Brains and speed: these are the two things consulting firms have always sold. Today, clients want these companies to deliver the same strategic depth, only compressed from a month‑long engagement into a Monday‑to‑Thursday sprint.
In a market where boutique shops can spin up dashboards overnight and internal corporate strategy teams wield GPT‑powered research tools, the Big names have a new KPI: “time‑to‑strategic decision.” That’s why, while the press fixates on chatbots as social companions and AI art, McKinsey, Bain, Deloitte, and the rest have been quietly rewiring their operating systems with generative AI inside the firewall.
Why Now?
The pandemic has left us all with a huge patience deficit. In 2020, every board learned Zoom. By 2025, they expect that same click‑and‑receive immediacy from their consultants. Waiting three weeks for a 90‑slide “market landscape” now feels like watching buffering dots on 5G.
Besides, many firms are assessing their talent costs vs. tech costs. Partner comp is up, entry‑level analysts push six‑figure packages in major cities, and utilisation targets have nowhere left to climb. Automating first‑pass research with Gen AI shaves hours that used to be billed – or written off. For instance, Deloitte’s leadership calls this pivot an “engineering‑first mindset,” treating every deck as code that can be refactored by AI agents before humans add judgement.
Upstart pressure plays a role, too. Firms like Zest AI or Unique are already wielding LLM copilots, to deliver flash analyses at non-human speed. Accordingly, incumbents can’t simply staff bigger teams; they have to staff smarter ones. That’s where AI platforms enter: ingesting 100 000+ real‑time sources – news wires, patent filings, private‑market data – and pumping out briefing packs in minutes. Each pack references 200+ sources, runs through 2 000 micro‑prompts, and distills the noise via 50+ micro‑agents, letting senior consultants jump straight to hypothesis‑testing instead of Googling in the dark.
What Gen AI Makes Possible for Consultants
And it turns out, Gen AI has quite a lot to offer.
Let’s start with real‑time sector scanning. McKinsey’s proprietary Lilli chatbot, already in the hands of 70% of its workforce, surfaces historic engagement insights, benchmark data, and synthesis “snippets” on command. Need the CAGR for last‑mile pharma delivery in MENA? Lilli drops a sourced paragraph before the coffee machine finishes.
KPMG has deployed Wokelo AI for M&A deals, compressing timelines to deliver high burn commercial due diligence projects. Need company diligence or peer comps, an LLM agent delivers a well formatted PowerPoint deck in minutes capturing differentiated insights that would traditionally take days.
Risk‑signal early warning becomes better and swifter, too. A cross‑source crawl powered by an AI agent can flag that a key supplier just had a labour violation filing in Argentina or that a quiet Series C in climate tech shifts the competitive curve – alerts that trigger same‑day calls with client execs who thought they were just signing off an update.
Gen AI also offers scale. For instance, it helps teams with tailored, innovative thought‑starters. Deloitte’s AI Factory as a Service combines NVIDIA GPUs with Oracle Cloud to spin up fine‑tuned models for niche tasks, like “generate a five‑year lithium demand forecast under three regulatory scenarios,” pushing bespoke analytics to the edge of every project team.
Last but not least, Gen AI delivers slide‑deck acceleration. BCG’s internal tool Deckster generates storyline options and draft graphics, while GENE—its chat interface—rewrites bullets in the firm’s house voice. Consultants can spend the reclaimed hours validating the message instead of kerning the margins.
As a result, hours and hours of work are spared. A Big4 firm logged 3, 500 analyst hours saved in 10 weeks after embedding Wokelo AI into its knowledge‑center workflow. A mid‑market PE shop reported a 6× ROI when AI took the first pass at commercial due diligence memo creation, letting principals focus on deal viability, not data wrangling.
The Quiet Adoption: Why Firms Aren’t Talking About It
Consultancies sell “smart people in a room solving hard problems.” Broadcasting that an AI assistant did the heavy lifting can feel brand‑dilutive. Instead, Gen AI is being slotted into the steps clients rarely see, like research sprints where junior teams now start with AI‑generated “source books” instead of blank spreadsheets, or hypothesis vetting where mid‑level managers throw hypotheses at chat‑agents that sanity‑check against internal IP and public data.
Externally, the marketing stays human‑centric: notice how Bain’s expanded OpenAI alliance headlines “accelerate delivery of AI solutions,” not “replace consultants with bots.” The message: AI just types faster, while consultants still think and are essential for elevating narrative, contextualizing the findings, and visual polish.
What to Expect in the Long Run?
If AI can chew through tables, firms might need fewer bodies per project. However, they’ll need deeper expertise to interpret results. Expect analyst cohorts to shrink while specialist hire budgets rise. Besides, tech fluency becomes table stakes for teams. Deloitte’s push for consultants to “think like engineers” isn’t a mere marketing spin: those who can’t prompt, interpret model output, or spot hallucinations risk obsolescence.
When a due diligence timeline drops from 15 days to 48 hours, hourly billing starts to look awkward. That’s why value‑based pricing gets more and more real for the industry. Watch for more “insight‑subscription” or outcome‑linked fee models.
Proprietary data moats are expected to deepen. Lilli, Deckster, and Wokelo all rely on gated knowledge graphs and fine tuned Large Language Models. The firm with the richest corpus wins because everyone is feeding off the same open‑web content. At the same time, the regulatory scrutiny looms. In terms of data access, we are to expect more discussion as to what data is and is not made available. As AI begins suggesting strategic moves, further liability questions arise. Expect new disclosure norms around AI‑generated analysis sources – and maybe even an “AI audit trail” appended to deliverables.
Generative AI won’t replace consultants; it will replace consulting done the 1995 way. Think of it as the next Excel moment: in 1987, spreadsheets didn’t fire accountants; they made them indispensable to bigger questions. Likewise, platforms like Lilli and AI Factory are becoming the unglamorous but essential backbone that lets consultants spend more cycles on judgement, creativity, and board‑level storytelling. In a knowledge‑saturated economy, that’s the only sustainable edge.
