n\u003Cli id=\"4c55\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Act as intermediaries between users and data ecosystems\u003C/li>\n\u003C/ul>\n\u003Cp id=\"11e2\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">This raises fundamental questions about delegation, accountability, and control in governance systems where machines act on behalf of humans.\u003C/p>\n\u003Ch2 id=\"8d21\" class=\"on oo ho bb op oq or os ot ou ov ow ox oy oz pa pb pc pd pe pf pg ph pi pj pk bg\" data-selectable-paragraph=\"\">Conclusion: Data Governance as a Living Practice\u003C/h2>\n\u003Cp>\u003Cimg src=\"https://cms.thegovlab.com/assets/52041736-ef9b-4eac-b1fc-4a0578d097b4.webp?width=1100&height=738\" alt=\"1 E4 Kae Uw O R19 Pm V Ovo Q G6 Vq\">\u003C/p>\n\u003Cp id=\"694d\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">Data governance is the foundation upon which AI systems are built. But in the age of AI, it is no longer a static foundation — it is a dynamic, evolving practice and system shaped by the very technologies it enables.\u003C/p>\n\u003Cp id=\"a107\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">We are moving toward a world where:\u003C/p>\n\u003Cul class=\"\">\n\u003Cli id=\"96d3\" class=\"mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">Data governance shapes AI;\u003C/li>\n\u003Cli id=\"c0db\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">AI reshapes data governance;\u003C/li>\n\u003Cli id=\"92d5\" class=\"mw mx ho my b mz pv nb nc nd pw nf ng nh px nj nk nl py nn no np pz nr ns nt ps pt pu bg\" data-selectable-paragraph=\"\">And both co-evolve in a continuous feedback loop.\u003C/li>\n\u003C/ul>\n\u003Cp id=\"94ae\" class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">The challenge ahead is not simply to adapt existing frameworks but to reimagine data governance as a living practice and system—capable of ensuring that AI serves not only efficiency and innovation but also equity, accountability, and the public good.\u003C/p>\n\u003Cp class=\"pw-post-body-paragraph mw mx ho my b mz na nb nc nd ne nf ng nh ni nj nk nl nm nn no np nq nr ns nt hh bg\" data-selectable-paragraph=\"\">Image C: Daniela Zampieri / https://betterimagesofai.org / https://creativecommons.org/licenses/by/4.0/\u003C/p>",[49,50,51,52],"datagovernance","AIgovernance","innovation","opendata","blog","https://cms.thegovlab.com/assets/d286e56f-1179-4f39-8200-630dc667fea6","json",false,{},"/blogposts/data-governance-in-the-ai-era-10-shifts-redefining-data-institutions-and-practice",{"title":40,"description":46},"blogposts/data-governance-in-the-ai-era-10-shifts-redefining-data-institutions-and-practice",[49,50,51,52],"GS6GB9eUkMbrB4qg7k-NIIgnJ64I8nJVRoqZeQxdDhE",1775568952374]