AI Adoption vs. Adaptation: What Problem Are You Solving?

Paul McDonagh-Smith estimates that many business leaders would struggle to define their organization’s problem clearly in fewer than 25 words. With AI, that lack of clarity can quickly turn into fragmented solutions and misplaced expectations.

In this episode of The AI Forecast, Paul Muller sits down with Paul McDonagh-Smith, a Visiting Senior Lecturer at MIT Sloan School of Management and a Senior Advisor to NASA's Goddard Space Flight Center, to explore how organizations can approach AI with greater clarity and purpose.

Ideas shaping the discussion:

• Why problem framing can determine the outcome of an AI initiative
• The difference between adopting AI and adapting with it
• What the scientific method can teach organizations about AI 
• Why AI’s imperfections make human judgment even more important
• How organizational mindsets influence technology outcomes
• Why organizations should invest in capabilities that AI cannot replicate
• The growing importance of trust in AI adoption 

From healthcare to energy, Paul sees enormous potential for human imagination and machine intelligence to tackle problems once considered out of reach. The future, in his view, will reflect the choices we make today.

Want to hear more about the organizational side of AI? Check out Ep 78 | Mastering Enterprise AI: Why Some Projects Succeed While Others Fail.

Stay in touch with Paul:

Paul McDonagh-Smith on LinkedIn: https://www.linkedin.com/in/paulmcdonaghsmith/

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