Is generative artificial intelligence (AI) worth the money? Technology leaders such as Microsoft Corp chief technology officer Kevin Scott said costs would come down and capabilities improve, but as Wall Street heads toward correction territory — Nvidia Corp and Microsoft, two stocks that have ridden the AI wave, are down more than 15 percent and 8 percent respectively since July 10 — enterprises are grappling with a deeper problem: How do they put AI to use and measure the return on that investment?
Confusion around the answer has led to a growing malaise in recent months, sparked by bearish reports from Goldman Sachs Group Inc and Sequoia Capital questioning whether “genAI” would make as much money as the market seems to think.
AI capital expenditure is set to reach between US$600 billion and US$1 trillion in the coming years, the two reports estimate.
Meanwhile, spending on information technology is to rise 8 percent this year, Gartner Inc said.
If investors are taking a breather, that is a good thing.
Corrections can be healthy when a market position has been extreme, my colleague John Authers said about big tech stocks. The AI-driven market boom and a startling jump in capital spending at companies such as Alphabet Inc and Tesla Inc has happened far too quickly, benefiting those who did not always deserve the rally.
A senior AI executive at a large tech company told me point blank that artificial intelligence, despite being his bread-and-butter business, had become overblown in the market. He had lived through several hype cycles before, and this one was no different, he added.
Today at least, there are healthy differences to something such as the dotcom boom and bust. Businesses are emphasizing tangible outcomes more than they were back in the early 2000s, when the focus was more speculative and based on market potential. Metrics for success are focused on efficiency gains and cost savings instead of grabbing eyeballs. Businesses are also using more sophisticated risk models and arguably more rigorous return on investment calculations, because they have learned hard lessons from the dotcom era.
The nagging problem for generative AI is that tech firms have set expectations too high by marketing the technology as a magical, general-purpose solution that can enhance lots of business processes. It often cannot right away. Some companies are also rapidly rolling out gizmos to their workforces without showing how to use them effectively. That is always a mistake. Give a power tool to someone with training and they can build a treehouse; give it to an amateur and they would make a mess.
However, even while the process is often fitful, generative AI is taking hold in several markets. In the video games industry, major studios such as Activision Blizzard Inc are using it for concept art and asset generation, leading in some cases to widespread layoffs, an investigation by Wired magazine found.
JPMorgan Chase & Co CEO Jamie Dimon told Bloomberg News that the bank was putting AI into all of its processes — “trading, hedging, research, every app, every database” — sometimes to replace humans.
Payments company Klarna Bank AB said earlier this year that its customer service chatbot did the work of 700 customer service reps, meaning it could reduce the number of contractors it regularly hired, saving it US$40 million a year.
Corporate travel booking start-up TravelPerk said its margins have grown from less than 40 percent to 70 percent since it started using generative AI last year.
Analyzing AI’s return on investment is difficult. It involves taking abstract values such as efficiency and productivity, and turning them into numbers.
Take CNH Industrial NV, a farming and construction equipment manufacturer. It has been using an AI-powered chatbot to guide its service technicians on repairs and to help its software developers write code, a profile in CIOdotcom showed.
It is easier to measure success on the first project (did customer satisfaction scores go up?), but not so much for the second (did coders log how much time they saved?).
Do not forget that AI is also a controversial technology. Klarna CEO Sebastian Siemiatkowski got some blowback from users of X (formerly Twitter) when he posted details about how the company’s AI assistant “performs the equivalent job of 700 full-time agents.”
Some said it was callous to celebrate the displacement of so many human workers. If companies find that generative AI is helping their bottom line, they might not always want to talk about it.
Businesses and investors risk going too far in dismissing generative AI as all hype, especially if that means they would neglect some of its more insidious traits around the perpetuation of bias, copyright infringement and the erosion of human agency. The current skepticism is healthy and much needed — but in some markets, including customer service, marketing, gaming and other creative industries, it is also clear that generative AI is here to stay.
Parmy Olson is a Bloomberg Opinion columnist covering technology. A former reporter for the Wall Street Journal and Forbes, she is author of We Are Anonymous.
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