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10
Questions

1In government programs, where do you see AI pilots most often fail when scaling — and what does good governance look like before that happens?

2Many public-sector leaders still believe controls slow innovation. How do you show them that oversight and speed can actually coexist?

3You often stress that “data oversight is also budget oversight.” Can you share an example of how poor data management inflated program costs?

4When executives focus on customer-facing AI but ignore internal services, what kinds of bottlenecks do you see first — and how do you convince them to start with ESM?

5In your experience, what’s the tipping point when improving HR, IT, and finance begins to visibly affect customer experience and time-to-market?

6For ServiceNow and ESM teams, what are the early warning signs that a workflow automation won’t scale?

7You’ve led large global rollouts and post-M&A integrations — what lessons about change control and versioning from those environments still apply to AI today?

8“Design for scale or pay for rework later” is a hard truth. How do you make that case to leaders under pressure to deliver quick wins?

9In the GCC, digital transformation is happening at extraordinary speed. What governance patterns from mature markets actually translate — and which don’t?

10For high-growth organizations balancing compliance with ambition, what’s your framework for building AI foundations that can survive both regulation and scale?

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