MIT Sloan Management Review Article on The Working Limitations of Large Language Models

Large language models (LLMs) seem set to transform businesses. Their ability to generate detailed, creative responses to queries in plain language and code has sparked a wave of excitement that led ChatGPT to reach 100 million users faster than any other technology after it first launched. Subsequently, investors poured over $40 billion into artificial intelligence startups in the first half of 2023 — more than 20% of all global venture capital investments — and companies from seed-stage startups to tech giants are developing new applications of the technology.

But while LLMs are incredibly powerful, their ability to generate humanlike text can invite us to falsely credit them with other human capabilities, leading to misapplications of the technology. With a deeper understanding of how LLMs work and their fundamental limitations, managers can make more informed decisions about how LLMs are used in their organizations, addressing their shortcomings with a mix of complementary technologies and human governance.

About the Author

Mikhail Burtsev, Ph.D., is a Landau AI fellow at the London Institute for Mathematical Sciences, former scientific director of the Artificial Intelligence Research Institute, and author of more than 100 papers in the field of AI. Martin Reeves is chairman of the BCG Henderson Institute, focused on business strategy. Adam Job, Ph.D., is director of the Strategy Lab at the BCG Henderson Institute.

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