Artificial intelligence is reshaping how organizations build, decide, and operate. I focus on what actually changes inside companies when AI moves from theory to implementation.
My work examines the structural consequences of AI adoption — how product strategy shifts, where leadership assumptions break down, and what organizations must understand before embedding intelligence into real systems.
Signature Keynote
Product Is Not Dead. It Is Being Exposed.
AI is not eliminating product management. It is exposing weak strategy, unclear ownership, and shallow discovery.
As roadmaps compress and execution accelerates, ambiguity becomes visible faster. Assumptions fail sooner. Misalignment becomes expensive.
This keynote explores how product leadership must evolve in an AI-native environment — and why systems thinking, judgment, and organizational clarity matter more than feature velocity.
Attendees leave with a clear framework for leading product in a world where intelligence is embedded directly into software.
Additional Talks
AI First Was Inevitable. Most Companies Did It Wrong.
AI adoption accelerated quickly, often without the structural support required to sustain it. Governance, documentation, incentives, and ownership frequently lag behind executive mandates.
This session examines what happens when implementation outpaces organizational alignment — and how leaders can build durable foundations before scale.
Participants leave with practical criteria for assessing whether their organization is prepared for sustainable AI adoption.
The Illusion of Speed in AI Adoption
AI creates visible momentum. Prototypes ship quickly. Automation expands rapidly. But speed without structural understanding introduces hidden risk.
This talk explores the tension between acceleration and discipline — and why thoughtful implementation often outperforms reactive mandates.
Leaders leave with sharper questions to evaluate whether their AI initiatives are durable or simply fast.
Systems Under Stress: What Enterprise AI Reveals About Leadership
When AI integrates into workflows, it exposes fragility in processes, incentives, and decision structures. Enterprise systems behave differently under pressure.
This session focuses on governance, risk, and decision-making in complex environments where intelligence becomes operational.
Attendees develop a deeper understanding of how AI surfaces structural weaknesses — and how leadership must adapt in response.
Beyond the Hype: Building AI Inside Real Organizations
Most AI conversations happen in theory. Implementation introduces friction: documentation gaps, data realities, cross-functional misalignment, and unclear ownership.
This talk draws from enterprise implementation experience to examine what it takes to move AI from concept to production responsibly.
Participants leave with a grounded understanding of what sustainable AI adoption requires.
Audiences
I speak to:
- Product leadership teams
- Enterprise AI and data organizations
- Technology and innovation conferences
- Executive offsites
- MBA and graduate programs
Available for keynote, moderated conversation, executive workshop, and panel discussion formats.
Short Bio
David Monnerat is a product leader building enterprise AI systems. He writes and speaks about how artificial intelligence reshapes product strategy, leadership, and organizational design from inside real-world implementation.
His work focuses on systems thinking, governance, and how technology decisions reshape organizations over time — structurally, culturally, and operationally.
He also writes long-form essays on caregiving and complexity at epilepsydad.com, experiences that inform his perspective on systems under stress and long-term decision-making.
Booking
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