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AI adoption fails when it stops at access to tools. This episode introduces a practical model that bridges the gap between AI tools like Copilot and measurable business outcomes. The focus shifts from technology to people, addressing key blockers such as time, confidence, and relevance. By grounding AI in real workflows, tailoring role-specific use cases, and measuring outcomes, organisations can move from low usage to meaningful impact fast.

🎙 Full Show Notes
https://www.microsoftinnovationpodcast.com/837

👉 What you’ll learn     

  • Identify the real blockers stopping AI adoption in teams 
  • Shift from tool access to measurable business outcomes 
  • Design role-specific AI use cases that drive daily value 
  • Build AI training that fits real work, not theory 
  • Measure AI adoption with practical KPIs and usage data 

✅ Highlights     

  • "These two things are very, very different" 
  • "Some things really need to happen in between those two places" 
  • "This is not about the tech. This is about the people" 
  • "They didn't know how to use the tool" 
  • "They didn't know what they were allowed to do" 
  • "When would they sit and just learn a link" 
  • "To actually tailor use cases that are relevant" 
  • "We have to measure how they are moving" 
  • "We moved a department from 15% to 83%" 
  • "It shifts how you are working" 

🧰 Mentioned     

✅ Keywords      
ai adoption, copilot, generative ai, ai training, business transformation, ai use cases, digital productivity, ai skills, organisational change, ai strategy, workplace efficiency, ai literacy 

If you want to get in touch with me, you can message me here on Linkedin.

Thanks for listening 🚀 - Mark Smith

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