Investors face challenges in balancing the risk of missing out on an AI leader against the risk of investing in a company engaged in AI washing.panida wijitpanya/iStockPhoto / Getty Images
There’s a tsunami of capital pouring into artificial intelligence, bringing with it attractive rewards but also new risks for investors. A recent Goldman Sachs Global Institute study estimates that U.S. companies are poised to invest US$7.6-trillion in AI-related infrastructure by 2031. Alongside the trend is a growing number of companies branding, or rebranding, themselves as AI firms, raising the spectre of “AI washing.”
A recent analysis from The Financial Times shows that dozens of firms from sectors as diverse as gold mining, cancer treatment and footwear have rebranded themselves as AI companies since 2023. Initially, the rebranding increased total valuations by US$8.7-billion. However, the gains were short-lived, with some of the companies now sporting lower valuations than before their AI rebrand.
Peter Hofstra, senior vice-president and co-head of equities, research, at CI Global Asset Management and co-portfolio manager of CI Global Artificial Intelligence Fund, says “AI washing” may be a function of several factors.
One is the backdrop of every enterprise having to deal with AI in some way, either as a generational opportunity or as an existential threat.
“A lot of the chatter around AI use is very real, but it can get exaggerated, especially when someone’s trying to achieve a certain outcome, whether that’s a higher stock price or to support a capital raise,” Mr. Hofstra says.
“‘AI washing’ is classic capitalism, in which everyone wants to jump on the train and go for a ride. It’s essentially a marketing tool.”
Another vector may be the vague definition of what AI is.
“The only definition I’ve found is: if something appears intelligent and it’s not biological, it must be artificial intelligence,” Mr. Hofstra says.
“Yet, there’s a lot of deterministic programming that looks intelligent. When the first computer beat a chess master, it was all deterministic programming, but it seemed very intelligent,” he adds.
A related issue may be an AI knowledge gap among company leaders. During first-quarter earnings calls from S&P 500 companies, executives at 337 firms talked about AI.
However, a report by AI-Driven Enterprise Institute (AIDE), which scores companies on their AI initiatives, found that “literacy among the S&P 500 board members and executives in AI is not where it needs to be.”
Hence, in some cases, “AI washing” may be less a function of deceptive business practices and more a lack of AI maturity among chief executives amid rapid technological change. For business leaders, the financial incentives to highlight their companies’ AI capabilities are strong, Mr. Hofstra says.
Mickey Ganguly, associate portfolio manager at CIBC Global Asset Management in Toronto, who specializes in the global technology sector, notes several common red flags that could indicate exaggerated AI claims, starting with an executive who is unable to explain clearly how their company uses AI.
“If they’re a legacy technology company and are suddenly calling themselves an AI company, or they claim to be generating growing revenue from AI, but they’re not showing rising capital investments in R&D, that would give me pause,” he says.
“Sometimes, companies say they have proprietary data, but what they’re really doing is pulling their customers’ data with no real insight,” he adds.
He says some sectors, such as enterprise software, are more prone to “AI washing” because they are more likely to report that they have proprietary data and use AI to target their audience better.
“Are they really doing that, or is it just based on what they’ve always done?”
He prefers investing in Alphabet Inc. GOOGL-Q or Meta Platforms Inc. META-Q, for which “AI washing” is less of a concern, as they’re investing in their capabilities, which are supported by accelerated growth. Currently, he runs a concentrated portfolio of 35 technology stocks in which he has high conviction.
Mr. Hofstra acknowledges the challenge investors face in balancing the risk of missing out on an AI leader against the risk of investing in an “AI-washing” company.
“You don’t have to go too far to find out if someone is just trying to ride the wave or if they really have something innovative that could benefit the current trend,” he adds.
Mr. Hofstra focuses on companies that have true proprietary data and can use AI to provide valuable insights back to their customers.
The aforementioned Alphabet and Meta are mega-cap examples; however, even a smaller firm, for example, one that collects medical records at a metadata level and then uses AI to tease out why a placebo works half the time, could generate substantial economic value for its clients.
“If you’re truly the trusted partner and key in a decision framework that the [client’s] business depends on, that stickiness can certainly keep you in the game.”
However, he cautions investors to tread carefully, “because there are so many powerful and big things happening right now” in terms of AI development.