Stop Designing for Exploration. Start Designing for Explanation.
Many government data products are built for the wrong user. Here’s a practical framework for shifting toward understanding and action.
Many government data products are built for the wrong user. Here’s a practical framework for shifting toward understanding and action.
Government agencies are sitting on a growing volume of data. The problem is the interpretation gap.
Government organizations are racing to adopt artificial intelligence, but successful AI requires more than sophisticated technology.
A practical approach to ADA compliance can help districts build accessibility into everyday operations.
Compliance is often blamed for slowing the IT modernization efforts of federal healthcare agencies. But more often, architectural limitations are holding agencies back.
AI readiness doesn’t start with a pilot project or a new application. Read on to learn why it starts with your data.
Storage alone isn’t enough for state and local government. See why data infrastructure must be a strategic foundation for service delivery.
If agencies want to make responsible decisions about where AI should be used, they need to measure its net value — because “hours saved” can be misleading.
Federal agencies have spent the last decade building the data infrastructure needed to understand past performance. The next strategic advantage, however, will come from transforming enterprise data into predictive decision intelligence through Enterprise Digital Twins that allow leaders to simulate mission impacts before implementing major policy, operational, workforce, or technology decisions.
Trust is essential to effective government, but it’s not managed the way finance, cybersecurity, or operations are. Maybe it should be.