Three steps
to getting started:
Trust, comply, consume

Step 1 | Trust: Ensure data is reliable

The foundation for trusting data isn’t just about policies and procedures—it’s about reliably supporting your agency’s mission. Instead of adopting another agency’s framework, map your specific mission requirements.

What decisions do your leaders make
What evidence do they need
How does data flow through your organization

These questions will help shape a framework that works for you.

Take stock of your data landscape

Think of your agency’s data like city infrastructure—you need to know what you have before you can effectively manage it. Look beyond obvious databases to legacy systems, shared services, unstructured data and external feeds. Your goal is understanding your entire data ecosystem—from ownership to usage to mission urgency.

Build quality into the process

You know data quality isn’t optional—that citizens and agencies rely on high-quality data. So define what “good” data looks like. Monitor it actively. And create clear processes for addressing challenges before they become issues.

How to get started

Begin with a single mission-critical dataset. Document where you are and where you need to be. Map out who creates and uses the data, define what quality means in this context and create a focused plan for improvement. Remember, trust isn’t built overnight—start small, demonstrate value, and expand thoughtfully.

Step 2 | Comply: Enable unified governance

Compliance isn’t a checkbox

It’s a fundamental mission responsibility. While everyone shares responsibility for privacy, your risk, legal and privacy teams need to be woven into the fabric of your data operations. They aren’t gatekeepers but enablers, helping shape how data serves the mission while protecting citizen trust. The goal is embedding privacy into your agency’s DNA, making it part of how you think about and use data, not an afterthought.

As your agency explores AI, remember that algorithms are only as good as the data they learn from. AI governance isn’t separate from data governance—it’s an extension of it and organizations like NIST have developed frameworks to make it easy for you to ensure you’re on the right track. The same teams that help govern your data should help shape your AI strategy. Start by understanding what AI projects are already happening across your agency.

Which models are approved
Which are experimental

Creating this baseline helps you govern AI initiatives properly from the start.

Nurturing a culture of compliance

Effective compliance isn’t about saying “No”—it’s about finding secure, responsible ways to say “Yes” to mission needs. Your governance framework should help teams understand not just what they can’t do, but how they can achieve their goals while maintaining public trust. This means creating clear pathways for data and AI initiatives that balance innovation with responsibility.

How to get started

Begin with your current AI initiatives. Map them to your data governance framework. Where are the gaps? What new controls are needed? Build from what works in your data governance program, adapting it for AI’s unique challenges. Remember, the goal isn’t perfect governance—it’s governance that enables mission success while protecting public trust.

Step 3 | Consume: The right data
in the right hands

Making data discoverable

Success in the public sector isn’t just about collecting data—it’s about getting the right information to the right people at the right time. Think of your data as a well-organized library where every book has its place and purpose. Your teams shouldn’t have to navigate a maze to find what they need. Instead, create clear pathways to reliable, mission-ready data that’s already vetted and validated.

Building a data marketplace

A government data marketplace isn’t like a commercial app store. It’s a curated environment where approved datasets, AI models and analytics tools come together to serve your agency’s mission. It’s not about unlimited access—it’s about streamlined, secure access to the resources your teams need. When someone needs data for a new initiative or report, they should know exactly where to go and what to expect.

The end goal isn’t just making data available—it’s enabling better decisions across your agency. Your marketplace should help teams understand not just what data exists, but how to use it effectively. Include context about data quality, lineage, and appropriate use cases. Help your teams make confident decisions with data they can trust.

How to get started

Start by identifying your most frequently used datasets. Make these your first marketplace offerings. Document their context, quality and proper use. Create simple processes for access that balance security with usability. Remember, adoption comes from making things easier—show your teams how the marketplace helps them serve the mission better.