The Agentic Shift: Scaling AI That Actually Works

The Agentic Shift: Scaling AI That Actually Works

What this video covers

Airia CEO Kevin Kiley works through why so many AI pilots stall and what separates the ones that scale. He contrasts passive IT governance, built on training, policies, and point-in-time assessments, with active governance that enforces policy at runtime, then turns to measuring ROI, the anxiety that holds projects back, and the need to plan for scale before you reach it.

Key takeaways:

• Traditional IT governance is largely passive; assessments report a point in time and are likely stale as soon as they are processed, because AI is dynamic and non-deterministic.
• Active governance is the sprinkler system to passive governance’s smoke alarm: it not only sets policy but ensures it is enforced at runtime. If enforcement does not happen at inference, you are too late.
• Start measuring ROI with what you can confidently metric, such as throughput and error rates.
• Pilots that succeed have true executive sponsorship and clear success metrics; ambiguity on either leads to pilot purgatory.
• Think about scale well before you get there, because pilots that look great in a small lab often never contemplated the overhead of moving to production.

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