Rethinking your data governance strategy in the era of AI
Effective data governance ensures your data is trustworthy, usable, and compliant—ready to support real business decisions. The challenge? Figuring out how to actually make that happen. Todd Slind, VP of Technology at TRCA, shares an article on Fast Company that makes a powerful case: to succeed with AI, businesses must radically rethink how they approach data governance. Traditional, top-down governance models—designed to control how data is collected, stored, and accessed—are no longer effective in today’s fast-paced, data-rich environments. The problem? These rigid frameworks don’t reflect how data is actually created and used. Frontline employees, field teams, IoT systems, and AI tools like ChatGPT are now generating massive volumes of valuable data—often more than what’s centrally managed. These users aren’t just data consumers; they’re creators and curators.
To adapt, organizations need to shift to a user-empowered governance model. Instead of dictating how data should be handled, leaders should ask:
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What data do users find most valuable?
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Where are the quality issues?
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How can teams be supported in organizing and improving the data they generate?
This bottom-up approach means involving employees across all levels—not just those at desks—in shaping governance policies. Gathering feedback on how data is used helps identify what’s truly valuable and where governance guardrails are needed. Slind concludes that by democratizing data governance, organizations can improve data quality, increase its business impact, and build a more agile, AI-ready foundation.
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