Investment in artificial intelligence (AI) is accelerating rapidly, prompting both significant opportunities and heightened risks for investors. A recent study by Goldman Sachs Global Institute projects that U.S. companies will pour approximately US$7.6 trillion into AI-related infrastructure by 2031, underscoring the sector's expanding economic influence. However, this surge in AI spending has also led to an increase in firms adopting AI-related branding, a phenomenon known as "AI washing," which raises concerns about the authenticity of such claims.

An analysis indicates that since 2023, companies across a wide range of industries—including gold mining, cancer treatment, and footwear—have rebranded themselves as AI firms. This rebranding initially boosted their combined valuations by about US$8.7 billion. Nevertheless, many of these companies have seen their market value decline, in some cases falling below pre-rebrand levels, suggesting that investors are growing skeptical of superficial AI claims.

Peter Hofstra, senior vice-president and co-head of equities research at CI Global Asset Management, explains that "AI washing" stems from multiple factors. Given AI’s broad impact, companies either view it as a transformative opportunity or an existential threat, leading to extensive discussion and, at times, exaggeration about AI use to influence stock prices or support capital raises. Hofstra describes this trend as a classic marketing strategy in capitalism, where firms seek to capitalize on AI’s hype.

A contributing challenge is the lack of a precise, universally accepted definition of AI. Hofstra notes that the term often encompasses any system that appears intelligent and non-biological, blurring the lines with traditional deterministic programming, which can mimic intelligent behavior without leveraging true AI techniques.

Moreover, a recent report from the AI-Driven Enterprise Institute highlights a significant AI literacy gap among S&P 500 executives and board members, despite widespread references to AI during first-quarter earnings calls. This suggests that some instances of "AI washing" may reflect limited understanding rather than intentional deception.

Mickey Ganguly, associate portfolio manager at CIBC Global Asset Management, identifies several warning signs of exaggerated AI claims. These include executives who cannot clearly articulate how AI is integrated into their business, legacy technology firms suddenly labeling themselves as AI companies without corresponding increases in research and development spending, or claims of proprietary data usage that amount to merely repackaging customer data without novel insights. Ganguly points out that sectors such as enterprise software are particularly vulnerable to overstated AI assertions, given their traditional reliance on customer data for audience targeting.

Investors, he recommends, might find greater assurance in established technology companies like Alphabet Inc. and Meta Platforms Inc., which demonstrate sustained investment in AI capabilities accompanied by measurable growth.

Hofstra advises caution but also emphasizes the importance of identifying companies with genuine AI capabilities. Firms with proprietary data that employ AI to generate meaningful insights—and that serve as trusted partners integral to client decision-making—have the potential to create lasting economic value. He notes that while large-cap companies dominate the AI landscape, smaller firms leveraging specialized data, for example in healthcare research, could also play a significant role.

Ultimately, investors face the challenge of balancing the risk of missing out on true AI innovators against the pitfalls of AI hype. Hofstra underscores the need for thorough due diligence to distinguish substantive AI initiatives from superficial rebranding amid a rapidly evolving technological environment.