EXPOSED
The median financial analyst spends most of the week on tasks LLMs already do at usable quality: pulling filings and transcripts, updating three-statement models and comps, writing earnings recaps, screening universes, and formatting decks. What persists is the part where a named human takes a position, defends it to a portfolio manager or an investment committee, and absorbs the consequences when it's wrong. There is no licensure wall for most of the job — Series 86/87 registration for published research and CFA norms are thin shields compared to a CPA signature or a PE stamp.
Headcount grew steadily across the period.
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing.
BLS projection, 2024–2034
+5.7% 368,500 → 389,600 on the projections basis
Exposed, but growing
AI can already do a lot of these tasks, and the BLS still expects +5.7% more of these jobs by 2034. Demand for the output is growing faster than the work is being automated away — the mechanism BLS gives for software developers, and the combination people most often misread as an error.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~25,100 openings a year on average, including replacing people who leave.
AnalystInvestorBank AnalystBond AnalystPrime BrokerBrand AnalystMoney ManagerStock AnalystTrust OfficerFiscal AnalystBanking AnalystFinance AnalystPricing AnalystPlanning AnalystTreasury AnalystCommodity AnalystFinancial AnalystInvestment BankerPortfolio AnalystPortfolio ManagerAccounting AnalystInvestment AnalystInvestment OfficerPricing Specialist
Holding it up: judgment & accountability . Weakest point: embodiment .
Core tasks are already automatable Building a DCF from a 10-K, spreading quarterly comps, tracking guidance changes across a coverage universe, and drafting the earnings-day note are all sequence-to-sequence work over structured filings and transcripts — the data feeds are machine-readable and the output templates are standardized, which is why this sits at 6 rather than in the mixed band where original channel checks or private-company diligence would push it.
Fully desk- and screen-based The job is a Bloomberg terminal, Excel, and a video call with management; the 2 rather than 0 covers site visits, plant tours, and conference attendance that a few sell-side and PE-side analysts still do, but nobody's model breaks because they couldn't be physically present.
Certification preferred, not legally required Series 86/87 gates publishing research and Reg AC requires the analyst to certify the view is their own, but no statute makes an analyst personally answerable for a bad price target — enforcement lands on the firm's supervisory failures, which is why this is 6 and not the 12-plus that a CPA attesting to financials carries.
Meaningful discretion Setting the terminal growth rate, deciding a management explanation is not credible, and putting a Sell on a banking client's stock are consequential calls the analyst signs, but they route through an investment committee, a PM's position sizing, or a research director's review before capital moves — real discretion inside a mandate, not final authority over it.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (6/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (6/20) is whether the law requires a licensed human to sign. Trust premium (10/20) is whether buyers specifically pay for a person. Judgment and accountability (11/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 27 of this occupation's 35 points (77%).
Embodiment (2/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
No occupation passed every test: close enough to financial and investment analysts on skills and subject matter, at least 10 points more resistant, no big jump in training, no new licence, no pay cut, and not shrinking on its own. That happens for 223 of the 654 occupations here that aren't SAFE, and it is worth stating plainly rather than leaving the section off.
The usual reason is that exposure travels with the skill profile. The jobs most similar to yours tend to be exposed for the same reasons yours is, so the near neighbours don't clear the gap — and the ones that do are a different kind of work, not a transfer of what you already know. Read that as a limit of this method, not a verdict that you're stuck: it only compares whole occupations, and it cannot see specialisation, industry, or anything you'd bring that isn't in a federal skill survey.
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 51/100, still EXPOSED.
Genuine two-tier structure: if the filings-pull / comps-update / earnings-recap tier is fully absorbed by internal copilots (already underway at large banks and asset managers), the residual job is idea origination, channel checks and private-source diligence, and defending a variant view to an IC — work with no ground-truth label to train on
FINRA/SEC enforcement or rule interpretation requiring that a Series 86/87-registered supervisory analyst personally review and approve any AI-generated research content before publication, with named-person liability for the AI's factual claims — FINRA's 2024 Reg Notice 24-09 on gen-AI already asserts existing supervision rules (3110, 2210) apply to AI-produced communications; a formal rule making the approving analyst's registration the required sign-off (rather than firm-level supervision) is the concrete step to watch
Fiduciary-side analog: SEC adopting a final version of the withdrawn 2023 predictive-data-analytics proposal, or state fiduciary rules requiring a documented human analyst attestation on model-derived recommendations in advisory files; would make the analyst's name the audit artifact in exams
Investment committee minutes and allocator due-diligence questionnaires (ILPA, consultant DDQs) increasingly demand a named human decision-owner per position and an explicit statement of where the human overrode the model; formalizing 'who is accountable for this call' in mandate documents raises the score without any regulation
Allocators writing AI-disclosure clauses into IMAs or refusing to pay active fees for signals a client could generate themselves — the premium survives only where the human is the differentiator; watch for consultant questionnaires asking what fraction of research output is model-generated
The limit. The realistic ceiling is mid-50s. There is no CPA- or PE-style stamp available: most of the 362k workers are buy-side or corporate analysts with no registration at all, so liability shields reachable through FINRA touch only the published-research minority. Trust premium is structurally capped because the buyer pays for returns, not for authorship, and the sell-side product is already commoditized.
| New York-Newark-Jersey City, NY-NJ | 53,870 | $128,930 +25% |
| Los Angeles-Long Beach-Anaheim, CA | 19,600 | $102,260 +0% |
| Chicago-Naperville-Elgin, IL-IN | 17,150 | $101,750 -1% |
| Boston-Cambridge-Newton, MA-NH | 13,010 | $117,520 +14% |
| Dallas-Fort Worth-Arlington, TX | 11,530 | $100,350 -2% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 10,930 | $108,330 +5% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 10,050 | $95,400 -7% |
| San Francisco-Oakland-Fremont, CA | 9,910 | $130,520 +27% |
| Bridgeport-Stamford-Danbury, CT | 2,550 | $158,310 +54% |
| San Jose-Sunnyvale-Santa Clara, CA | 3,880 | $144,910 +41% |
| San Francisco-Oakland-Fremont, CA | 9,910 | $130,520 +27% |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 35. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.