Why this is a threat if you do nothing
The classic entry-level value proposition (a smart graduate who can gather data, build a model, and turn it into clean slides faster than anyone else) is exactly the profile AI compresses best. That work is structured, high-volume, and document-heavy. If your entire pitch to a firm is that you are diligent and produce good output, you are competing directly with a tool the firm already owns.
This is not hypothetical. It is already happening to the market research and knowledge units inside MBBs. Their contribution was typically narrower than what a good junior consultant brings: largely retrieving and packaging information, with less problem-solving on top. That is precisely the task AI now does in a fraction of the time, which is why those functions are the first to feel the squeeze. The lesson for an aspiring consultant is direct: if your value is finding and organising information, the machine already does it faster.
The second-order effect is subtler. As firms shrink the number of juniors per case, each one is expected to operate closer to a manager: less producing slides from a brief, more directing the work and judging whether the output is right. The bar for what a first-year is expected to contribute is going up, not down. That is the real threat, and it is also, once you see it, the opportunity.
Why it is an opportunity for those who adapt
- The premium on judgment rises. When the mechanical work is cheap, the scarce thing is knowing which analysis to run, spotting when a number is wrong, and framing what it means for the client. AI produces an answer instantly; it cannot tell you whether it is the right answer to the right question. That discernment was always what separated good consultants from fast ones. Now it separates them earlier.
- The learning curve compresses in your favour. The tasks that used to consume a junior's first two years (formatting, first-pass research, assembling the base case) are the tasks AI absorbs. Handled well, that frees you to spend your early years on the parts that actually build a consultant: client exposure, structuring problems, forming a point of view. You can become genuinely useful faster than the generation before you, if you use the freed time deliberately rather than coasting on it.
- Fluency is now a differentiator, not a nice-to-have. Firms increasingly expect new joiners to manage AI workflows rather than work around them. The junior who can get a genuinely useful first draft out of these tools, and knows where they break, is more valuable than one who ignores them or trusts them blindly. Two years ago this was optional. It is quickly becoming table stakes, which means demonstrating it early sets you apart from a field that mostly still treats it as an afterthought.
What you can actually do about it
Know which AI skills actually matter. You do not need to code or become a data scientist; firms are not hiring juniors to build models. What matters is practical fluency with the everyday tools: getting a useful first draft of an analysis, a structure, or a research summary out of them, and knowing where they are wrong. That means being able to prompt well, sense-check what comes back against your own logic, and catch the confident errors these tools produce. The relevant skill is judgment applied to AI output, not engineering behind it. You can build it now, on your own prep, before you ever join.
Talk about AI the way a consultant would. In an interview, how you frame AI says more about you than any tool you have used. Do not oversell it as a magic solution, and do not dismiss it. Treat it as a lever with clear uses and clear limits, exactly as you would talk about any resource on a team. Have one real example ready of using it well on something you actually did, and be able to say plainly where you would not trust it. Almost nobody at your level talks about it this way, which is why it lands.
Once you are in, treat AI as leverage on the human work, not a substitute for learning it. Let it take the mechanical first pass, then spend the time you save on the parts that compound: understanding the client's business, building relationships with the people who staff the good cases, forming a genuine point of view. AI gives every junior the same free hours. What separates them is whether those hours go into coasting or into learning the parts of the job that actually count.
Do not compete where you will lose. Never position yourself, in an interview or on a case, as someone whose value is producing output quickly and accurately. That is the one contest you cannot win against a tool the firm already owns. Position yourself as someone who decides what is worth producing and whether it is right. That framing is available to you now, years earlier than it used to be, and it is the whole game.
A word on the fear itself
Consulting has been here before. When the spreadsheet arrived, a large part of the junior job was manual. The tool wiped that work out almost overnight. It did not shrink the profession. It moved the value up, toward deciding which analysis mattered and what the numbers meant, and it raised the bar for everyone who stayed. AI is the same shift on a wider front. Every real shift in this industry has looked, from the outside, like the end of the opportunity, and turned out to be a reshuffling of who wins inside it. The candidates who thrive through this one will not be the ones who out-produce the machine. They will be the ones who let it do what it is good at and concentrate on the judgment it cannot replicate.
