The AI mistake companies are making — and how they can fix it, according to a BCG tech leader

Business Insider

11-05-2025

Like a first date that's gotten awkward, some companies struggling to win at artificial intelligence might be trying too hard.
They might take on too many projects or fail to understand that AI windfalls often come from rewiring how people work, not from "super-cool" AI engines or large-language models, said Sylvain Duranton, global leader of BCG X, the tech build and design division of Boston Consulting Group.
Those types of missteps can balloon into big-time frustrations for business leaders, he told Business Insider.
Duranton said that if CEOs' big question around AI in 2024 was which model to use, their ask in 2025 is "Where's my money?"
Indeed, he said, there are often challenges around implementing broad use of AI.
"Scaling this thing from a tech standpoint — it is hard," Duranton said.
To help companies salvage their AI efforts, he said, his "golden rule" is that organizations allocate about 10% of their effort and money to the algorithms — to build AI engines or train LLMs. Another 20% should be reserved for data and technology. Essentially, that's to make the AI work in a company's tech environment, Duranton said.
The bulk of the effort — the remaining 70% — should go to changing the way people work, he said.
"Assuming you have a technology that can scale, you need to bring that into the hands of the people. It's a massive change effort," said Duranton, who's based in the company's Paris office and oversees BCG X's global army of nearly 3,000 technologists, scientists, programmers, engineers, and others.
Some companies are struggling
Companies' frustration is real. In the final months of 2024, BCG surveyed some 1,800 C-suite execs from big companies in nearly 20 countries and found that while 75% of respondents ranked AI among their top-three priorities, only 25% reported seeing "significant value" from the technology.
To find more value, Duranton recommends that companies not try to do everything all at once. He said the scope of change that companies need likely can't be achieved with tens or hundreds of use cases.
"That's not the plan. The plan is to focus on a very few things, and the things that matter," he said.
Duranton said companies sometimes also look to "incremental initiatives." He said he thinks that's often a mistake. Instead, he said, companies should home in on a few "quintessential" things.
For a retailer, Duranton said, this might be using AI to ensure a brick-and-mortar store has the perfect product mix for that location to better withstand competitors nearby and online.
Retail CEOs understand the stakes, Duranton said. They'll often tell him something like, "I know that if I don't do that better than others, I'm cooked," he said.
Duranton said another imperative for a retailer might be to develop an AI agent that can shop for customers — one that's so good that users won't want to switch to a competitor.
"With those two things, you have both a strategic agenda and an AI agenda," he said, referring to making sure inventory is dialed and the shopping bot.
The trick, then, is to keep the focus on those efforts, Duranton said.
"Those quintessentials, that's where you put all your money, all your energy," he said. That's necessary, Duranton said, if companies want to take the 10%, 20%, 70% approach he recommends.
AI's Bermuda Triangle
He said scaling AI is also often difficult because companies can feel pressure to compromise on expenses, quality of results, or the speed at which they're produced.
"You have a sort of Bermuda Triangle, where it is either costly and relevant with a good latency, or you have to compromise on one of the three, and you have to optimize," Duranton said, referring to AI results.
He said it's often easy to demonstrate some tech wizardry in a demo. What's difficult, Duranton said, is handling millions of requests every day and producing timely and relevant results.
"It's a different ballgame," he said.
Ultimately, to succeed with AI, Duranton said, companies will need to bring along people, not just bots.
"Invest in change-management, not just technology, and have your fearless and strongest leaders be in charge," he said.