Ethos secures $22.75 million in Series A funding to address the issues AI has caused in hiring.

      The London-based AI platform for expert matching, established by former DeepMind and McKinsey professionals, is currently being valued as hiring becomes an area in the labor market most affected by AI. The funding round is being led by Andreessen Horowitz, which is joined by General Catalyst, the initial seed investor.

      In just around 30 months, generative AI has significantly simplified the process for candidates to appear qualified for jobs, while simultaneously making it much more challenging for employers to assess their actual qualifications. This asymmetry is evident: tools for candidates have inundated the market with seamless CVs, refined cover letters, and AI-enhanced portfolios, whereas tools for recruiters that traditionally help distinguish meaningful information from irrelevant data—like screening, interviews, and references—have not advanced at a similar speed.

      As a consequence, by mid-2026, the hiring landscape will be dominated by a situation where the less expensive input has expanded rapidly, while the more costly input, the recruiter's time, has been inundated.

      Ethos, the London-based AI startup co-founded by former Google DeepMind and McKinsey alumni, believes this is a viable problem worth funding. On Wednesday morning, the company revealed a $22.75 million Series A funding round led by Andreessen Horowitz, with participation from General Catalyst, XTX, and Evantic. This is one of the largest Series A funding rounds for a UK AI startup this year, highlighting how seriously Andreessen Horowitz is considering the impact of AI on the labor market.

      What Ethos offers is straightforward: it is an AI-enabled expert network. Unlike companies like GLG and Guidepoint that have spent years building curated lists of consultants, retired executives, and specialist advisors for paid calls, Ethos employs AI for the curation process.

      In context, TNW’s broader coverage of the expert network sector is relevant here: GLG and Guidepoint's rosters are now data partners within Claude Opus 4.7. Ethos appears to be creating a different approach: instead of using existing expert networks for AI products, it generates expert profiles with AI and matches them to opportunities at a scale manageable only by a model-based system.

      As described on the company’s product page, Ethos has a two-pronged approach. An Ethos voice agent conducts a detailed interview with each expert, revealing the nuances of their professional knowledge in ways that a static CV cannot. Concurrently, Ethos’s AI analyzes the expert’s existing body of work—including academic papers, code repositories, blog posts, podcast appearances, and conference speeches—developing a richer understanding of the individual's actual expertise. The resulting profile is then matched autonomously with opportunities from the platform’s customer base.

      The range of opportunities is notably broad. According to the company, Ethos connects its experts to consulting assignments, expert calls, market research surveys, AI data-labeling tasks, and full-time jobs. The provision of AI data is structurally significant, as frontier model labs require high-quality, domain-specific training data in sectors where generalized web scraping is inadequate—such as finance, medicine, law, and advanced engineering. Ethos has positioned itself as a conduit for these labs to access verified domain experts at scale.

      The traction data shared in the announcement supports the Series A funding size, with the company claiming that over 5,000 experts are joining the platform weekly across various fields, including accounting, banking, consulting, law, technology, and healthcare, as well as skilled trades like electrical and plumbing work. This blend of white-collar professionals and skilled tradespeople is atypical for an expert network and aligns with Ethos’s broader proposition that validated expertise is the unit of value, regardless of how it was attained.

      On average, experts on Ethos reportedly earn an additional £4,500 per month through the platform, while the top 10% earn over £7,000. Since January, the number of experts generating income via Ethos has reportedly increased six-fold. An independent review on AItrainer.work, which assesses AI-training-adjacent expert platforms, noted that Ethos’s hourly rates ranged from $105 to $225, significantly higher than standard AI training compensation and consistent with the platform’s positioning for mid-to-senior roles.

      The sustainability of these figures will depend, as is commonly the case in expert-network economics, on the ongoing demand from customers. The paid expert call model risks collapse if the customer base shrinks, the supply of qualified experts exceeds demand, or successful engagements from AI-driven matching commoditize the experts themselves. Ethos’s strategy operates on the assumption that none of these scenarios will outpace its growth, particularly as it seeks to broaden its client base from private equity and consulting to AI labs and corporate research roles.

      The founders bring complementary expertise: James Lo, the CEO, previously worked as a strategy consultant at McKinsey and as an investor at SoftBank’s Vision Fund before establishing Ethos. Daniel Mankowitz, the CTO