How Consultants Actually Use AI in 2026 (Lilli, GENE, and Sage)
McKinsey's Lilli runs 500, 000 prompts a month. BCG's GENE and Bain's Sage automate research and slide-building. Here's what AI has, and hasn't, changed about the consulting job.
In 2026, McKinsey's internal AI assistant, Lilli, runs more than 500, 000 prompts a month. Consultants using it report up to 30% time savings on knowledge work. BCG tells investors it expects roughly 40% of its revenue to come from AI-enabled work this year. Bain says AI- and tech-enabled work is already about 30% of its consulting business, and leadership projects 50%.
If you're preparing to enter consulting, or trying to understand whether the job is worth entering, these numbers matter more than any salary table. They describe a profession mid-transformation.
Here's what's actually happening inside the firms.
The three assistants every consultant now uses
Each of the MBB firms has built its own internal AI layer. They are not ChatGPT with a logo. They are systems trained on decades of proprietary engagement data.
McKinsey's Lilli is a retrieval-augmented generation (RAG) system. It searches and summarizes the firm's internal knowledge, past decks, expert profiles, research, and answers in seconds what used to take a junior analyst a day of digging through the knowledge management system. Lilli launched to 7, 000 employees in 2023 and is now firm-wide.
BCG's GENE is built on GPT-4o and customized to BCG's knowledge. Consultants use it to analyze interview transcripts, synthesize data, and draft. BCG also built Deckster, a slide-generation tool, and equips consultants to spin up their own GPT agents for specific use cases.
Bain's Sage, originally built on GPT-4o, sits inside Bain's three-year-plus partnership with OpenAI. Bain consultants have built more than 19, 000 custom GPTs for tasks ranging from competitive teardowns to financial modeling.
The pattern is identical across all three: take a foundation model, feed it proprietary firm knowledge, and embed it in the daily workflow.
What the analyst job used to be, and what it's becoming
The traditional first-year consultant job was, in large part, two activities: research and slide-building. Find the data. Structure it into a story. Build the deck. Repeat under deadline.
One analysis estimated that by 2025, tools like Lilli and Deckster could already perform roughly 80% of a junior analyst's typical research and slide-generation work. A BCG study of around 750 participants found 30–40% efficiency gains for junior staff and 20–30% for experienced staff using generative AI.
That doesn't eliminate the analyst. It changes what the analyst is for.
The work moving up the value chain is judgment: deciding which question to ask, recognizing when the AI's answer is plausible-but-wrong, contextualizing a generic recommendation for a specific client's politics and constraints, and owning the conversation in the room. The work moving down, to the AI, is the mechanical execution.
This is why firms increasingly describe the entry-level role as "directing and verifying AI output" rather than producing it from scratch.
What this means if you're interviewing
Three concrete implications for anyone recruiting in 2026:
1. The case interview is testing judgment harder than ever. As AI absorbs the structuring-and-calculating layer, the human premium shifts to the things AI can't do well: reading a client, making a defensible decision under ambiguity, and prioritizing. Your case structure still matters, but the firms are increasingly probing the so what.
2. AI fluency is now a baseline, not a differentiator. Nearly one in four employers say AI proficiency is now a basic expectation for MBA-level roles. Knowing how to use these tools won't win you an offer, but not knowing will lose you one.
3. The ability to challenge AI is the new skill. McKinsey's new AI-powered interview round, rolled out for US candidates, reportedly focuses on whether you can take AI-generated output, question it, spot its blind spots, and adapt it, not whether you can write a clever prompt. (We break that round down in detail in our McKinsey AI interview guide.)
Practice this framework
Work through the Microsoft 2014: Satya Nadella's Turnaround case with AI coaching.
The skill that compounds
The consultants thriving in this transition aren't the ones who memorized more frameworks. They're the ones who developed strong business judgment, the instinct for which numbers matter, which assumptions are load-bearing, and when an answer is too clean to be true.
That instinct is exactly what AI can't yet replicate, and it's what separates a consultant who directs the tools from one who is replaced by them.
You build it the same way consultants always have: by reasoning through real business decisions until the patterns become intuition. That's what working through case studies and live decision scenarios trains. The tools change; the underlying judgment is the moat.
BoardroomIQ helps business students and professionals build the strategic judgment that AI can't replace. Explore our case library and interview-prep tools at boardroomiq-ai.com.
Frequently asked questions
Will AI replace entry-level consultants?
Not wholesale, but it is compressing the work. AI tools now handle a large share of the research and slide-building that defined the first-year analyst role. Firms are hiring fewer juniors for pure execution and more for judgment, client interaction, and the ability to direct and verify AI output.
What AI tools do McKinsey, BCG, and Bain use?
McKinsey built Lilli, a retrieval-augmented assistant trained on the firm's internal knowledge base. BCG built GENE (on GPT-4o) plus a slide tool called Deckster. Bain built Sage and, through its OpenAI partnership, supports more than 19, 000 custom GPTs built by its consultants.
Should I learn prompt engineering before a consulting interview?
Learn to use AI tools well, but don't over-index on prompt engineering as a party trick. Firms care more about whether you can challenge an AI's output, spot where it's wrong, and adapt it to a specific client context, that's judgment, and it's what interviews now probe.