Responsible AI Governance: How Public Sector Leaders Avoid Costly Mistakes
AI is already inside your organization — whether you’ve approved it or not. In this episode of Untangled, we break down what responsible AI governance actually looks like for local government leaders....
26 Mars 58min
How Long Should Digital Transformation Really Take?
How long should digital transformation actually take? Nine months? Twelve? Eighteen? Two years? In this episode of Untangled, we break down what truly determines a realistic public sector transformati...
12 Mars 29min
5 Budget Decisions That Will Shape Local Government Through 2030
In this episode of Untangled, an experienced public-sector consultant walks through the five critical technology areas local governments must prioritize as they prepare 2026–2027 budgets. With AI now ...
5 Mars 55min
Your Employees Will Reject This ERP Unless You Do This First
ERP implementations don’t fail because of software. They fail because people were never prepared to change. In this episode of Untangled, we unpack why so many government ERP projects stall after go-l...
26 Feb 23min
Government AI Pilots Are Failing — Here’s Why
Over 90% of enterprise AI pilots never make it to production — and in local government, the consequences go far beyond wasted budgets. In this episode of Untangled, we break down why so many AI initia...
19 Feb 34min
AI & GovTech: The Race to Do It Right
AV sits down with Vidhu Shekhar, AI thought leader and Microsoft executive, to explore what it really means to lead in the age of artificial intelligence—from space-based data centers to responsible A...
12 Feb 28min
The 90-Day ERP Check: Warning Signs That Predict Project Failure
Most ERP failures don’t come out of nowhere. They announce themselves early — usually within the first 90 days. In this episode of Untangled, we break down why the first three months of an ERP impleme...
5 Feb 26min
Why Your AI Pilot Will Fail (And What Actually Works Instead)
Most government AI pilots don’t fail because the technology is bad. They fail because the problem was wrong, the data wasn’t ready, the demo lied, and no one defined what success actually meant. In th...
29 Jan 34min
