Is artificial intelligence giving a big bottom-line boost to most companies? No is the resounding answer, according to a new study out today from the Boston Consulting Group and MIT Sloan Management Review. It found that only 10% of businesses have seen “significant financial benefits”* from increased revenue or cost savings.
But more and more companies are adopting A.I. Of the 3,000 companies surveyed across 29 industries and 112 countries in the spring of 2020, the study found 57% had A.I. pilots underway or were using A.I. in full-scale deployments, up from 44% in 2018. And 59% of these companies also say they now have an “A.I. strategy”—up from 43% last year.
So why are so few businesses seeing any real gains from the technology? The answer lies in how companies are configuring their organizations to use A.I. The most successful A.I. adopters, the report’s authors say, create a virtuous circle of learning between human workers and A.I. systems, in which each provides valuable insights to the other.
In one example, at the carmaker Porsche, an engineer had a Eureka moment while getting coffee from an automated machine. He suddenly realized that the machine made a different sort of sound when it was making a good cappuccino versus a watery one. This provided the inspiration for Porsche to create an A.I.-based system to detect anomalies in car parts by having the software listen for subtle differences in the parts’ sounds. The A.I. itself could never have suggested that Porsche look at acoustic data—that required human imagination. But A.I. was perfect for implementing the system.
The report identifies five “modes” of human-A.I. interaction: the A.I. decides and implements a decision on its own; the A.I. makes a decision which a human implements; the A.I. makes a recommendation to a human, but the decision remains in the human’s control; an A.I. generates insights from data that help the human’s decision-making calculus; humans make decisions that an A.I. system only evaluates after the fact.
The most successful companies were more likely to use multiple modes of interaction, with almost a third of them using all five modes and an additional third using three or four different modes. Those businesses that used all five modes were six times more likely to see financial gains from A.I. than those that relied on just one kind of interaction.
Critically, the businesses that saw the biggest gains from A.I. knew when to alter these modes to suit different kinds of situations. Walmart uses an A.I.-based system to present stocking recommendations to store managers. The managers can agree or disagree with them and provide feedback on what they would change. During the COVID-19 pandemic, when consumers’ purchasing behavior suddenly shifted, managers rejected many more of the A.I. system’s recommendations. But this, along with the managers’ feedback, provided new training data for the software. After retraining the A.I., Walmart found that its managers could rely more on the A.I.’s recommendations again.
But configuring a business to take advantage of A.I. requires a lot. BCG and Sloan Management Review found the companies that made extensive changes to many business processes were five times more likely to reap financial rewards from using A.I. than those that made only small changes to organizational structure and processes.
Shervin Khodabandeh, a BCG senior partner and one of the report’s authors, says that too many companies draw a false analogy between the adoption of A.I. and another technology overhaul that had a big impact on business processes: enterprise resource planning (ERP) systems in the 1990s. There’s a big difference, he says. ERP systems tended to force all businesses to adopt similar processes for key administrative functions.
“There is no generalized, standardized A.I. process,” he says. “An A.I. solution for one company is not generalizable to another company even in the same sector.”
BCG likes to say A.I. success is a “10-20-70 problem,” he says: 10% of the effort is designing the right algorithms; 20% is building all the underlying technology to gather the data and run the A.I. system; 70% is getting the organizational structure and processes right.
Few companies have seen big financial gains from A.I. because the structural changes to undertake are extensive. But Khodabandeh says the fact that 10% of companies have seen large gains from using A.I. means that it is not impossible.
*What’s a “significant financial benefit,” by the way? The BCG and Sloan authors defined it on a sliding scale: at least $100 million in additional revenue or cost savings for companies with more than $10 billion in annual revenues; at least $20 million in gains for those with yearly revenues between $500 million and $10 billion; at least $10 million for those with revenues between $100 million and $500 million; and at least $5 million for those with less than $100 million in annual revenues.
Several months ago for this newsletter, I interviewed Tom Siebel, the outspoken billionaire and CEO of C3.ai. To hear more of Siebel’s sharp takes on the development of artificial intelligence, check out this week’s edition of the Fortune’s Leadership Next podcast, hosted by Fortune‘s own CEO Alan Murray and senior editor Ellen McGirt. Siebel shares why he thinks A.I. should be regulated, why he won’t do business with China, and why, although C3.ai does work for the U.S. government, it won’t help the Pentagon build autonomous weapons. You can tune in on either Spotify or Apple podcasts.
With that, here’s the rest of this week’s news in A.I.