Summary

‍In this conversation, Mio Suzuki, an AI strategist and founder of MoD+M, discusses the practical adoption of AI in traditional industries. She shares her journey from engineering to AI consultancy, highlighting the challenges businesses face in understanding and implementing AI. Mio outlines a four-step AI adoption model and provides a real-world example of how she helped a bicycle manufacturer integrate AI into their operations. The discussion emphasizes the importance of stakeholder involvement, ROI estimation, and overcoming organizational skepticism towards AI. Mio also shares insights on designing AI solutions, the role of internal champions, and the future of AI in business.

Takeaways

• AI adoption in traditional industries is often hindered by misconceptions.
• Understanding the business problem is crucial before implementing AI.
• A four-step model can guide AI adoption effectively.
• Stakeholder involvement is key to successful AI projects.
• Estimating ROI helps in gaining leadership buy-in for AI initiatives.
• Internal champions can significantly aid in AI project execution.
• Education on AI is essential for organizational alignment.
• Automation of repetitive tasks can yield quick wins with AI.
• Real-world examples illustrate the tangible benefits of AI.
• The future of AI includes the integration of AI agents in business processes.

Chapters

• 00:00 Introduction to AI in Traditional Industries
• 03:01 Mio's Journey and the Birth of Mod-D
• 05:49 Challenges in AI Adoption
• 09:06 The Four-Step AI Adoption Model
• 11:47 Real-World Example: AI in Bicycle Manufacturing
• 15:02 Stakeholder Involvement and ROI Estimation
• 17:51 Designing AI Solutions
• 20:58 Overcoming Roadblocks in AI Implementation
• 23:52 Lessons Learned and Future Directions
• 27:05 Quick Wins for AI Adoption
• 29:56 Looking Ahead: The Future of AI Agents