Approaching AI with governance as the starting point, not an afterthought, will reduce risk, increase transparency and improve service delivery.
In this video interview, Terry Dorsey, Senior Data Architect and Evangelist at Denodo, discusses rethinking data management in the age of AI.
Governments are racing to adopt AI, yet many struggle. In 2026, success will belong to those who invest in trust, interoperability, and shared purpose.
Government agencies continue to face the critical challenge of preparing the workforce to operate effectively in an AI-driven environment.
AI has come a long way in the past few years, and agencies have learned a lot about best practices. The good news is there’s a growing body of guidance.
Processing data locally speeds up the time for decision making. Edge data can better support mission context and relevance. But distributed data brings with it new challenges. Here’s how to meet them.
Whether you’re planning to use more AI or just want to improve analytics and tighten cybersecurity, good data management must be the foundation for your efforts.
You can’t apply AI to your data until you’ve taken care of some fundaments of data governance and hygiene. Here are some tips on how to get ready.
To make evidence-based policy, takes more than information–it requires the ability to turn information into knowledge and to base decisions on it.
When Pittsburg failed to get certification from Bloomberg Philanthropies’ What Works Cities Certification Program, the city dusted itself off and worked hard to change its entire data mindset. Here’s how they did it.