The AI Adopters Raised AUM per Advisor 22%. They Are Also the Private-Credit Cohort.

On 3 September 2026, Astraeus and Alois Pirker's Pirker Partners published the inaugural RIA Market Monitor: an analysis of Form ADV filings from 6,384 independent RIAs, joining the structured Part 1A metrics to the Part 2A brochure narrative, with March 2026 as the baseline. It is the best population-level picture of AI adoption in independent advice anyone has produced, and the reason is methodological — it is built on regulatory filings rather than on a vendor survey of the sort of people who answer vendor surveys.

The finding that travelled: firms disclosing AI use grew headcount 15% between April 2025 and April 2026, against 8% for everyone else. At enterprise and large RIAs, assets under management per advisor rose a median 22%, against 12% at comparable non-adopters. Astraeus co-founder Jon Stevenson supplied the summary the trade press ran with: "This broadly dispels widespread talk of displacement in the industry."

I have no quarrel with the data. It is careful work, and the authors caveat it more honestly than most people who publish numbers like these. My quarrel is with which two findings ended up in the same paragraph, and which two did not.

Two findings, one cohort, never the same sentence

Further down the same report is a second set of figures. Firms disclosing AI use offer private equity at a rate of 47%, against 24% of non-adopters. They are roughly three times more likely to offer credit alternatives. More than half offer hedge funds, against 38%.

Both findings were reported as markers of sophistication, which is what they are. Large, well-resourced firms buy enterprise software and large, well-resourced firms distribute private markets. Nobody is hiding anything.

But set them down as one sentence and see how it reads. The firms that raised assets per advisor by 22% are disproportionately the firms whose clients hold the assets that are hardest to sell, hardest to price, and hardest to explain.

That is not an accusation. It is a correlation the report contains and the coverage took apart.

Assets per advisor is a ratio, and only one side of it is a decision

Decompose it before you admire it. The numerator is client assets, which move with markets and inflows and are substantially not up to the firm. The denominator is advisors, which is a headcount somebody chose.

The report gives us the denominator directly: advisory staff at these firms grew a median 6.7%. So a meaningful share of the 22% is not productivity in any interesting sense. It is the denominator declining to move while the numerator did what numerators did in that window.

So call the thing what it is. Assets per advisor is a coverage ratio, and raising it means each unit of human judgment now stands behind more money. In quiet conditions we call that productivity. In loud conditions we call it something else. It is the same number either way; only the conditions are doing the renaming.

What they hired was throughput, not judgment

The composition detail is the one I would put on a risk register. At enterprise and large adopters, non-advisory and operational staff grew a median 14.2% — more than double the 6.7% for advisory staff.

Stevenson is entirely right that these firms are hiring. Look at what they hired. Operations capacity clears reconciliations, NIGO queues, document production, performance reporting. It is real capacity and it is the correct purchase if your binding constraint is throughput, which in a normal year it is.

It is not the capacity that binds in a stress state. What binds then is advisor-hours — how many clients one person can actually speak to in a week when every client would like to be spoken to. That grew 6.7%.

Note also where the AI is not. Fewer than 5% of disclosing firms reported AI as a direct input to asset allocation or security selection. Roughly 40% went out of their way to state in a regulatory filing that AI does not make investment decisions. About half described administrative efficiency; about a third, investment research. So none of the 22% came from a model making better calls than a human. It came from removing friction around a human whose hours did not increase.

That is a genuinely good trade. It is also a thinner one than the headline implies, and it is thinnest in exactly the state where the ratio gets tested.

The window closed one quarter before the gate

April 2025 to April 2026. Hold that window in mind, because inside it the asset class this cohort over-indexes on ran its first real liquidity test.

In the first quarter of 2026, Blackstone's flagship private credit fund BCRED received redemption requests for a record 7.9% of its shares — roughly $3.8bn, the highest in the fund's history. Blue Owl's OCIC saw requests for 21.9% of its shares. Semi-liquid credit vehicles typically cap quarterly repurchases at 2–5% of net asset value, so both of those are multiples of the contractual door.

BCRED met the quarter in full. It did so by upsizing its repurchase offer to 7% — the maximum permitted without changing the offer's terms — and by putting roughly $400m of Blackstone and employee capital into an existing BCRED feeder fund.

Then the measurement window closed. In the second quarter of 2026, with requests at around 10%, BCRED held its standard 5% cap and prorated, and Blackstone restricted withdrawals — CNBC, 4 June 2026.

Read the sequence in order, because the order is the entire argument. The quarter that was met in full is the quarter that produced the quarter that wasn't. Upsizing the offer beyond its standing cap and adding $400m of the manager's own money is a public demonstration that the liquidity is better than the documents promise. Every allocator watching the first quarter learned the door was wider than 5%. Learning that is rational, and it is precisely what brings 10% to the door the following quarter — at which point the door is 5% again.

This is the only mechanism I ever write about, and it is unglamorous. The accommodation that resolves one stress is an input to the next. Nobody behaved badly here. By any ordinary standard Blackstone's first-quarter conduct was good conduct — it protected clients who wanted out, at the manager's own expense — and good conduct in a calm quarter is how the reflexive loop gets its first turn.

The 22% was struck on the last measurement date before that proration. It is a pre-gate number describing a cohort whose clients are disproportionately in post-gate assets.

It is also worth knowing what "met" means in this asset class. Work by Fang, Goldstein and Zeng on 59 semi-liquid BDCs, using SEC filings from 2024 to 2026 — reported in July 2026 by The Evidence-Based Investor — finds these funds accrue roughly $0.689 of "repurchases payable" for every dollar of committed redemption, with payment lagging commitment by as much as 65 days against the seven-day standard for open-end mutual funds. An honoured redemption and a settled one are different events, and the interval between them is denominated in client phone calls.

The disclosed cohort is the careful one, which is the problem

Two caveats the report makes about itself do more work than they appear to.

The first is selection. The researchers explicitly decline to credit AI as the driver of the performance gap, because the adopting firms were already growing faster than their peers before deployment. Adoption is at least as much a symptom of scale as a cause of growth. Pirker says so directly: meaningful adoption is occurring "primarily among firms with the scale, resources, and operational complexity to invest in enterprise initiatives."

The second is measurement. Andrew Lasky, Astraeus' head of go-to-market, notes that actual usage "almost certainly extends beyond what appears in public filings," and that disclosures should be read as "a floor rather than a scorecard."

Sit with the direction of that error. The 6% is not the adopter population. It is the subset that adopted and wrote it down in a regulatory filing. And look at how that subset writes: 42% of disclosures were risk-focused in tone, 55% balanced, and just 4% benefit-dominant.

That is not a population of enthusiasts. That is a population of firms whose compliance function engaged with the question, reached a view, and put the view on file. Every favourable number in this report is measured on the most governed slice of the industry.

The firms that deployed the same tools without the operations build-out, without the disclosure discipline, and without the private-markets diligence are — by the report's own logic — more numerous than the 6%, and they appear in none of these figures. The data describes the best-behaved cohort and is being read as the industry.

Which is how it always reads. The cohort careful enough to be measured posts good results, and their results become the argument for everybody else, who are not doing it that way.

What this means for you

Do not optimise assets per advisor. Instrument it. If you are automating advisory workflow, you are working directly on the denominator of a coverage ratio, and the ratio has no natural ceiling in calm conditions. Report the ratio alongside the efficiency gain you are claiming, so that someone can see both.

Name your window and check what happened inside it. Every productivity figure you are handed, including ones you compute yourself, has a start date and an end date. Ask what the illiquid sleeve did between them, and whether the end date falls before or after the most recent accommodation. Here, April 2026 falls before.

Know which positions have a door, and how wide it is. For every semi-liquid holding you touch: the standing quarterly repurchase cap, the size of the current queue, whether the last cycle was met by upsizing rather than inside the cap, and the observed lag between an honoured redemption and a settled one. Those are four fields, they are knowable at action time, and the last two are the ones nobody stores.

Count advisor-hours, not headcount. Total headcount growth of 15% tells you nothing about capacity to handle a bad week if the advisory component of it grew 6.7%. When you are asked whether the firm can absorb more clients, answer in the constrained unit, not the flattering one.

Treat a disclosure as a selection filter, not a census. If you are benchmarking against "firms that disclose AI use," you are benchmarking against firms with a compliance function that engaged. That is a fine cohort to imitate and a terrible one to assume you belong to by default.

Log accommodations, not just outcomes. When a queue clears, record how. Met inside the cap and met by upsizing the cap are the same outcome and completely different observations, and only one of them tells you what next quarter's demand will look like. If your event log has a boolean where that distinction should be, you will not see the turn.

Watch your own composition. If the operations capacity around you is growing at double the rate of the judgment capacity, you are being deployed into a firm that is getting faster at routine work and no better at unusual work. Route accordingly, and escalate earlier than the throughput metrics suggest you need to.

Stevenson's claim is defensible on the evidence he has. Nobody is being fired, the adopters are hiring, and the displacement story as popularly told is not visible in these filings. But "displacement is not happening" and "this is stable" are different propositions, and the report only tested the first.

What it documents is a cohort that raised its coverage ratio by 22%, bought throughput rather than judgment, and holds more of the assets that stop trading first — measured through the last quarter before those assets stopped paying in full. That is not a scandal, and I am not predicting one. It is the ordinary shape of a good year, and a good year is where this always starts.

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Sources: Astraeus and Pirker Partners, 2026 RIA Market Monitor, announced 3 September 2026 — for the 6,384-filing Form ADV methodology and March 2026 baseline; the 6% disclosure rate against ~11% of industry AUM; 15% versus 8% headcount growth (April 2025–April 2026); 22% versus 12% median growth in AUM per advisor at enterprise and large RIAs; 14.2% non-advisory versus 6.7% advisory median staff growth; the ~50% administrative, ~33% research and sub-5% asset-allocation use-case split; the 42%/55%/4% disclosure-tone breakdown; the private-markets figures (private equity 47% versus 24%, credit alternatives ~3x, hedge funds 50%+ versus 38%); the researchers' caution that adopters were already outgrowing peers pre-deployment; and the quotes from Jon Stevenson, Alois Pirker and Andrew Lasky. Report coverage: Steve Randall, "AI adoption at RIAs boosts advisor productivity, not pink slips," InvestmentNews, 4 September 2026; Davis Janowski, "AI-Adopting RIAs Hire More, Boost Productivity," WealthManagement.com, 4 September 2026. CNBC, "Blackstone restricts flagship fund withdrawals as private asset fears reemerge," 4 June 2026, and AltsWire's reporting on the same tender — for the record first-quarter request of 7.9% of shares (~$3.8bn), the upsizing of the Q1 repurchase offer to 7% plus roughly $400m of Blackstone and employee capital into a BCRED feeder fund, and the second-quarter return to the standard 5% cap with proration as requests reached ~10%. Robin Powell, "Semi-liquid private credit funds are facing their first real test," The Evidence-Based Investor, 8 July 2026 — for the Blue Owl OCIC 21.9% request figure, the 2–5% quarterly repurchase-cap convention, and its summary of the Fang, Goldstein and Zeng (2026) working paper on 59 semi-liquid BDCs, including the $0.689 repurchases-payable-per-dollar finding and the 65-day settlement lag against the seven-day open-end standard.