Data folks are talking about data governance just as much as AI these days — and for good reason.
The two are deeply interconnected: strong governance ensures AI is ethical, transparent, and reliable, while AI can enhance governance through automation and efficiency.
Today, we’re providing a simple, actionable framework to make governance work with your AI goals — not against them.
Without governance, your AI goals are useless. Without AI, governance is a manual burden on your organization.
Here's your action plan to align your AI and data governance initiatives:
👉 AI for Governance
Don't just manage governance manually — use AI to automate routine tasks. For instance, leverage AI to suggest definitions in your business glossary or proactively flag data quality issues. This saves you hours each week and ensures accuracy.
Ask yourself: What repetitive governance tasks can AI automate to free up your team's time?
👉 Governance for AI
Make your data governance strategy AI-ready. Clear, standardized, and consistently governed data directly improves AI model accuracy and reliability.
Consider: Is your data organized and documented clearly enough to feed reliable AI outcomes?
👉 Governance of AI
Stay accountable. Develop clear processes and criteria to oversee how AI tools are selected, deployed, and maintained. This ensures your AI initiatives remain ethical, aligned with business goals, and protected from regulatory risks.
Evaluate: Who in your organization currently oversees AI compliance and ethics, and is that oversight clear and enforceable?
When you start thinking clearly in terms of these dimensions, governance becomes less abstract and more actionable — helping you spend less time untangling complexity and more time driving measurable value.
“Breaking down your governance approach into clear categories ensures you use AI thoughtfully — solving real problems instead of creating new ones.”
