How to lose a job in 10 days?

Monday, 9 a.m., the coffee on your desk cools. The company newsletter sits in your mailbox announcing the acquisition of an AI firm and its integration into internal processes. You skim it, unbothered. You are from a top European business school, and your value, you assume, lies in strategic thinking, not in learning software.

For decades, juniors learned by doing the work AI can now complete in seconds. If that work disappears, will juniors be replaced by AI and, if so, who will be the seniors tomorrow? Over the next ten days, you will see that the real risk is not unemployed juniors but the seniors who will never exist.

Week One: A consultant’s countdown to imminent unemployment.

Leadership mandates AI training. You politely decline. For you, AI is a passing trend. You miss that it is not a temporary fix but a long-term integration. Senior consultant Jean-Philippe Guihaumé ^[1] puts it, “Now you push a button, and you get everything."

By Tuesday, most of your colleagues have adapted, and you are left with obsolete tasks. When your manager asks you to speed up, you try the tools and are surprised by how easy they make your work. You paste the output into your presentation and send it. When the client asks how you reached your conclusion, you refer vaguely to “the analysis."

This is your first nail in the coffin. On Wednesday, the client notices that your polished models rest on outdated data and ignore current requirements. You cannot defend them because you never did the actual reasoning. The AI did. As Jean-Philippe explains, “Use AI, but don’t hide behind it, and don’t pretend you didn’t use it either." You can delegate work to AI, but not accountability. His advice is simple: “Check, double-check, re-check."

Thursday, however, feels like a success: you have saved hours on research and sent every deliverable. You expect a promotion next year, but leadership is not convinced. AI cannot shorten any stage of professional development; you must build your own experience and face the consequences of your recommendations. In your hurry, you completely skipped building relationships with clients. Jean-Philippe stresses that client relationships and judgement skills “take time to acquire." They come from observing experienced colleagues, making strategic decisions with incomplete information, and learning from mistakes. 

AI can help you generate an answer; your judgement earns you the right to give it. By Friday, you are still miraculously employed, even after you have made every possible mistake. But the job you were hired to do is already gone. Yet looking around the office, you realize you are not the only one. Your firm is making a mistake of its own.

Week Two: A firm’s countdown to its last senior.

Monday morning, you are staffed on a new project: your job is to check what the AI has produced. You “check, double-check, re-check," but as Jean-Philippe warns, “You will just be asked to produce more," so nobody has time to explain why a recommendation holds. Morgan Herry ^[2] and Victor Lesur ^[3] from Sopra Steria Next argue that the senior’s new role is to help juniors challenge the machine.

On Tuesday, you understand. Clients refuse to pay for days of analysis that AI completes in minutes, and when everyone delivers faster, speed stops being a selling point. So, consultancies are moving to fixed fees and outcome-based pricing. McKinsey reports that around a quarter of its fees are now tied to results (Thompson, 2025). When every junior hour was billable, every junior was worth training. Now training is an hour nobody bills, so nobody funds it.

On Wednesday, the hiring figures come out: fewer graduates. Jean-Philippe notes that firms are recruiting fewer graduates “because of the economic environment," not only because of AI. Either way, the result is the same: fewer seats at the bottom of the pyramid.

On Thursday afternoon, a partner suggests the obvious fix by hiring experienced consultants directly. But they too need training on internal AI tools, and “More than 4 in 10 companies say they can’t find talent with the AI skills they need” (Payscale, 2026). If every firm buys seniors instead of making them, the shortage simply moves to someone else. Jean-Philippe, a former partner himself, sees the flaw: “If you want to get people to your senior level, where do you find them? If you don’t develop them (...), where do they come from?” A firm that stops training juniors is not saving money; it is endangering its own future.

By Friday, the pattern is clear: every cohort that is trained less shrinks the pool significantly from which the seniors of 2035 will be drawn, and leadership asks whether the pyramid ^[4] can survive. Jean-Philippe points to the firm he built: "It wasn’t a pyramid; it was a cylinder," with no grades and juniors learning hands-on in front of clients. A cylinder ^[5] works for a handful of consultants, not for ten thousand. The pyramid economics rest on many juniors for each partner; a cylinder cannot carry that leverage.

Monday, again.

For decades, the pyramid trained juniors through volume, with hours of research and hundreds of slides, and judgement absorbed by repetition. AI is taking this volume away, but not exposure through client meetings, proposals, and recommendations that you must defend in person. So, the choice is neither a pyramid nor a cylinder. Keep the pyramid’s scale and add the cylinder’s exposure: an exposed pyramid. The seniors of 2035 are made, or lost, starting this Monday.

Some will say AI can tutor juniors. It can explain an answer, but it cannot make you defend it. Hence, firms should put every junior in client meetings from their first project and turn “checking the AI” into a supervised task with a senior explaining why the recommendation holds.

Juniors should disclose every use of AI and ask a senior, “Why does this hold?” They should ask to join client calls and defend one recommendation per project.

You arrived at an unfortunate point in your career not only through your own mistakes but also through your firm’s inability to adapt to the change, because, at the end of the day, it takes two to lose a job and two to make a senior consultant. 

Notes

[1] Jean-Philippe Guihaumé (interviewed for the article) is a senior strategy consultant with more than 35 years of experience, specializing in leadership development and coaching. He climbed the traditional ladder from EY and Capgemini to Senior Partner at Sopra Consulting (now Sopra Steria Next), then founded his own boutiques, and now teaches at CentraleSupélec, Emlyon Business School, and Audencia.
[2] Morgan Herry is a manager at Sopra Steria Next in Nantes. A graduate of Audencia's Master in Consulting, he spent seven years at CGI Business Consulting in Paris and Montréal, rising from consultant to senior consultant, before joining KPMG and then Sopra Steria Next in 2025.
[3] Victor Lesur is a Data & AI consultant at Sopra Steria Next in Nantes, where he currently acts as Product Owner on generative AI products. An engineer by training, he graduated from INSA Rouen Normandie in mathematical engineering, specializing in artificial intelligence and decision support.
[4] The consulting pyramid is the characteristic workforce structure of a consulting firm: broad at the base, with many junior consultants, and progressively narrower toward the top, with fewer people at each successive senior level. (https://www.venconresearch.com/knowledge/consulting-pyramid)
[5] In our interview with Jean-Philippe Guihaumé, we discovered the cylinder structure of a consulting firm with a flat hierarchy, where juniors get hands-on experience very early on and have more freedom.

• Guihaumé, J.-P. (2026) Interview with BANIK Rishita, TIAKPA Dahi Romellie, BAKALIAN Carla, 24 September, Audencia Business School.
• Herry, M. and Lesur, V. (2026) Conference for the MSc Business Strategy and Consulting of Audencia, 23 September, Audencia Business School.
• Payscale (2026) ‘The AI Skills Vortex is Remaking Work and Fragmenting Pay - and HR Isn't Ready’ [Press release], 24 September. Available at: https://www.payscale.com/pressreleases/2026-ai-workforce-impact-preview
• Thompson, P. (2025) ‘AI is reshaping how McKinsey makes money’, Business Insider, 17 November. Available at: https://www.businessinsider.com/ai-reshapes-how-mckinsey-makes-money-consultancy-025-11

Article written by BAKALIAN Carla, BANIK Rishita, TIAKPA Dahi Romellie