HBR On Strategy
The Right Way to Launch an AI Initiative
May 7, 2025
Iavor Bojinov, an assistant professor at Harvard Business School and former LinkedIn data scientist, delves into the challenges of launching AI initiatives, which often fail due to their complexity. He outlines five key steps for success: selection, development, evaluation, adoption, and management. The discussion highlights the importance of trust between users and AI, balancing speed with ethical standards, and the critical role of experimentation. Case studies from Etsy and LinkedIn reveal valuable lessons about user interactions and strategy alignment.
25:01
Episode guests
AI Summary
AI Chapters
Episode notes
Podcast summary created with Snipd AI
Quick takeaways
- Selecting the right use case is crucial for AI project success, necessitating a balance between technical feasibility and strategic business alignment.
- Ongoing evaluation of AI products is essential to understand their broader implications, ensuring they deliver value and adhere to ethical standards.
Deep dives
High Failure Rates of AI Projects
AI projects face a staggering failure rate, with approximately 80% failing due to a variety of complex factors. Unlike traditional IT projects, AI initiatives are inherently probabilistic, leading to unpredictable outcomes with repeated attempts. This uncertainty means that even well-planned projects can fail if they do not deliver valuable results or if the algorithms are biased. The challenge is compounded by the necessity for user trust; if users do not trust the AI product's capabilities, they are less likely to engage with it, regardless of its potential benefits.
Remember Everything You Learn from Podcasts
Save insights instantly, chat with episodes, and build lasting knowledge - all powered by AI.
