AI and your next move · 7 min read
Will AI replace financial analysts? Where the judgement stays
AI can build models and summarise filings fast. Judgement about assumptions and responsibility for the call still sit with people. A task audit for analysts.
The short answer
AI is automating parts of financial analysis such as gathering data, summarising filings, drafting models and producing standard commentary. It is not removing the need for analysts who can question assumptions, understand a business deeply, explain risk to decision-makers and take responsibility for a recommendation. Analysts who use AI to cover more ground while strengthening judgement and communication are well placed.
On this page 8 sections
What changes first
| Task | Hours a week | AI can draft it? | Who checks and decides? | Keep, shrink or grow |
|---|---|---|---|---|
| Pulling actuals into the monthly pack | 6 | Largely | Me, reconciliation | Shrink |
| Writing variance commentary | 4 | Drafts | Me and finance lead | Shrink, add insight |
| Challenging budget assumptions with managers | 3 | No | Me | Grow |
| Scenario modelling | 4 | Builds drafts | Me | Keep |
| Presenting to leadership | 2 | Drafts slides | Me | Grow |
Assumptions are where the value is
A model is only as good as its assumptions. AI tools can build a three-statement model in minutes, but they will happily use a growth rate nobody would defend. The analyst's job increasingly becomes interrogating assumptions: where did this number come from, what would make it wrong, and what happens to the decision if it is.
A practice exercise
Take a public company's latest annual report. Ask an AI tool for a summary of the main risks. Then read the risk section yourself and list what the summary missed or overstated. Write three questions you would ask management. This exercise builds the habit that keeps analysts valuable.
Directions to explore
- Business partnering: working closely with operational managers on decisions.
- Risk and controls: understanding what can go wrong, including with AI-generated numbers.
- Strategy and corporate development: judgement-heavy, deal-focused work.
- Fintech product roles: designing the tools that change finance work.
Assumption questions worth practising
- Where did this growth rate come from, and what would it be in a bad year?
- Which three inputs change the answer most? Show me the sensitivity.
- What does the model assume about pricing, and does sales agree?
- What would have to be true for this forecast to be wrong by 20 percent?
- Which numbers were estimated by a tool, and which were checked against source documents?
Analysts who habitually ask these questions add value whether a model was built by a colleague, a template or an AI tool.
A worked example of checking an AI-built model (illustrative)
Illustrative example: an AI tool builds a quick revenue forecast for a subscription business, assuming customer numbers grow 5 percent a month and nobody cancels. The analyst checks the company's actual cancellation rate, finds it is meaningful, and rebuilds the forecast with growth and churn separated. The forecast falls noticeably, and the conversation with leadership shifts from “how fast can we grow?” to “why are customers leaving?”. That shift is the analyst's contribution.
Protect confidential information
Financial data is often confidential or market-sensitive. Use only tools your organisation has approved, and do not paste non-public figures into consumer AI services.
Questions people ask
- What parts of financial analysis can AI do?
- Data collection, summarising reports and earnings calls, drafting spreadsheet models and formulas, generating standard commentary and screening large numbers of companies. All of it needs checking.
- Is finance still a good career with AI?
- Finance roles continue to exist, but their content is changing. Skills in judgement, sector knowledge, client communication and risk are becoming more central.
- Should financial analysts learn to code?
- Basic data skills, such as SQL or Python for analysis, are increasingly useful. They help you build and check workflows, including AI-assisted ones.
- What can financial analysts move into?
- FP&A, corporate development, strategy, risk, investor relations, product roles in fintech, and operations finance all use analyst skills.
Exercises are practice, not evidence of career fit or a qualification. How to read our guides and report a correction.
Sources
- Generative AI and Jobs: A 2025 Update · International Labour Organization
- Future of Jobs Report 2025: digest · World Economic Forum
- Financial Analysts (Occupational Outlook Handbook) · U.S. Bureau of Labor Statistics
How this page is written
Sources support the factual background, not a guarantee that an exercise predicts career fit. Fictional practice material is labelled. Dates record content updates; no independent expert review is implied. More about OffLadder.