Free sampler. Re-scored every six months.
An entry-level financial analyst role scores 8.0 out of 10 for AI exposure, where 10 is most at risk — among the highest in this index. Wealth and financial advisory scores 4.6. The 3.4-point spread is one of the widest we measure. Finance protects the person in the room with the client, and offers very little to the person preparing the materials for that room.
The short answer for parents: yes for the relationship and judgment tiers — advising people, managing risk, owning decisions. Much less so for the spreadsheet tier, which is both the most automatable work we score and the traditional way in.
Every career in this index is scored 1–10, where 10 is most exposed to AI. Same six factors, same weights, applied identically to an analyst and a paramedic.
| Finance track | 2023 | 2025 | Now | 3-yr move | Band |
|---|---|---|---|---|---|
| Wealth / financial advisory | 3.9 | 4.2 | 4.6 | +0.7 | Low–Mod |
| Risk & compliance | 4.5 | 4.8 | 5.3 | +0.8 | Moderate |
| Investment banking (senior) | 4.9 | 5.3 | 5.7 | +0.8 | Moderate |
| Corporate finance / FP&A | 6.0 | 6.4 | 6.8 | +0.8 | Mod–High |
| Entry analyst / research | 6.4 | 7.3 | 8.0 | +1.6 | High |
2023 and 2025 figures are reconstructed using current methodology, not archived from past editions.
For scalethe median career in this edition scores around 5.5. A business analyst scores 7.6. Entry-level software development scores 8.1. Bedside nursing scores 2.8.
The entry analyst track moved +1.6 in three years — fourth-fastest in the index. One honest caveat on that figure appears below.
It is doing a great deal of what junior analysts were hired to do, and almost none of what senior advisors do.
Major firms have begun testing whether candidates can direct AI through modeling and research, rather than perform it, in final-round interviews. That is a profession redesigning what a first-year is for.
How wealth and financial advisory rates against each. Ratings are 0–10 on each factor's own terms.
So you can see what the analysis actually looks like.
Does someone need a human they can trust and hold responsible? — rated 9.0
Finance is almost entirely a screen-based profession. Nobody in it is protected by physical presence. So this one factor does most of the work separating a 4.6 from an 8.0, and it is worth understanding precisely what it measures.
Two things sit inside it. Trust: does someone need a specific human they can rely on? Accountability: must a human carry responsibility when it goes wrong?
A financial advisor rates 9.0 on both. Clients hand over decisions about retirement, a house, a child's education, an inheritance. When markets fall they want to speak to a person who knows their situation and can be held to the advice. Fiduciary and suitability obligations attach to a licensed human, not to a system. One firm leader's analogy is worth borrowing: robots assist in surgery every day, and patients still expect a surgeon in the room.
An entry-level analyst rates 4.0. They produce work that someone else signs off. No client knows their name. Nobody is relying on them personally, and no regulatory obligation attaches to them individually. The work is real and the accountability sits above them.
The pattern generalizes across this whole index: exposure falls as personal accountability rises. The further a role sits from someone answering for the outcome, the less protected it is — which is why the model consistently finds senior work safer than junior work in every profession that lacks a physical or licensing moat.
The uncomfortable implication for a finance graduate is that the protection cannot be acquired at the start. It has to be earned, and the roles where you traditionally earned it are the ones being compressed.
Ranked by exposure, safest first:
Finance is the most cyclical profession we score, and that makes its three-year trend harder to read than any other.
Deal activity slumped sharply in 2023–24 and recovered as rates stabilized. Hiring at major banks moved with it. So some portion of the +1.6 on the analyst track is almost certainly the deal cycle rather than automation, and we cannot cleanly separate the two.
What persuades us to hold a high score is the content of the surviving roles rather than their count. When firms describe the first-year job as directing and checking AI output rather than building the model, the apprenticeship has changed even if headcount recovers. A graduate can get the analyst seat and still not get the training the seat used to provide.
We will be watching analyst class sizes through a full deal cycle before concluding either way, and we will say so if we were wrong.
Yes, with the destination clearly in mind.
The safe end of finance — advisory, wealth management, risk, compliance — is protected by things that have not moved: licensing, fiduciary obligation, and clients wanting a human. Those are durable protections in our framework.
The traditional route in is the part under pressure. The two-year analyst program exists to do precisely the work AI now does, and the advisory door was never open to new graduates anyway; it is earned through years and trust.
The degree versions that hold up pair finance with real quantitative depth — the people building the models remain scarcer than the people running them — or point explicitly at licensed advisory paths.
Worth asking any program: what proportion of graduates enter analyst programs versus client-facing or risk roles, and how has that mix shifted in three years? The shift is the market telling you where the jobs went.
This sampler tells you where finance stands. The full profile tells you what to do about it.
Most families are weighing two or three careers seriously, and a few more they haven’t ruled out. Pick the ones you need.
Each includes a short version written directly to the student and the technical scoring appendix. Spring 2027 updates of whatever you buy are included.
Read one complete profile free → We publish computer science in full so you can judge the depth before buying anything.