legacy consulting – Higher rates, AI-driven productivity, and tougher client demands are pressuring Big Consulting’s pyramid model—and opening space for faster, specialist boutiques.
Big Consulting is facing a multi-front squeeze, and it won’t be solved by adding more AI tools.
The client payoff is changing
That shift is now colliding with generative AI’s ability to deliver drafts, summaries, and analysis at speed.. In practical terms. the early-stage work that used to take teams of junior consultants—research. structuring. creating slide narratives—can be produced in minutes.. The implication is not that consulting disappears.. It’s that parts of the traditional delivery pipeline become less differentiated, and pricing power becomes harder to defend.
The firms that built their brand on research-heavy deliverables are being forced to compete with something much faster and often cheaper.. That pressure is showing up in hiring decisions, staffing plans, and internal cost structures.. Even the narrative around “digital workers” versus real business impact is changing. with buyers and boards increasingly focused on whether projects land outcomes. not whether teams can produce decks.
Why the pyramid model is under pressure
But the model’s logic breaks when the cost of producing “information work” falls.. If AI reduces the time required to draft and synthesize materials. the business case for filling the base of the pyramid weakens.. Misryoum sees this as a structural issue, not a temporary staffing adjustment.. When technology compresses the labor needed for entry-level tasks. firms must redesign both how they staff engagements and how they justify premium pricing.
Restructuring isn’t trivial.. Any move toward fewer entry-level roles raises two immediate challenges.. First, it changes the pipeline that develops future partners, which is a long-term corporate capability, not a short-term expense line.. Second. it increases reliance on more experienced consultants—who are typically more expensive to employ and more difficult to retain unless they can do meaningful. hands-on work.. In other words, eliminating junior layers can create a talent bottleneck unless the delivery model changes at the same time.
A common misreading is to treat AI as the main lever and “technology adoption” as the solution.. Misryoum would argue the tougher lever is the commercial model: what the firm is selling. how work is delivered. and which people are best positioned to do it.. If AI improves output quality but the firm’s value proposition remains anchored in junior-generated artifacts. buyers will notice the gap.
The bigger threat is execution demand
This changes the purchasing logic.. In many industries. early-stage strategy has been pulled in-house because firms can use AI-assisted tools to handle first drafts and internal analysis.. The remaining external need tends to move toward harder problems: execution. complex change management. integration across functions. and specialized industry experience.. Buyers also want speed—shorter timelines from kickoff to visible impact.
The talent model built for decades now has to compete with a different kind of delivery.. Legacy firms often have long “cradle-to-grave” development paths for younger employees, with a culture oriented toward learning inside the firm.. But the new client requirement is often the opposite: specialized experience, demonstrated outcomes, and professionals who can implement decisions quickly.. Misryoum sees the risk as a mismatch between what legacy organizations are built to train and what clients are built to buy.
For firms that do not provide execution opportunities internally, retaining experienced operators becomes harder. If those professionals are used primarily to supervise work that can be generated faster elsewhere, they may leave or push clients toward alternative providers.
What “survivors” may look like in the next decade
One model is the boutique approach that concentrates senior expertise and uses AI to reduce administrative drag.. Another is platform-based consulting networks that assemble specialists on demand. matching project needs with people who have already solved similar problems.. These structures can be more agile in staffing and pricing because they’re not constrained by a large base of permanent junior labor.
This doesn’t mean legacy firms cannot evolve.. It means evolution will be expensive and slow, involving changes in hiring, incentives, career development, and engagement design.. Converting an institution built around a specific staffing logic is more than a reorg—it’s an overhaul of culture and the commercial engine.
Misryoum’s key takeaway is that the debate shouldn’t be framed as “AI will replace consulting.” The real contest is between firms that can translate AI-enabled productivity into client outcomes and those that continue to monetize slower, labor-intensive pipelines.
The client, not the tech, decides the winners
As this perfect storm brews—tightened budgets. shifting demand toward implementation. and the compression of junior-led tasks—Misryoum expects legacy firms to face hard choices.. Some will attempt structural reform and repositioning.. Others may be squeezed until they become niche operators within a changing market.
The opportunity is real, but it belongs to organizations that redesign for speed and measurable value—not just for smarter production.