Artificial intelligence is harder to implement than most CIOs think, and most lack the experience and insight needed for a successful AI project. The experiences of early adopters can help CIOs identify the best ways to implement this emerging and evolving technology for their firms’ specific needs.
- AI in Insurance: What CIOs Can Learn From Early Adopters of a Promising but Early-Stage Technology
- Lesson No. 1: No One Technology Is Right for All Insurers’ AI Needs, and AI Product Selection Is Unusually Difficult
- Lesson No. 2: Ensure That Your AI Project’s ROI Targets, Metrics and Timing Are Clearly Understood by Both the Business and IT
- Lesson No. 3: Begin With a Small Use Case That Addresses a Real-World Problem and Can Deliver Measurable Results Reasonably Quickly
- Lesson No. 4: Build an AI Team With the Skills and Expertise Necessary for Project Success, Including the Business, IT, Data and Innovation Organizations
- Lesson No. 5: Reduce the Risk of Project Failure by Ensuring That Data Is Clean, Accessible and Holistic
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