AI Fails Fast Without The Right Execution Model

Chance Weaver, VP of AI Adoption, Pax8

Parth Gargish, EVP Business Growth, Netsmartz

Burke Anderson, Director, Channel Partnerships, Netsmartz

What separates AI pilots that die in testing from those that scale into durable business value In boardrooms today, that question is driving urgent conversations. Leaders are discovering that technical capability alone doesn’t translate to production success, and the gap between experimentation and real-world impact is where most AI strategies fail.

Execution is the difference. Without clear ownership models, aligned leadership, and operating structures designed for scale, even the most promising AI initiatives stall. The organizations winning at AI aren’t those with the most pilots, but they’re the ones with the right execution framework to move ideas into impact.

Watch this closed-door discussion with Chance Weaver, VP of AI Adoption at Pax8, and the Netsmartz leadership team. Together, they explained why accountability breaks down, what operating models actually work, and how to build AI capabilities that deliver measurable outcomes, not just a proof-of-concept promise.

In this session, you’ll explore:

The real reasons AI investments stall after the pilot phase. Where ownership fractures and how to rebuild accountability. Operating models that scale AI without exponential headcount growth. How to align AI initiatives with business priorities that boards care about. A realistic view of what successful AI execution looks like 18 months out.

Leave with a clearer understanding of the execution gaps in your own AI strategy and a roadmap to close them.