VCs Grow Cautious of AI‑Washing as Genuine Innovation Wins Funding
Key Points
- VCs are increasingly skeptical of AI‑washing and demand concrete proof of product performance.
- Gradient Labs secured a €11.1 million Series A by delivering a regulated‑industry customer‑service solution.
- The company’s technology was built to address compliance challenges identified at Monzo, not just to showcase AI.
- Investors now prioritize measurable outcomes, market fit, and differentiated value over AI buzzwords.
- Early relationship‑building with investors helped Gradient Labs shorten the fundraising process.
- Founders are urged to assess whether large AI providers could replicate their solution.
- A focus on deep expertise and rigorous product testing can overcome skepticism in the AI sector.
Investors who once rushed into any startup that mentioned artificial intelligence are now scrutinizing claims more closely. The practice of exaggerating AI capabilities—known as AI‑washing—is prompting venture capitalists to seek concrete proof of product performance and market fit. Companies that demonstrate real value, especially in tightly regulated sectors, are attracting capital despite a broader slowdown in AI‑driven funding. Gradient Labs, a customer‑service platform built for regulated industries, illustrates how focused product development and strong investor relationships can secure a successful Series A round without relying on hype.
Venture Capital Shifts Toward Substance
In recent years, the promise of artificial intelligence acted as a magnet for venture capital, with many firms eager to back any startup that referenced AI. This enthusiasm led to a surge in capital flowing into AI‑centric businesses, even when the technology was only loosely integrated or primarily a marketing angle. However, investors are now becoming wary of "AI‑washing," the practice of overstating a company’s use or capabilities of AI to attract funding.
Evidence of this shift includes a noticeable decline in overall AI‑related investment, suggesting that the era of easy capital driven by buzzwords is ending. Venture capitalists are increasingly demanding tangible demonstrations, measurable metrics, and clear evidence that a product works in real‑world conditions before committing capital.
Genuine Innovation Still Finds Support
Despite the broader slowdown, startups that deliver real, differentiated solutions continue to secure funding. Gradient Labs, an AI‑powered customer‑service platform for highly regulated industries, successfully closed a Series A round valued at €11.1 million. The company’s founders emphasized that their technology was not built for AI’s sake but to solve a specific compliance‑driven problem they encountered while working at Monzo, a leading UK fintech.
By focusing on a clear use case—automating customer interactions in sectors where mistakes can cause severe reputational damage—Gradient Labs created a product that consistently outperformed human agents. This performance, backed by concrete data, resonated with investors who prioritized proof over promises.
Product Quality Over Pitch Flair
The experience of Gradient Labs underscores a broader lesson for founders: product quality now outweighs flashy pitches. Investors are no longer convinced by the label "AI‑native startup" alone. Instead, they scrutinize whether a solution is truly irreplaceable and whether it can maintain a competitive edge as AI technology rapidly evolves.
Founders are encouraged to assess the likelihood that a large AI provider, such as OpenAI, could replicate their solution with a new model release. If the answer is high, the startup’s long‑term relevance may be at risk. Gradient Labs mitigated this risk by hiring deep expertise, obsessively refining their platform for 14 months, and ensuring that even a single error would not jeopardize compliance.
Building Trust Through Relationships
Beyond product development, establishing early relationships with investors proved crucial. Gradient Labs spent months engaging with potential backers, sharing updates, and allowing investors to verify claims and speak with customers before the formal pitch. This groundwork meant that when the funding round opened, the company was already familiar to investors, reducing the reliance on cold outreach and increasing the speed of decision‑making.
The company’s network effect also generated momentum, as even investors who passed on the round helped spread awareness of the startup’s credibility. This relational approach aligns with the current climate of heightened skepticism, where trust and verified performance are paramount.
Outlook for AI‑Driven Startups
While the AI boom may be cooling, capital remains available for startups that solve genuine problems rather than chase hype. The shift toward diligence and proof‑of‑concept suggests a more sustainable investment environment, where innovation is rewarded on its merits. As long as founders focus on delivering real value, particularly in complex, regulated markets, they can still attract the venture funding needed to scale.