What EY's Bet on Junior Consultants Reveals About the Future of Work

EY leaders recently noted that “inexperience” is a junior consultant’s biggest advantage in the age of AI. Junior consultants arrive without assumptions, a blank sheet of paper that lets them challenge how work gets done.

EY’s right — but the “inexperience advantage” isn’t about age. It’s about mindset.

Anyone, whether junior or senior, who approaches work from first principles and leans into AI has asymmetric advantage. A 25-year old or a 25-year veteran who genuinely questions the operating model has MORE leverage today with AI.

This is the substrate: AI provides the horsepower. Humans provide the steering. When intelligence becomes abundant, the ability to “aim it” becomes the scarcest resource.

𝟭. 𝗧𝗵𝗲 𝗮𝗹𝗹𝗶𝗮𝗻𝗰𝗲𝘀 𝘁𝗲𝗹𝗹 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹 𝘀𝘁𝗼𝗿𝘆.

This month alone: OpenAI launched Frontier Alliances with BCG, McKinsey, Accenture, and Capgemini. Anthropic deepened its enterprise push with Infosys and Accenture. Every major consulting firm is now aligning with AI labs.

The limiting factor is how AI is used to reinvent the organization.

That’s an operating model conversation. Exactly the thesis I laid out in Beyond Faster Work: agentic AI doesn’t optimize tasks, it makes entire workflows obsolete. The firms that redesign around outcomes rather than bolt agents onto existing processes will open a gap that closes very slowly.

But as firms scale AI integration, a quieter risk emerges inside the enterprise: human learning decay.

𝟮. The cognitive atrophy risk.

Yes, the work will shift from “assembly” to interpreting insights and shaping outcomes. BUT the harder question is: how do juniors actually learn if you strip out the reps that built judgment in the first place?

This is the “Cognitive Atrophy” risk I flagged in my 2026 outlook and in a recent panel discussion on Workplace AI. If juniors offload all the grunt work, they lose the reps that produce good judgment and you get a hollow organization. When juniors skip the reps that build judgment, experience becomes an unreachable layer.

Stop training people with busywork. Start training them with simulation. Let them use AI inside the sandbox. For example, PwC is training its 75,000 U.S. employees in AI skills through its new AI Learning Collective.

𝟯. 𝗧𝗵𝗲 𝗲𝗾𝘂𝗮𝘁𝗶𝗼𝗻 𝗵𝗮𝘀𝗻’𝘁 𝗰𝗵𝗮𝗻𝗴𝗲𝗱, the source of leverage has.

Impact = (Leverage × Wisdom) / Friction.During the industrial age we moved from human muscle to machines for greater leverage. Now, we are moving to human intelligence to machine intelligence for greater leverage.

But leverage without wisdom creates faster mistakes at larger scale. And leverage without low-friction decision architecture creates more work than it eliminates.

This is where the human premium lies.

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Here’s the bottom line.

Entire industries are being restructured in real time. AI labs are choosing their enterprise partners. Firms are choosing their AI platforms. And somewhere in between, a generation of knowledge workers (young and experienced alike) are figuring out where they fit.

The answer won’t come from the technology. It will come from the organizations brave enough to redesign how people grow, decide, and lead alongside intelligence that never stops improving.

Deploy agents where relevant. But invest just as deliberately in the human capacity to direct them. The winning firms won’t just use AI, they will develop people who can aim it

Until next time,

Ram

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Ram Srinivasan

MIT Alum | Author, The Conscious Machine | Global Future of Work and AI Adoption Leader published in Business Insider, Fortune, Harvard Business Review, MIT Executive Viewpoints and more.

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Ram Srinivasan currently serves as an Innovation Strategist and Transformation Leader, authoring groundbreaking works including "The Conscious Machine" and the upcoming "The Exponential Human."

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