The Junior Gap: What Happens if AI Replaces the Training Ground?

For decades, junior roles in banking and finance were the de facto apprenticeship for future leaders. Analysts and associates cut their teeth on repetitive tasks—building models, running analysis, drafting presentations—earning their stripes through repetition, technical grounding and exposure to the subtleties of finance. This traditional ladder built technical skills, commercial judgment and resilience, and ensured a pipeline of leaders ready to take on high-stakes decisions later in their careers.

Today, that dynamic is being fundamentally challenged by artificial intelligence.

AI is now rapidly absorbing the very work that once trained the next generation. Tools that can generate financial models, summarise data, and prepare reports—once the bread-and-butter of junior bankers—are becoming default capabilities in many firms. According to recent labour market analysis in financial services:

• Entry-level job postings (0–2 years’ experience) have fallen by 24% globally, largely driven by automation and AI replacing routine tasks once done by junior hires. Meanwhile, demand for senior professionals (10+ years’ experience) is more resilient, rising 6%. (Ranstad)
• In the UK, financial sector job vacancies rose ~12% in 2025, but roles skew toward AI, data and tech skills, while administrative and clerical roles—typical entry points for new graduates—declined significantly. (computing.co.uk)
• Employers are accelerating skills-first hiring, moving away from rigid job titles and privileging capabilities that cannot be easily automated. (Ranstad)

This creates an uncomfortable question for the future: if machines take over the grunt work, how will the next generation of bankers, investors and CFOs be trained?

1. The Risk of Hollowing Out Talent Pipelines

Without the opportunity to “learn by doing,” junior talent risks missing out on the foundations of analytical deep work. Spotting anomalies in models, vetting assumptions, or understanding the nuance behind numbers has historically come from hours of manual practice. If AI accelerates processes too far, future leaders may lack the depth needed to make high-stakes decisions—a core competency for senior roles in investment banking advisory or finance leadership.

The experience gap will widen unless firms provide alternative ways to develop judgment and expertise, because the work juniors used to do is increasingly automated or absorbed into AI-enabled workflows. (newstoday)

2. Rethinking the Path to Expertise

Instead of eliminating training, AI may force firms to redesign it. Traditional repetition—once the crucible for skill development—will give way to structured development pathways, such as:

• Structured rotations across deal teams and client coverage areas where juniors can observe and participate strategically rather than just execute rote tasks.
• Mentorship and coaching programmes paired with senior advisors to translate complex outputs from AI into strategic insights.
• Simulated deal environments and scenario-based learning that model real advisory decisions, not just technical execution.

These approaches shift the skillset from execution to oversight—training juniors to interpret, challenge and contextualise AI outputs rather than simply produce them. This echoes broader labour market trends showing that finance jobs requiring AI fluency command premiums and are reshaping expectations for entry roles. (Siai)

3. What Employers Need to Do

The firms that succeed will be those that plan talent development deliberately:

• Design career paths that retain exposure to fundamentals, even if specific tasks are automated.
• Invest in coaching, mentorship, and critical thinking frameworks that emphasise strategic judgment.
• Build progression pathways independent of manual task volume, focusing instead on decision quality, client engagement and strategic synthesis.

Without this intentionality, firms risk a “junior gap”—a shortage of leaders with the depth of experience required to succeed at senior levels. This exposes organisations to risk, particularly in high-pressure areas like transaction advisory, corporate strategy, or C-suite roles, where judgment based on deep domain experience remains essential.

Conclusion

AI is reshaping how work gets done, but it should not accidentally reshape talent development. If repetitive tasks disappear, firms must be intentional about how juniors gain the skills once learned through them. Efficiency cannot come at the expense of the next generation of finance leaders—especially in a market where senior skills and adaptive judgment will be the true differentiators in leadership pipelines.

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