"AI Washing": Understanding the Emerging Trend
Yesterday, I had lunch with a startup Chief Product & Technology Officer (CPTO) whose company was recently acquired by a PE firm. After some World Series chatter, he noted the rising trend of "AI Washing" among PE portfolio companies, with some overstating their AI capabilities to boost valuations and sales.
CPTOs in PE-backed firms are often in a unique position to observe the gap between authentic AI integration and superficial claims, appreciating both the potential benefits and the challenges of implementing true AI solutions in portfolio companies.
“AI Washing” refers to the practice of exaggerating or misrepresenting the use of AI in products or services. It’s similar to “greenwashing,” where companies claim to be environmentally friendly without substantive actions to support their claims. In the case of “AI Washing,” a product may have minimal or superficial AI components, yet companies promote it as advanced or transformative AI to attract attention or boost sales.
This can mislead customers, investors, service providers and the public about a product's capabilities and value. It is especially prevalent in industries where AI adoption is seen as a competitive advantage, leading some companies to overstate their use of AI technology to appear innovative or cutting-edge. This practice can undermine trust in genuine AI solutions and create confusion about AI’s actual capabilities.
PE firms appear to be leading the trend of engaging in “AI Washing” to capitalize on AI hype, often claiming AI integration to appear innovative and attract investors. Many firms use basic analytics or automation, branding them as “AI-driven,” rather than investing in advanced machine learning models or predictive tools that genuinely enhance performance. This practice can dilute real AI advancements and risk eroding investor trust, as true AI impact requires dedicated investment, expertise, and robust infrastructure that not all firms genuinely pursue.
Conclusion
The trend of “AI Washing” among PE firms risks undermining trust in real AI innovations, emphasizing the need for transparency and genuine investment in advanced AI capabilities.