HBR IdeaCast
Setting AI Projects Up for Success
Dec 5, 2023
Iavor Bojinov, an assistant professor at Harvard Business School and former LinkedIn data scientist, shares his expertise on successful AI project management. He discusses the high failure rate of AI initiatives, stressing the importance of strategic setup. Listeners learn about five critical steps: selection, development, evaluation, adoption, and management. The conversation also delves into balancing innovation with ethical standards, the significance of user trust, and the cyclical nature of project management to harness AI's potential effectively.
24:53
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Quick takeaways
- Choosing the right project is critical for AI success, focusing on impact and feasibility while understanding the intended audience helps involve them in the process.
- Evaluation is crucial for AI projects, requiring attention to ethical considerations, unintended consequences, long-term effects, and constant evaluation and improvement.
Deep dives
Failure Rate of AI Projects
AI projects have a higher failure rate compared to traditional IT projects. This is due to the probabilistic nature of AI, which adds complexity and uncertainty. AI projects can fail at different stages, such as selecting a project that does not add value, low accuracy of algorithms, or the presence of biases. Trust is crucial for AI projects, as users need to believe in the product and its developers.
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