Successful AI adoption
summary
Argues against piecemeal, siloed pilots and insists on a holistic AI platform that uses microservices + MLOps, defines sprints for data curation versus modeling, and refuses AI when simpler automation suffices. Introduces an ROI metric called AI Valot that converts speed, cost, and CX gains into dollars and segments value by automation, AI, and analytics. Proposes a skills pyramid—AI prime (2–3 years of focused expertise), then architect, coach, champion—and treats people as the hardest change while applying proven software engineering disciplines.
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chapters (5)
- 0:00Start
- 0:17What Are the Challenges for Implementation for a Successful Ai Adoption Strategy
- 7:06Ai Architect
- 8:40Practical Tips
- 9:16Change Management What Are the Three Key Aspects of Change Management
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