The success of ChatGPT has been both a blessing and curse for technology leaders. On one hand, it has opened up the world’s eyes to the seemingly unlimited potential of generative AI, increased investment to underfunded R&D teams and propelled technology to the top of the boardroom agenda. On the other, it has knocked other important AI and technology projects off course, syphoned resources from elsewhere to fuel a desperate game of competitor catch-up, and potentially created a massive compliance timebomb that could go off at any time.
In short, ChatGPT has become a distraction. Most forward looking and innovative businesses were already experimenting or implementing with AI, often to great success. The issue is that a lot of AI innovation isn’t always very obvious or sexy. Automating and optimizing a vital but mundane process may improve operational efficiency and contribute to the bottom line, but it’s unlikely to grab headlines in the same way as a language model capable of credible performance on a difficult exam.
As ChatGPT fever took hold, it seemed every business was racing to get their generative AI news out there ahead of the competition. And with good reason – analysis shows that the businesses in the S&P 500 that mentioned AI during earnings calls saw their share price outperform those that didn’t. The likelihood is that behind these companies’ AI announcements were accelerated timelines, a few all-nighters and, crucially, redirected efforts that had been busy somewhere else.
Great news for the stock price. Not so great for innovation strategies that now need another layer of scrutiny.
The irony is, even if in theory generative AI is available to everyone via a chat interface or a simple API and a credit card number, not everyone has grasped either the urgency or the most beneficial way of using this technology. Opportunities are being missed because…
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