The Big Four accounting and consulting firms—Deloitte, PwC, KPMG, and EY—are confronting a fundamental challenge as agentic AI transforms traditional career development paths. For decades, junior employees built foundational expertise through repetitive tasks like drafting documentation, data input, reconciliations, and quality checks. Now, AI agents can complete these tasks in seconds, fundamentally disrupting how the next generation of professionals develops critical skills.
Yvonne Hinson, CEO of the American Accounting Association, highlighted the central dilemma: “This is the big question right now that I haven’t been able to get anybody to answer for me.” The concern is that employees advancing without understanding the underlying work creates significant risk for both firms and clients. Even Niale Cleobury, KPMG’s AI workforce lead, acknowledged the uncertainty, stating “I probably don’t 100% know the answer to that question” when asked about developing core skills alongside AI agents.
The cognitive risks are substantial. Experts warn that reviewing AI-generated outputs can create an “illusion of understanding” without deep comprehension. There’s also concern about over-reliance and codependency, where professionals lose confidence in their own judgment. This challenge extends beyond the Big Four—at Davos, executives across industries struggled to articulate how education and job preparation should evolve for AI-native workers.
The firms are responding with new training approaches. PwC’s Margaret Burke, US talent acquisition and development leader, emphasized teaching “the ‘why,’ not just the task.” Entry-level hires now complete a “four-day AI immersion course” pairing technical AI skills with corresponding human capabilities. KPMG is shifting learning patterns so juniors “pull apart agents’ outputs” to understand how conclusions are drawn. EY’s Errol Gardner, global vice chair of consulting, argues that foundational skills now include “developing judgment about where and how to use AI.”
Firm leaders suggest this transformation may actually accelerate professional development. AI assistance enables earlier client exposure and faster progression to strategic work. Gardner notes that AI-native graduates arrive with unique strengths, and their ability to challenge established norms makes multigenerational teams more valuable. However, whether this new model can truly replace learning-by-doing remains unanswered—a question that may only be resolved when the first generation of AI-native managers reaches leadership positions.
Key Quotes
This is the big question right now that I haven’t been able to get anybody to answer for me.
Yvonne Hinson, CEO of the American Accounting Association, expressed concern about how professionals will develop deep understanding if they skip traditional grunt work. Her statement underscores that even industry leaders lack clear solutions to this fundamental challenge.
I probably don’t 100% know the answer to that question.
Niale Cleobury, KPMG’s AI workforce lead, candidly admitted uncertainty about how to develop core skills when AI agents handle foundational tasks. This admission from a major firm’s AI leader reveals the unprecedented nature of this workforce transformation.
We believe foundational skills still matter. Even when AI assists with parts of the work, our early-career professionals are learning how the work fits together and how to ask better questions.
Margaret Burke, PwC’s US talent acquisition and development leader, outlined the firm’s philosophy of teaching ’the why, not just the task.’ This approach represents PwC’s attempt to preserve skill development while embracing AI efficiency.
AI actually gives us the opportunity to be more deliberate about development, helping early-career professionals move into higher-value work sooner.
PwC’s Margaret Burke presented an optimistic view that AI acceleration could enhance rather than undermine professional development. This perspective suggests the transformation may create better-trained leaders, though this remains unproven.
Our Take
This article exposes a critical blind spot in the AI transformation narrative: we’re automating work faster than we’re figuring out how to develop expertise in an AI-first world. The Big Four’s struggle is particularly significant because these firms have functioned as de facto business schools, training leaders who eventually populate C-suites across industries.
The honest uncertainty from executives is both refreshing and alarming. When KPMG’s AI workforce lead admits she doesn’t have answers, it signals we’re conducting a massive, uncontrolled experiment with professional development. The cognitive risks—illusion of understanding, over-reliance, lost judgment—could create a generation of leaders who excel at prompting AI but lack the deep expertise to recognize when it’s wrong.
Yet the optimistic view has merit: perhaps deliberate exposure to strategic work will produce better leaders than years of grunt work ever did. The answer likely depends on whether firms can successfully teach critical thinking, judgment, and the ability to interrogate AI outputs—skills that may prove more valuable than task-level proficiency in an AI-augmented future.
Why This Matters
This story reveals a critical inflection point for professional services and knowledge work broadly. The Big Four employ hundreds of thousands globally and have historically served as training grounds for business leaders across industries. Their struggle to adapt career development for the AI era signals challenges that will ripple across sectors.
The skills gap dilemma highlights a fundamental tension in AI adoption: efficiency gains versus expertise development. If junior professionals skip foundational tasks, organizations risk creating leaders who lack deep understanding of the work they oversee—potentially compromising quality, judgment, and risk management. This concern extends beyond accounting to law, finance, consulting, and any field where AI agents automate entry-level work.
The lack of clear answers from industry leaders—both at the Big Four and among Davos executives—suggests we’re in uncharted territory. Educational institutions, employers, and policymakers must urgently rethink how professionals develop expertise in an AI-augmented workplace. The outcome will shape workforce competency, organizational risk, and competitive advantage for decades. As the first AI-native generation enters the workforce, their success or failure will determine whether this transformation strengthens or weakens professional standards across industries.
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Source: https://www.businessinsider.com/big-four-ai-agents-creating-upskilling-challenge-2026-1