MIT Sloan Management Review Article on Moving Beyond Islands of Experimentation to AI Everywhere

Companies in a wide range of sectors are making significant investments in AI — and are increasingly concerned with how to scale use of the technology to gain benefits from it across their organizations. Too many companies stall out on their AI journey and have difficulty getting past pilot projects or point solutions. That’s not necessarily because the technology is so complex. Our research finds that companies fail to extract the potential business value from AI not for lack of technical expertise but rather due to structural and process issues.

We took an in-depth look at the AI scaling journey of 10 market-leading legacy companies with three to eight years of AI implementation experience across diverse industries, including consumer packaged goods, pharmaceuticals, banking, insurance, security services, and automotive. These companies were at different stages of progress, ranging from relatively nascent capabilities to extremely sophisticated. How they organized their efforts at each stage had implications for what they were able to accomplish. We found that AI projects in enterprises generally begin as what we call islands of experimentation (IOE) before coming together around a corporate center of excellence (COE). Only a small number then move to a sophisticated federation of expertise (FOE) model built on a centralized base of knowledge, systems, processes, and tools, and on decentralized embedded capabilities.

About the Author

Amit Joshi is a professor of AI, analytics, and marketing strategy at the International Institute for Management Development (IMD). Ivy Buche is associate director of the Business Transformation Initiative at IMD. Miguel Paredes Sadler is vice president of AI and data science at Albertsons Companies.

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