How to Capitalize on Generative AI

A guide to realizing its benefits while limiting its risks

by

and

Erik Brynjolfsson

by

and

Erik Brynjolfsson

From the Magazine (November–December 2023) · Long read

Michael Brandon Myers

01

How to Capitalize on Generative AI

02

Helping Employees Succeed with Generative AI

03

Keep Your AI Projects on Track

Summary.

Business leaders are struggling to understand how seriously they should take generative AI. It has already displayed breathtaking powers to create new content and is used to do things such as write software, transcribe physicians’ interactions with their patients, and let people converse with a CRM system. But it is far from perfect: It can produce distorted or entirely fabricated output and can be oblivious to privacy and copyright concerns. Is its importance being overblown? Are its risks worth the potential rewards? How can companies figure out where best to apply it? How should they go about taking their first steps? This article will provide guidance.

Idea in Brief

The Quandary

Fledgling generative-AI systems have huge potential but also are prone to fabricate answers, invade privacy, and violate IP rights. Given the risks, are leaders best off taking a wait-and-see attitude?

Why to Take the Plunge

This new technology is akin to the steam engine, electricity, and the internet but with one big difference: Whereas those general-purpose technologies took decades to have a major impact on competition and the economy, generative AI will do so in a few years.

How to Proceed

Inventory your knowledge-work jobs. Identify which of those roles would benefit most from the technology’s assistance. Prioritize projects whose ratio of benefits to costs is the largest. Take advantage of the available ways to curb generative AI’s risks. Use the agile approach to develop applications.

Business leaders are struggling to understand how seriously they should take the latest phenomenon in the world of artificial intelligence: generative AI. On one hand, it has already displayed a breathtaking ability to create new content such as music, speech, text, images, and video and is currently used, for instance, to write software, to transcribe physicians’ interactions with their patients, and to allow people to converse with a customer-relationship-management system. On the other hand, it is far from perfect: It sometimes produces distorted or entirely fabricated output and can be oblivious to privacy and copyright concerns.

A version of this article appeared in the November–December 2023 issue of Harvard Business Review.

Next In

Helping Employees Succeed with Generative AI

How to manage performance when new technology brings constant and unpredictable change

Andrew McAfee is the cofounder and co-director of the MIT Initiative on the Digital Economy and the inaugural visiting fellow in Google’s Technology and Society group. He is the author of the new book, The Geek Way, and coauthor with Erik Brynjoflsson of The Second Machine Age.
DR

Daniel Rock is an assistant professor of operations, information, and decisions at the University of Pennsylvania’s Wharton School and a cofounder of Workhelix, which creates generative AI strategies and implementation plans for companies.
Erik Brynjolfsson is the director of the Stanford Digital Economy Lab, a professor at the Stanford Institute for Human-Centered AI, a research associate at the National Bureau of Economic Research, and a cofounder of Workhelix, which creates generative AI strategies and implementation plans for companies.