The Day I Replaced a Junior Banker with AI

How soon will AI start replacing junior finance roles?

I wanted a real answer—so I ran a real test.

I gave ChatGPT o3 a job I’d normally assign to a junior banker: Take a raw dataset with 28,000 rows of timesheet-level data and build the backbone of a sell-side Confidential Information Memorandum (CIM).

No summary tables. No structure. Just raw data.

The Test

The dataset simulated 10 years of financial and operational data for a consulting/accounting firm. I asked ChatGPT o3 to:

• Calculate KPIs an investment banker would include

• Identify trends and inflection points

• Build a narrative to sell the firm

• Suggest buyer types and value levers

This wasn’t "hey AI, summarize this." This was structured financial storytelling and analysis.

The Results

Here’s what it produced in under 10 minutes:

✅ Accurate KPI Analysis

• 29.7% revenue CAGR

• Utilization, realization, bill rates, revenue per FTE—all calculated and consistent

✅ Contextual Insight

• Identified a 2020 revenue dip and correctly linked it to COVID

• Compared performance to peers, noting a 52% rebound in 2021

✅ Strategic Narrative

• Framed the firm as a "high-margin, data-rich, PE-ready platform"

• Proposed a buyer universe and hooks (PE, strategic consolidators, vertical SaaS)

• Suggested a 4-step process to maximize valuation pre-sale

This is work that takes a junior analyst 2–3 days. AI did it in minutes. And it wasn't just fast—it was good.

The storyline was actually pretty similar to the one I came to on my own, when I analyzed the data. But to get there, I had to spend a few hours (yes I'm thankfully more efficient than a junior banker at this stuff), build an entire data model and dashboard in Power BI, and analyze the trends and KPIs from there. Screenshot of that exercise below (and original post here).

Why This Matters

This isn’t theoretical. AI can already do a meaningful share of analytical, finance-oriented work in a fraction of the time.

For firms who rely on junior talent to:

• Analyze large datasets

• Write early drafts of CIMs, pitchbooks, or investor memos

• Build storylines around operational KPIs

...that work is about to look very different.

The question is no longer if AI can replace junior finance work. It’s how soon, and what will differentiate the humans left in the loop.

So what do we do about it?

• How do you train juniors in a world where AI is doing the analytical heavy lifting?

• What new skills matter?

• How do we structure teams when AI can generate draft 1 before the analyst opens Excel?

Appendix: ChatGPT o3’s CIM Draft

Author's note: a few of the KPIs it came back with look different than mine, so I would next need to have it define the exact calculations. It's not perfect, but I only spent 10 minutes on it, with zero iteration, which is still pretty impressive. I would never do that in a client engagement but as a proof of concept it certainly surprised me.

Executive Summary — “From Boutique to Scaled Platform”

Over the past decade the Firm has quietly transformed itself from a 25‑person boutique into a $21.7 million, 95‑headcount professional‑services platform that commands premium pricing and generates sticky, recurring project flow. A disciplined focus on utilization, pricing power and talent leverage has delivered ~30 % revenue CAGR and a 2.7× gain in revenue per FTE, while maintaining billable‑hour productivity and improving realization.

Investment Highlights

1. Compounding Growth Engine 29 % 10‑year CAGR driven entirely by organic expansion in the Accounting Advisory practice. Impressive pricing power (bill rate CAGR 4.6 %) despite incremental mix of junior talent, underpinning margin expansion.

2. Operational Excellence & Scalability Utilization has held in the high‑80s/low‑90s even through rapid hiring cycles, demonstrating strong bench management. Realization >90 % in the last two years signals rigorous scope control and minimal write‑downs.

3. Attractive Unit Economics Revenue per FTE up 2.7× since 2015; every incremental dollar of revenue now requires ~40 % fewer hours than a decade ago. Variable cost model plus offshore experimentation (not yet in baseline) positions EBITDA margins in the high‑20s / low‑30s and rising.

4. Resilient Through Cycles 2020 revenue dip limited to 4 %, outperforming peers that saw double‑digit declines. Rapid snap‑back (+52 % in 2021) validates counter‑cyclical demand for finance transformation.

5. Multiple Avenues for Future Upside Practice Expansion – immediately add FP&A, Technology Enablement, or CFO Services to cross‑sell into an existing 250‑client roster. Geographic Extension – proven playbook can be replicated in under‑penetrated UK & DACH markets. Buy‑and‑Build – bolt‑on specialist boutiques to accelerate to a $100 M+ platform within 4‑5 years.

Suggested Narrative

“The Modern Back‑Office Architect”

Pitch the Firm as the go-to architect of finance operations for the lower-middle-market—delivering audit-ready, investor-grade reporting without Big-4 overhead. Born as an agile accounting advisory shop, it perfected a repeatable delivery engine, layered in tech, and is now ready to scale into CFO services.

Buyers gain:

• Recurring, non-discretionary revenue

• 10 years of timesheet data (transparent delivery engine)

• Proven promotion model (expanding margins)

Pre-Sale Roadmap

1. Lock FY‑2025 forecast with >20% growth

2. Codify delivery playbook

3. Quantify backlog coverage (>75%)

4. Pilot a second practice (e.g., FP&A)

Conclusion:

The Firm presents a rare opportunity to acquire a high-growth, high-margin, data-driven professional services platform still in the early innings of scale. With a decade of validated unit economics and a clear expansion roadmap, buyers can underwrite a credible path to $100M+ revenue and 30%+ EBITDA within five years.