CTO Hour with Peter Bell: Cracking the AI Adoption Code
by Peter Bell, Camille Fournier, Ali Dasdan
Overview
While the pressure to implement AI is intense, most senior leaders are still figuring out where LLMs deliver real value and how to progress from isolated experiments to company-wide adoption. The gap between pilot projects and enterprise success remains frustratingly wide.
In this CTO Hour, you’ll hear from senior engineering leaders who’ve begun to crack this code. They’ll share the specific applications and use cases where LLMs are delivering measurable business impact in production, practical strategies for scaling LLM usage across skeptical teams and departments, and the organizational tactics that separate success from failure.
The panelists dispense with the usual summaries of LLM capabilities and focus on real-world results and the strategies that make them possible. Whether you’re just starting your LLM journey or struggling to scale existing initiatives, you’ll come away with clear examples of what works—and how to make it happen across your organization.
What you’ll learn and how you can apply it
- Discover which LLM applications are delivering real business value in production and which have failed to achieve expected results
- Pick up strategies for driving LLM adoption and managing resistance across skeptical teams, departments, and entire organizations without creating chaos
- Get practical guidance on how to move from pilot projects to enterprise-wide LLM success
This live event is for you because...
- You’re a CTO, VP of engineering, or senior technology leader responsible for driving AI adoption and proving business value.
- You’re struggling to scale LLM initiatives beyond pilot projects or facing resistance from teams skeptical about AI tools.
- You want to learn from peers who have successfully implemented LLMs at scale and understand what separates success from failure.
- You need practical strategies and real-world examples—not theoretical frameworks—to guide your LLM adoption journey.
Recommended follow-up:
- Listen to Generative AI in the Real World Podcast (podcast)
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