Technology bubbles can pose difficult quandaries for business leaders: They may feel pressure to invest early in an emerging technology to gain an advantage over competitors but don’t want to fall for empty hype. As we enter a period of greater economic uncertainty and layoffs in multiple industries, executives are grappling with questions about where to cut costs and where to invest more.
The rapidly developing field of artificial intelligence and machine learning poses a particular challenge to business decision makers. Investments in proven predictive models are increasingly seen as sound and are expected to drive an increase in spending on AI from $33 billion in 2021 to $64 billion in 2025. But further out on the cutting edge, generative AI is sparking a huge amount of noise and speculation.
Generative AI refers to machine learning models — such as ChatGPT, Bing AI, DALL-E, and Midjourney — that are trained on vast databases of text and images to generate new text and images in response to a prompt. Headlines like “Ten ChatGPT Hacks You Can’t Live Without!” and “You’re Using ChatGPT Wrong! Here’s How to Be Ahead of 99% of ChatGPT Users” have begun to proliferate. Meanwhile, Axios reported that funding is pouring into generative AI, rising from $613 million in 2022 to $2.3 billion in 2023 — money that will only fuel the hype cycle.
This story is from the Summer 2023 edition of MIT Sloan Management Review.
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This story is from the Summer 2023 edition of MIT Sloan Management Review.
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