Last week, we asked a simple question with serious implications: Which types of decisions should always require human judgment, even as AI tools become more advanced? Employee hire or dismissal: 0% Award or disqualify bids: 0% Budget or funding approvals: 0% All of the above: 100% That result was surprising. And also telling. Because when […]
Author: Eric Sylvia
Federal agencies are rapidly deploying AI – often faster than their ability to validate outputs. In our recent poll, teams were divided: some trust their systems; others admit they wouldn’t catch a bad output until it was too late. So what happens when an AI makes a decision it was never meant to? This is […]
Part II of the “Five Questions Federal AI Leaders Are Asking” Series, When the Rubber Meets the Mission: Operationalizing AI Oversight The policy was clear. The model was tuned. The team was trained. Still, it broke. Welcome to the messy middle – implementation. It’s where the ideal meets the edge cases. Where oversight gets tangled […]
Part I of the “Five Questions Federal AI Leaders Are Asking” Series The machine doesn’t blink. It doesn’t weigh intent or consequence. It runs the data, executes the code, and returns a decision. Approve. Deny. Act. But someone has to own the outcome. That’s where the conversation around federal AI adoption gets uncomfortable – because […]
Governing AI in Motion The Three Domains That Make or Break AI Oversight The system passed testing. Then it failed in the field. Not loudly. No alarms. Just a slow drift. A shift in how it ranked inputs. A different tone in outputs. No one noticed — until the call from legal. What failed wasn’t […]
Governing AI in Motion: How to Build Resilience in a Rapidly Evolving Threat Landscape Part II: The Four Levels of AI Governance Maturity: From Ad Hoc to Resilient You’re Not Starting from Zero — But You May Be Stuck Every organization working with AI has governance. The real question is: what kind? Is it designed […]
Governing AI in Motion: How to Build Resilience in a Rapidly Evolving Threat Landscape Part I: Why AI Governance Must Move Faster Than the Systems It Oversees The Shift Has Already Happened AI no longer lives in the lab. It is writing policies, ranking resumes, interpreting satellite imagery, and shaping battlefield decisions. It has moved […]
The future of AI oversight won’t be won by rigid frameworks. It will be won by systems that sense. In the last three parts of this series, we’ve mapped the shift from traditional risk management to adaptive governance. We’ve shown how artificial intelligence moves us from the predictable into the emergent. From systems you can […]
When artificial intelligence moves from pilot to production, governance stops being theoretical. It becomes operational. This is the moment when frameworks meet reality. Governance is no longer a planning artifact or compliance checkpoint, it becomes a living discipline embedded in how systems are monitored, corrected, and evolved. Traditional oversight works well in environments that are […]
Why We Love Risk Matrices There’s a reason risk management has been canonized across federal programs. It works—at least in domains that behave predictably. Whether you’re building a satellite or migrating legacy data, the discipline of risk is indispensable. You can scope it. Score it. Mitigate it. But that same structure can become a liability […]