AI in Action AI adoption demands more than just new tools
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Oct 7, 2025 
Conor Grennan, Chief AI Architect at NYU Stern, shares insights on successfully adopting AI in organizations. He emphasizes that it's not just about new tools but about driving a behavioral shift among teams. Conor discusses common pitfalls of AI adoption, like treating it merely as a replacement for existing processes. He advocates for cultivating AI champions within organizations and rethinking workflows to embrace AI's full potential. Trustworthy AI relies on high-quality data, and leaders must set the standard for effective use.
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AI Adoption Is A Behavioral Shift
- Conor Grennan frames AI adoption primarily as a behavioral shift rather than a technical learning curve.
- Organizations must change how people work, not just teach tools, to realize AI's value.
Stop With Tool-Only Rollouts
- Avoid teaching only use cases or rolling out tools and expecting mass adoption to follow.
- Focus on changing behaviors and building adoption systems, not just distributing licenses or demos.
Brains Force Simplistic AI Uses
- When people assume AI must replace a known tool, they lock into simplistic uses and miss broader possibilities.
- Large language models invite rethinking workflows, not one-to-one replacements.