Navigating the Balance Between Speed and Effectiveness in AI Development

Unfortunately, you can’t set up your organization’s artificial intelligence projects like just any other IT project. By their nature, AI endeavors are quite different and suffer high failure rates. But there are proven approaches you can take to increase your odds of success. Iavor Bojinov, assistant professor at Harvard Business School and former LinkedIn data scientist, breaks down five critical steps for an AI project to turn into an effective product: selection, development, evaluation, adoption, and management. He’s the author of the HBR article “Keep Your AI Projects on Track.”

Key episode topics include: artificial intelligence, project management, product management, product launches, trust, employee engagement, technology and analytics, competitive strategy, strategy,

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