The buzz around artificial intelligence (AI) is undeniable in today’s tech-driven landscape. However, not all claims of AI prowess hold up under scrutiny. There’s a new phenomenon known as “AI washing,” where companies exaggerate their use of AI to appeal to investors, clients, and consumers.
Recently, the Securities and Exchange Commission (SEC) cracked down on two investment advisers, Delphia (USA) Inc. and Global Predictions Inc., for falsely marketing AI-enabled investment predictions. Despite claims of AI integration, these companies were not utilizing the technology as advertised. This case sheds light on a broader trend of misrepresentation within the industry.
AI washing isn’t limited to finance. Across various sectors, businesses are jumping on the AI bandwagon, often without the infrastructure or expertise to back it up. According to analytics firm FactSet, a record number of S&P 500 companies mentioned “AI” in recent earnings calls, raising questions about the authenticity of these claims.
Michael Stewart, managing partner at Microsoft’s venture arm M12, warns against the superficial adoption of AI for the sake of appearances. While it’s easy to incorporate AI into presentations or marketing materials, true innovation requires a deeper commitment. Stewart emphasises the importance of building sustainable competitive advantages through genuine AI integration.
Moreover, Timothy Bates, professor of practice at University of Michigan-Flint College of Innovation & Technology, highlights the risks associated with relying on superficial AI applications. Button-pushing solutions that lack true learning capabilities may provide short-term benefits but fail to deliver meaningful insights or value over time.
How to Navigate AI Washing
To navigate the murky waters of AI washing, industry experts offer practical advice. Toby Coulthard, chief product officer at Phrasee, suggests scrutinizing companies’ claims and seeking transparency regarding their AI practices. He encourages businesses to define their AI strategies clearly and demonstrate ethical considerations in their use of AI.
For investors like Stewart, evaluating AI startups involves a holistic approach. M12 employs the “four D’s” framework—data, dividends, distribution, and delight—to assess the viability of AI ventures. By focusing on factors like access to data, financial performance, market reach, and user experience, investors can distinguish between genuine AI innovation and empty promises.
As the AI landscape continues to evolve, distinguishing between hype and reality becomes increasingly crucial. By fostering transparency, accountability, and responsible AI adoption, businesses can harness the true potential of AI to drive meaningful progress and innovation.
