Will AI Kill or Supercharge Investment Banking Analyst & Associate Jobs?

This newsletter breaks down exactly which tasks will change, what skills you now need, and how to build them over the next 90 days.​

Fear vs reality: “Is my job disappearing?”

Picture this: you walk in on Monday and the new AI tool has already scraped filings, pulled comps, and produced a first‑draft model and deck skeleton before lunch. Where does that leave the junior on the deal?​

Analyst and Associate roles are not vanishing, but the headcount needed for the same volume of work is falling as banks roll out AI for research, modelling, and documentation. The value is shifting away from “I can grind longer than anyone” toward “I can frame the problem, direct the tools, and make better decisions, faster.”​

What AI is Actually Doing to Your Workflow

AI in banking is moving from experiment to infrastructure. Embedded in research platforms, modelling tools, and presentation software. For juniors, this is already reshaping the day‑to‑day in three big ways.​

• Due diligence: AI systems can review thousands of pages of filings, contracts, and transcripts to flag red flags and themes in hours, rather than the days of manual page‑turning that many analysts are used to.

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• Pitchbooks: Generative tools can draft market slides, industry overviews, and initial comps tables, cutting pitch production time sharply and turning the junior’s job into review, refinement, and tailoring.

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• Modelling: AI‑enabled platforms can auto‑build standard three‑statement models and DCFs from linked data feeds, leaving humans to stress‑test scenarios, validate assumptions, and adjust to deal quirks.​

The core shift is this: less time on blank‑page creation and formatting, more time on judgment, narrative, and coordination, if you are willing to step into that space.​

Tasks That Shrink, Tasks That Grow

To make this real, map it to your calendar. Some parts of your job are about to consume far less of your time; others will become disproportionately important.​

Tasks likely to shrink dramatically (time spent down 50–80%):

• First‑pass company screening and basic market maps, as AI can scan databases and open sources much faster than manual searches.

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• Data extraction from 10‑Ks, investor decks, and industry reports, which AI can now summarise and structure automatically.

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• Formatting pitchbooks and building standard charts, which design and slide tools increasingly automate.​

Tasks that change nature (from doing to supervising):

• Financial models move from cell‑by‑cell construction to a “review and challenge” role, where you focus on edge cases, scenario design, and error‑spotting in AI‑generated outputs.

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• Diligence packs shift from manually assembling every data point to validating what the AI found, filling gaps, and highlighting true deal breakers.​

Tasks that grow in importance (where humans win):

• Synthesising the “so what”: turning all the analysis into a clear, persuasive deal story for clients and internal committees.

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• Real‑time problem‑solving when deals deviate from the template: regulatory twists, political risk, founder dynamics, or surprise bidders.

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• Coordinating people: managing timelines, expectations, and information flow across internal teams, and client stakeholders as leaner deal teams run more processes.​

If 80% of your value today is long hours in Excel and PowerPoint, you are exposed. If your value is increasingly in how you think, challenge, and coordinate, AI becomes a force multiplier, not a threat.​

The New Analyst & Associate Skill Stack

AI doesn’t remove the need for technical skills; it raises the bar on how you use them. Think of your development in three shifts.​

1. From Tool User to AI Supervisor

• Prompting: You need to know how to specify context, constraints, and desired outputs so AI helps you, rather than generating noise.

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• Quality Control: You must be able to detect hallucinated numbers, misclassifications, and missing information instead of blindly trusting the output.​

2. From Spreadsheet Operator to Strategic Thinker

• Deal Logic: You should be able to explain, in plain language, what creates value in the deal, what the key drivers are, and where the risks lie.

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• Assumption Challenge: Instead of just accepting model structure, you test sensitivities, question benchmarks, and understand how changes propagate through the case.​

3. From Back-Row Junior to Visible Operator

• Ownership: As teams get leaner, you will be expected to run parts of workstreams, summarise meetings, and take the first shot at recommending next steps.

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• Relationship Micro‑Skills: Reliability, clarity of communication, and internal reputation become more important when there are fewer juniors and more visibility on each person’s contribution.​

In a world of AI‑enabled tools, the analyst or associate who only “presses buttons” is easy to replace; the one who can orchestrate work, interrogate outputs, and frame decisions becomes indispensable.​

A 90-Day Plan to Become “AI-Proof and AI-Powered”

To turn all this from theory into a career advantage, treat the next 90 days as a deliberate upgrade cycle.​

Days 1–30: Make AI Your Daily Co‑Pilot

• Pick one recurring task each week. For example, drafting sector overviews, summarising 10‑Ks, or building initial comps and run it through AI first, then refine manually.

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• Start building a personal “prompt library” for common analyst workflows (comps, peer screens, market maps, bullet‑point summaries), so you get consistent, replicable outputs.

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• After each use, note where AI helped and where it failed; this is the raw material of your supervision skill.​

Days 31–60: Shift From Execution to Judgment

• For every AI‑assisted output, force yourself to answer three questions: “What would I challenge?”, “What’s missing?”, and “What would a sceptical MD ask?”

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• Volunteer to summarise meetings and propose next steps in email or decks; this is how you practise turning analysis into recommendations.

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• Take one model or deck per week and write a one‑page “deal logic memo” explaining the story in plain language; this builds the exact skill machines can’t replace.​

Days 61–90: Make The Shift Visible

• Share specific productivity wins with your VP or staffer, such as “This went 40% faster using AI for the first draft; here’s how I used the extra time to deepen the analysis.”

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• Ask for one new responsibility that reflects your upgraded capabilities. For example, owning a workstream, leading a section of a client call, or drafting first‑cut client emails.

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• Capture 2–3 concrete stories where you used AI to improve quality or speed, and be ready to reference these in mid‑year and year‑end reviews.​

In a world of fewer juniors, the real question isn’t “Will there still be analysts and associates?” It’s “Will you look like the person this team simply cannot function without?”​

Final Thoughts: Your Move

AI is killing the old Analyst and Associate job, the one defined by manual grunt work and late‑night formatting. But it is supercharging the careers of juniors who lean into supervision, judgment, and leadership. The gap between those two profiles is exactly where your next promotion will be decided.​

If you’re already using AI on live deals, reply and share one concrete example of how it has changed your workflow, the IB Leaders Club may feature anonymised stories in a future issue to help the community learn faster. And if you want more content like this on AI‑ready careers and the VP‑to‑MD leap, make sure you’re subscribed and share this issue with the one colleague who most needs to read it.

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