Why AI Won’t Save Junior Bankers From the Grind (And Why That’s a Good Thing)

Slightly different to my usual posts, but still a topic I find very interesting & relevant...

The Financial Times’ recent coverage of AI start-up Rogo’s $50mn funding round – led by Thrive Capital – has reignited debates about automation in investment banking. If AI can churn out pitch books, LBO models, and due diligence reports in minutes, what’s left for juniors? While optimists hail this as liberation from Excel hell, the reality is more nuanced. I genuinely believe that mastery in finance isn’t just about output; it’s about how you learn – and that requires grit, late nights, and yes, the grind.

The Illusion of Shortcuts

Rogo’s promise to automate “labour-intensive junior tasks” taps into a different narrative: replace drudgery with efficiency. But let’s dissect this. Consider Tiger Global Management, a firm frequently cited for its tech-driven, rapid-fire investment strategy. Even they acknowledge that replicating senior-level judgment – the kind that turned early bets on Meta and Microsoft into 180%+ returns – remains beyond AI’s reach. As Rogo’s founder admitted, approximating the intuition of a Tiger Global partner is still a “far way off.”

This isn’t just about technical skill. Junior tasks, however tedious, forge critical reflexes:

• Pattern recognition: Spotting outliers in a 100-tab Excel model trains you to sniff out risks in live deals.

• Client psychology: Formatting slides at 3am isn’t about aesthetics – it’s learning how senior bankers tweak messaging to placate a CFO or sway a board.

• Resilience: As one Wall Street Journal report highlighted, enduring 110-hour weeks (controversial as they are) builds the stamina needed for high-stakes negotiations.

AI might trim the fat, but it can’t replicate the muscle memory earned through repetition.

The Hidden Curriculum of Banking

When I transitioned into finance, I quickly realised banking’s “hidden curriculum”. Memorising SUMIFS shortcuts mattered less than absorbing the intangibles:

• Narrative instinct: Watching MDs reframe a client’s weak EBITDA as “untapped synergy potential” taught me more than any template.

• Emotional IQ: A 4am pizza party after a brutal week? I have seen how firsthand revealing how teams bond under pressure – a dynamic no algorithm can decode.

• Strategic timing: Knowing when to push a deal vs. when to let silence work its magic isn’t found in a DCF model.

This apprenticeship is ambient. It happens in late-night edits, overheard client calls, and the unspoken rules of hierarchy. AI might spare juniors the all-nighters, but it risks creating a generation of bankers who can’t read a room – or a balance sheet’s subtext.

The Tiger Global Paradox

Let’s address the elephant in the room: efficiency vs. expertise. Tiger Global’s meteoric rise was built on speed – deploying capital faster than rivals into tech disruptors. Yet even they’ve faced reckoning. Their 2022 losses (up to 70% in some funds) exposed the perils of over-reliance on momentum without deep due diligence. Their rebound in 2023-24? Arguably a testament to human adaptability, not just data-driven bets.

The lesson? AI excels at scaling what’s known. But banking thrives on ambiguity – the 2am debate over whether a startup’s “burn rate” is visionary or reckless. These judgments demand battle-tested intuition, not just clean outputs.

MY TAKE: Embrace the Grind

Here’s where I stand:

1. AI as a tool, not a teacher: Use it to automate formatting, not thinking. Let juniors focus on why a revenue multiple comps range from 8x to 12x, not just pulling the numbers.

2. Quality over quantity: Long hours should be purposeful. A 90-hour week spent shadowing a live deal beats 50 hours of mindless slide-tweaking.

3. Own your experiences: As a junior analyst myself, I've learnt how to not just “do the work” – but reverse-engineer it. Why did the MD cut that slide? How did the client react to the valuation cap?

Closing From Me

The FT’s Rogo piece asks, “What happens to juniors?” The answer: we need to adapt. AI won’t replace the grind; it’ll redefine it. Mastery still requires showing up – not just to input data, but to decode the unspoken, to fail, and to forge judgment that no algorithm can mimic.

As for me? I’ll take the late nights. Because in the trenches of a live deal, there’s no substitute for having lived through a hundred dead ones first.

MY PERSPECTIVE: Key Takeaways

• AI’s limits: Efficiency ≠ expertise. Tiger Global’s reliance on human judgment underscores this.

• Grind with purpose: Use AI to eliminate busywork, but protect tasks that build intuition (e.g., model stress-testing, client-facing drafting).

• Cultural shift needed