AI and public leadership: 5 takeaways from fireside chat on leading AI well 

April 17, 2025

Artificial intelligence is moving fast—and the agencies that lead in AI won’t be the ones that invest in the most technology. They’ll be the ones that invest in people, trust and governance. 

That was the focus of a recent fireside conversation with Partnership SAGE Dan Chenok, executive director of the IBM Center for The Business of Government, hosted by the Partnership for Public Service’s Public Service Leadership Institute’s AI Government Leadership Program. Here are five key takeaways from our conversation, designed to help public sector leaders guide their agencies through this era of rapid change. 

1. Not everyone needs to be an AI expert, but everyone needs AI fluency. 

Leaders often ask, “How much do I need to know about AI?” The answer: You don’t need to build the model, but you do need to guide the mission. Front-line teams need confidence using AI tools and trust in their leaders to set clear guardrails. AI specialists need to go beyond the tech. If AI isn’t aligned to mission, it’s wasted effort. 

Nontechnical leaders need “triage skills” to assess where AI fits: 

  • Is AI the right solution for this problem? 
  • Does the data reflect the communities we serve? 
  • Are the right experts at the table?

2. AI governance can’t be an afterthought. 

Responsible AI doesn’t start after deployment—it starts before a single line of code is written. 

  • Legal and compliance teams must be involved from day one. If AI isn’t compliant, it isn’t responsible. 
  • Security and privacy must be designed into systems from the start. 
  • Governance structures should be agile, not rigid. Test, iterate and scale what works. Build learning into the process. 

3. Generative AI is already reshaping how government works. 

The public sector isn’t experimenting with AI anymore—it’s operationalizing it. 

  • Tasks that once took months can now be done in days. 
  • Teams are shifting from manual processes to strategic problem-solving. 
  • The next horizon? Quantum-powered AI. Leaders must prepare for post-quantum cryptography risks—and begin planning today. 

4. Procurement must evolve for AI’s pace. 

Traditional acquisition cycles weren’t designed for iterative, learning-based technologies. 

  • Agencies need flexible, risk-tolerant funding models to test and adapt before scaling. 
  • Shared services and government-wide platforms can help smaller agencies deploy AI responsibly without starting from scratch. 

5. The biggest risks in AI aren’t just technical—they’re human. 

How we lead AI matters more than what tools we use. 

  • If models aren’t trained on the right data, they won’t deliver the right outcomes. 
  • Fear of job loss is real. Leaders must communicate that AI is here to augment, not replace, public-sector talent. 
  • And yes—our adversaries are using AI too. The strongest defense is a collaborative one: red teaming, scenario planning and interagency coordination in real time. 

AI leadership starts with people 

AI leadership isn’t about memorizing algorithms, it’s about making thoughtful, timely, human-centered decisions. 

At the Partnership for Public Service AI Center for Government, we believe the best AI strategies are built on leadership, not just infrastructure. And that leadership is already emerging, from chief information officers and policy advisors to HR executives and program leads. 

If your agency is taking steps to lead AI well, we’d love to learn from you. Join us as we highlight real-world AI use cases and convene public-sector leaders from across the country to share tools and insights to lead confidently in the age of AI. 

We’re here to help.

Interested in learning more? 

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