Revelio Labs is a New York-based workforce-intelligence company that constructs labor-market datasets from public employment records, job postings, and professional profiles. It describes its data as spanning more than 30 million companies, over 5 billion job postings and 195+ countries (Source: prnewswire.com). Its chief executive is Ben Zweig and its chief economist is Lisa Simon (Source: prnewswire.com). In the debate over AI's labor-market effects, Revelio's data is one of the few sources that shows occupational composition at a higher frequency than official statistics. It has been cited both for evidence of AI-related restructuring and for evidence against broad AI-driven job loss.
Middle-manager postings
Revelio's most-cited figure in the AI context concerns middle-management hiring. For a Business Insider feature by Aki Ito published December 2, 2024, Revelio economist Lisa Simon compared job postings for four employee tiers with April 2022, which the article calls "the hiring heyday of 2022". At the low point of white-collar hiring earlier in 2024, postings were down 14% for junior roles, 43% for middle managers and 57% for senior leaders. By October 2024, postings for most tiers had rebounded, but employers were still advertising 42% fewer middle-management positions than in April 2022 (Source: businessinsider.com).
The Guardian's May 15, 2026 feature on AI-driven management cuts at tech companies repeated the figure, with a baseline in which managers made up 13% of the US workforce in 2022. It dated the decline to "the end of 2025", but the Business Insider article it linked to reports October 2024 data ('I didn't want to be the guinea pig': inside tech's AI-fueled manager purge (Guardian, May 15 2026); see Intelligence Replaces Hierarchy). The October 2024 data therefore predates the 2026 restructurings at Coinbase, Block and Meta described in the same Guardian feature. Business Insider attributed the decline to a "Great Flattening" of corporate hierarchies under way over the preceding two years, citing Meta, Citi, UPS and Amazon (Source: businessinsider.com).
The figure supports the argument that AI's organizational effect runs through coordination roles rather than through task automation at the front line, the thesis set out in Intelligence Replaces Hierarchy. Two cautions apply to that use. Postings data measures hiring intent rather than employment levels, and a decline measured against 2022 captures the post-pandemic hiring correction as well as any AI effect.
AI adoption and employment research
In June 2026 Ramp Economics Lab and Revelio Labs published "A New Look at AI's Impact on Jobs" (Kharazian, Simon and Stevens). The study linked Ramp card and bill-pay records of AI vendor spending to Revelio workforce records for 21,559 US firms observed monthly from January 2021 through February 2026. Using a staggered difference-in-differences design, it found that firms adopting AI grew headcount 10.2% over the two years after adoption. The gain came entirely from high-intensity adopters, which averaged about $33.67 of AI spend per employee per month, compared with about $2.78 for lower-intensity adopters, which saw no statistically significant change. Entry-level headcount at high-intensity adopters rose 12%. The authors state that adopters were already larger, more engineering-intensive, more likely to be venture-backed and faster-growing, and that the sample is not nationally representative and likely skews toward tech-forward firms. They also state that the 24-month window cannot rule out later reallocation within firms (Source: ramp.com). Ramp's lead economist Ara Kharazian cautioned that the results show correlation rather than causation (Source: bigtechnology.com). See AI Labor Disruption.
Revelio publishes an AI Labor Market Tracker, combined from September 2026 with its public employment statistics in a Monthly Workforce Update. The September 3, 2026 edition reported that employment in the most AI-exposed occupations had fallen about 6% relative to the least-exposed occupations since November 2022, and that the gap reached 19% among workers aged 22 to 25. It also reported that the most AI-exposed firms were recording fewer layoffs than the least-exposed firms. Simon said the data showed opportunities "becoming increasingly uneven" for younger workers in AI-exposed occupations, but "we still do not see evidence of broad AI-driven displacement" (Source: prnewswire.com).
Revelio Public Labor Statistics
Revelio announced Revelio Public Labor Statistics (RPLS) on August 12, 2025, a free monthly release of employment change, job openings, hiring and separation rates, and salaries in new postings. The data is broken down by occupation, sector and state and published the day before the Bureau of Labor Statistics (BLS) jobs and JOLTS reports. Revelio said RPLS draws on more than 150 million US profiles covering 85% of employed individuals. Zweig said "trusted data on the macroeconomy should be a public good", and Simon cited "underfunding and outdated methodologies" at the BLS (Source: prnewswire.com). In a one-year retrospective, Revelio placed the launch in the context of President Trump's August 2025 firing of the BLS commissioner and falling survey response rates. It reported that RPLS monthly employment changes correlated with BLS estimates at 0.77, against 0.67 between BLS and ADP. RPLS revisions averaged 47.7k jobs in absolute terms, against 44.3k for the BLS. JOLTS response rates had fallen to the mid-30% range from about 60% in the 2010s (Source: reveliolabs.com).
Relationships
- supports: Intelligence Replaces Hierarchy — supplies the middle-manager postings evidence
- related: AI Labor Disruption — Ramp–Revelio adoption study and AI Labor Market Tracker
- related: AI and Productivity
- related: 'I didn't want to be the guinea pig': inside tech's AI-fueled manager purge (Guardian, May 15 2026) — cites the middle-manager figure