Executive search closed the first half of 2026 running hotter than it has in years, though the strength was far from evenly distributed, as has become the pattern.

Opened searches rose 1% quarter-over-quarter and 15% year-over-year to 1,612, the highest quarterly total in our dataset since early 2022. The headline figure, though, obscures a fairly wide dispersion beneath it. Private-equity and venture-backed demand climbed, public-company hiring firmed, and independent private-company searches fell sharply. The gains were concentrated rather than broad, flowing to the corners of the market where capital, much of it AI-related, has been building up.

Compensation, by contrast, was close to flat: median base held at $325K (unchanged QoQ, up 3% YoY) and OTE edged to $462K (up less than 1% QoQ, 2% YoY), with the small move in on-target earnings coming from bonus rather than base. That aggregate stability masks a widening split by function, arguably the quarter’s more interesting story, and one where the pull of AI is at least visible, even if not yet cleanly measurable.

Velocity told a now-familiar story of urgency without finality. The median time to identify a placed candidate held at 18 days — well below the 23 days of a year ago — while the time from identification to close stretched to roughly 89 days, near the top of our historical range. Firms appear quick to engage and slow to commit.

The through-line of Q2 was concentration, both of capital and of the hiring that tends to follow it. External analyses point in a broadly similar direction, if from different angles: BCG estimates that 50–55% of U.S. jobs could be reshaped by AI over the next two to three years, EY’s 2026 CEO Outlook describes a year of “disciplined ambition” in which AI spending is increasingly tied to ROI, and BCG’s 2026 M&A Outlook notes fuller deal pipelines than in recent years even as sponsors stay measured. None of that maps one-to-one onto executive search. But the general pattern of capital moving selectively, with hiring following it, is consistent with what our data showed this quarter.

Against that backdrop, the asset-class picture sorted cleanly into leaders and laggards:

• Private Equity. PE opened searches reached 579, up 14% quarter-over-quarter and 26% year-over-year, the highest single-quarter PE demand in our dataset. That is consistent with the pickup in sponsor activity others have flagged, which tends to surface first inside portfolio companies. The demand skews toward finance, operational, and value-creation leadership, the kind of hiring generally associated with positioning assets ahead of an exit window that many expect to reopen.
• Venture Capital. Venture-backed searches rose 7% QoQ and 26% YoY. The most striking piece is the earliest stage: Seed/Series A demand of 144, following 152 in Q1, marks the two strongest early-stage quarters we have recorded. It is tempting, and probably at least partly right, to tie that to the 2026 funding environment: global venture investment reached a record ~$510B in the first half, with a large majority flowing to AI and early-stage dollars up roughly 41% year-over-year. The caveat is that those dollars are unusually concentrated in a small number of large rounds, so record demand may sit on a narrower base than the headline suggests.
• Public Companies. Public-company searches rose 11% QoQ and 20% YoY, to 201, weighted toward leadership tied to financial discipline and efficient growth. The clear laggard sat outside all three sponsor- and venture-backed buckets: independent private-company searches fell 18% QoQ and 28% YoY, the quarter’s weakest cohort. Firms without a capital sponsor or venture tailwind appear to be the ones sitting this stretch out.

The compensation data shows the strongest signs of AI’s influence, though it is also the easiest to over-interpret. Aggregate pay barely moved, but the dispersion by function was pronounced.

Engineering leadership compensation rose 9% in base and 4% in OTE year-over-year, extending the double-digit engineering gains we first noted in late 2025 and running ahead of the broader market; in public companies, engineering base pay was up 27%. Product leadership moved the other way — base down 1% and OTE down 7% year-over-year, with the softness most pronounced at later-stage venture. Finance (up 14% base, 21% OTE) and HR (up 21% base, 20% OTE) posted the largest gains outright, while CEO and Sales/BD pay was flat to lower.

One reading of the engineering-versus-product split is that it echoes, at the executive tier, what AI coding tools appear to be doing lower in the org: as agentic assistants absorb more routine implementation, the premium may be shifting toward those who can architect systems and direct the tools rather than write the code themselves.

Some external figures are at least consistent with that story: PwC puts the wage premium for AI-fluent skills at 56%, and several trackers report steep declines in entry-level developer hiring. We would be cautious, though, about leaning on it too hard. Median compensation at this level moves on relatively small samples, functional definitions blur at the edges, and a single strong quarter for engineering — or a soft one for product — is not yet a trend. The divergence shows up clearly in the data, but what is causing it remains, for now, a hypothesis.

Velocity reinforced the same theme of discipline. The 18-day median to identify a candidate is roughly two weeks faster than at the peak of the 2021 boom, yet total time-to-fill is little changed, because the post-identification window has widened. Sourcing has gotten faster while final commitment has not. In a market where the cost of a wrong senior hire is high, and where the definition of the right one may itself be shifting, that hesitation seems understandable.

Q2 leaves the market more uneven than at most points in this series: sponsor- and venture-backed demand strong, independent private hiring receding, and pay flat in aggregate but re-sorting by function. AI is the common thread running through each of those observations, though its precise role is hard to prove.

The question worth watching is whether the engineering premium and the softer product numbers reflect a durable change in how AI-native organizations value their leadership, or simply a cyclical feature of an AI investment wave that is itself unusually concentrated: fewer than 3% of venture deals are absorbing most of the capital. Our data can’t yet distinguish between the two, and a quarter or two either way could tip the read.

For now, the more grounded takeaway is the one the last several reports have circled: demand returns in the places where capital and conviction line up, and hesitates most everywhere else. That the gap between how quickly firms engage candidates and how slowly they close them keeps widening suggests they are not yet sure which reading is the right one either.

About the Report

This report was developed to provide executive recruiters and talent leaders with data-backed insights to help them both gain a better understanding of the industry, market, and environment they operate in and make more informed decisions.

We anonymized and aggregated our data from more than 31,000 compensation and search records to construct the benchmarks, statistics, and trends you will see in this report. We also cross-referenced relevant industry analysis and sources to understand how leadership recruiting is being impacted by rapidly evolving macro and socioeconomic events, in addition to recent extreme volatility in growth markets.

Our data and combined research uncovers leading indicators for executive hiring, how public and private market fluctuations impact demand for leadership hiring, why VCs have been impacted more than others, what the forecast is for leadership hiring over the next few quarters, as well as trends with executive compensation benchmarks.