Last Updated on July 6, 2026
By Florian Smeritschnig, former McKinsey Senior Consultant. Updated July 2026.
The impact of AI on consulting is the shift from a people-heavy pyramid, where large cohorts of junior analysts do research, modeling, and slides, toward leaner, AI-augmented teams. AI now handles much of that entry-level production work, which raises the bar on judgment, client skills, and AI fluency for anyone trying to get in.
Every week a candidate asks me some version of the same question: is it even worth breaking into consulting if AI is about to gut the job? The honest answer is that AI is not ending the consulting career, but it is rewiring the bottom of it, which is exactly the part you are trying to enter. The research and modeling that used to fill an analyst’s first year is the first thing AI takes off the table, so firms hire fewer generalist juniors and screen harder for judgment and AI fluency.
After five years at McKinsey and 2,200+ case and consulting career coaching sessions since, here is what has actually changed, what is still hype, and how to position yourself for it.
Key Takeaways
- AI is automating the production work of consulting (research, benchmarking, modeling, first-draft decks), not the judgment, client trust, and accountability firms actually sell.
- The clearest effect on careers is a flatter pyramid: fewer generalist entry-level hires, more specialists, and an AI-fluency filter on everyone.
- AI cannot yet do the job end to end. In Mercor’s February 2026 benchmark, top models finished under 25% of real consulting tasks correctly on the first try.
- Consulting is still a strong career, but the path in is more competitive and more skill-specific than it was three years ago.
- What gets you hired has not changed at its core: structured thinking and business judgment. AI just raised the bar on both.
How AI Is Actually Changing Consulting Work
Start with what is real, because most takes on this topic are either breathless or dismissive. Inside McKinsey, BCG, and Bain, AI is already a standard part of the workflow, not a pilot. Firms have built their own tools (McKinsey’s internal assistant, Lilli, is the best-known) to search proprietary knowledge, summarize documents, draft analysis, and speed up slide creation. The work that used to take a junior team two days now takes an afternoon.
That matters for your career because of where the time was spent. Historically, a first-year analyst’s value was partly raw capacity: pulling data, building benchmarks, formatting exhibits, and turning a partner’s outline into 20 slides overnight. That is precisely the production layer AI compresses best.
In my five years at McKinsey and the coaching work since, I have watched this change in real time. The grunt work that used to define year one is thinning out. What replaces it is not “nothing.” It is a higher expectation that a junior directs the AI, checks its output for the errors it confidently produces, and owns the client-ready judgment on top.
The floor moved up. You are now expected to start where the old analyst finished.
What AI Can’t Do (and Why the Job Still Exists)
Here is the part the doom takes miss. AI is strong at pieces of consulting and weak at the thing consulting actually sells: reliable, end-to-end judgment under ambiguity.
The best evidence to date is not opinion, it is a benchmark.
In February 2026, the research firm Mercor released APEX-Agents, a test that drops AI agents into realistic consulting workflows: work through a messy file system, analyze consumption data, compute the right metrics in a spreadsheet, and write a defensible summary.
The underlying paper documents the result. Even the best models (Google’s Gemini 3 Flash and OpenAI’s GPT-5.2) completed fewer than 25% of these tasks correctly on the first try, and the top agent reached only about 40% even with eight attempts.
Mercor’s 2026 benchmark: top models finished under 25% of real consulting tasks on the first try.
Read that number as a candidate.
It says AI can draft and calculate, but it still fails the whole job most of the time, because consulting is an end-to-end process: define the right question, decide where to look, pull signal from fragmented information, and synthesize a recommendation that survives a partner’s challenge.
That is judgment, and judgment is what a case interview screens for. Our breakdown of the Mercor findings goes deeper, but the takeaway is simple: AI changes how the work is executed, not who is accountable for the decision.
The Real Impact on Hiring: A Flatter Pyramid
The structural change is the one that touches your odds directly. The consulting model was a pyramid: a wide base of junior analysts feeding work up to a narrow tier of partners. When AI absorbs the base’s production work, the pyramid starts to look more like a diamond, wider in the middle, narrower at the entry level.
| Traditional pyramid | AI-era consulting | |
|---|---|---|
| Entry-level hiring | Large analyst and associate cohorts | Fewer generalist juniors |
| What juniors do | Research, benchmarking, modeling, slides | Direct and check AI, interpret, own the client-ready story |
| What gets you hired | Structured thinking plus work capacity | Structured thinking plus judgment plus AI fluency |
| Team shape | Big, layered teams | Smaller, senior-heavier, specialist-mixed |
| Fastest-growing roles | Generalist consultants | AI and data specialists, engineers, AI translators |
Firms have already shown they will cut headcount and flatten structure when the economics change. McKinsey trimmed around 2,000 support roles and Accenture roughly 19,000, both reported by Bloomberg and both driven by cost rather than AI. The point is not that AI caused those cuts.
It is that the willingness to shrink the base was there before AI, and AI now gives firms a structural reason to hire fewer juniors and different ones.
For a full view of how the entry-level role itself is being rebuilt, see our guide on how the junior consultant’s work is changing.
From pyramid to diamond: fewer generalist juniors, more specialists, an AI-fluency filter on all.
Will AI Replace Consultants?
Short version: no, not the role, and yes, parts of the work. AI is automating tasks inside consulting, and it is reshaping which tasks a human is paid for. What it is not doing is replacing the consultant as the person who frames the problem, carries the client relationship, and owns the recommendation, and the Mercor data above is the clearest sign that full autonomy is not close.
The more useful question for you is not “will the job vanish” but “which version of the job survives and grows.”
That is the AI-augmented consultant who uses the tools to move faster and spends the saved time on judgment, synthesis, and client trust. We cover the replacement debate and the evidence on both sides in the future of consulting.
Is Consulting Still a Good Career in the AI Era?
Yes, with sharper conditions than three years ago. The economics that make consulting attractive (fast learning, exit options, compensation, brand) are intact, and demand for AI-strategy advice is a genuine tailwind for the firms. What changed is the entry bar and the skill mix.
The honest read: consulting is a better bet if you bring or build genuine analytical and AI skills, and a harder bet if your plan was to get in as a pure generalist and learn everything on the job. The learning curve is steeper because the easy first-year tasks that used to build your foundation are now automated.
You are expected to arrive with more. That is not a reason to skip consulting. It is a reason to prepare more deliberately than the candidate ahead of you.
What AI Means at Each Stage of Your Career
The impact is not the same for everyone, and where you sit changes the move.
Students and first-time applicants. You are entering exactly where AI bites hardest, the entry level. The old cushion of a year spent learning on low-stakes production work is thinning, so firms expect you to arrive with more structure and judgment. Prepare earlier and deeper than the class ahead of you did.
Career-changers and experienced hires. Your edge grows here. Firms increasingly value domain depth, data skills, and the judgment that comes from real work, which is what a strong experienced hire already brings. If you are switching in, lean on that experience rather than competing with new graduates on raw case volume. See our guide to experienced hires at McKinsey, BCG, and Bain.
Current consultants. The people pulling ahead use AI to move faster and reinvest the saved time in client work, synthesis, and judgment. The ones at risk are those whose value was mostly production speed. Make yourself the person who directs the tools, not the one the tools replace.
What AI Means for Your Interviews
The recruiting process is changing alongside the work. Firms are putting AI into the funnel itself, from AI-assisted screens to live problem-solving with an in-house tool. This is its own topic, so this pillar hands you to the interview lane rather than repeating it: start with how AI now sits in the consulting interview, then go firm-specific with the McKinsey AI interview, and read how to prepare cases in the age of AI so your tools sharpen your thinking instead of replacing it.
The through-line: every one of these formats rewards the same thing the work now rewards, which is structure and judgment you own rather than output a tool handed you.
How to Break Into Consulting in the AI Era
The shift is real, but your response to it is concrete. Four moves matter more than the rest.
- Build genuine AI fluency, not buzzwords. You do not need to train models. You do need to use AI the way a consultant does: to accelerate research and drafts, then catch what it gets wrong. Be ready to discuss, with a specific example, where AI helped you and where you had to override it.
- Double down on structure and judgment. This is the skill AI cannot hand you and the one interviews screen for. Learn to define ambiguous problems, prioritize, and defend a recommendation. Our complete guide to case interviews is the place to build it.
- Add a real analytical edge. Basic data literacy (reading data critically, a little SQL or a BI tool) now separates candidates, because firms expect you to interpret AI output, not just present it.
- Position it in your application. Weave AI awareness into your problem-solving story across the whole consulting application process, so you read as someone built for the 2026 job, not the 2019 one.
If you want that judgment trained against realistic cases and honest feedback, the StrategyCase Case Interview Academy and 1-on-1 coaching with a former McKinsey consultant are built for exactly the bar AI has raised.
The Impact of AI on Consulting: FAQs
Will AI take entry-level consulting jobs?
It is reducing them, not erasing them. Firms need fewer juniors for pure research and modeling because AI does that faster. The entry-level roles that remain expect you to direct AI, check it, and add judgment, so the job is smaller in number and higher in bar.
Is consulting a dying career because of AI?
No. Demand for consulting, including AI-strategy work, is healthy, and the evidence shows AI cannot yet do the job end to end. The career is changing shape, not disappearing. The realistic risk is a harder, more competitive entry, not a vanishing profession.
What skills do consulting firms want in the AI era?
Structured problem-solving and business judgment first, then AI fluency and basic data literacy. The classic consulting skill set still decides offers. AI fluency is now the differentiator on top of it, not a replacement for it.
Do I need to learn coding or data science to get into consulting?
For a generalist role, no. You need enough data literacy to interpret and challenge AI output, which is a lower bar than data science. Specialist and AI-focused tracks are different and do reward deeper technical skills.
Which consulting jobs are safest from AI?
The work built on human accountability: framing the problem, aligning stakeholders, carrying client trust, and making judgment calls under ambiguity. Roles heavy on routine research and production are the most exposed.
How is AI changing consulting recruiting?
Two ways. Firms hire fewer generalist juniors and screen harder for judgment and AI fluency, and they are adding AI into the interview process itself, from automated screens to live problem-solving with an in-house tool.
The Bottom Line
The impact of AI on consulting is real, but it is more specific than the headlines. AI is compressing the production work at the base of the pyramid, which means fewer generalist junior hires, a higher skill bar, and a steeper learning curve for the people trying to get in. It is not replacing the consultant, because the judgment and client trust the job is built on are exactly what today’s AI cannot deliver reliably.
For you, that turns into a clear plan: build real structure and judgment, add genuine AI fluency, and position both in your application. The candidates who treat AI as a reason to prepare harder, not a reason to give up, are the ones firms still want. Start with a StrategyCase preparation plan built for the bar AI has raised, and prepare for the 2026 job rather than the one that is disappearing.
About the author: Florian Smeritschnig is a former McKinsey Senior Consultant who spent 5 years at the firm, conducted more than 2,200 candidate interviews through StrategyCase and other platforms, and has coached his candidates to 700+ offers at McKinsey, BCG, Bain, and other top firms. He is the founder of StrategyCase.com and the author of three consulting interview and career books: “The 1%: Conquer Your Consulting Case Interview,” “The 1%: Case Interview Workbook,” and “Consulting Career Secrets.”
