AI is forcing professional services firms to rethink not only how they deliver value, but how they charge for it. As artificial intelligence accelerates large-scale transformation work, consulting’s traditional billable-hours model is giving way to outcome-based partnerships that tie compensation directly to performance. Leo Cummings, an associate at Hunt Scanlon Ventures, explores how McKinsey’s evolving model reflects the future of advisory work – and the talent implications that come with it.
Consulting is undergoing a fundamental reset. Clients no longer want episodic strategy advice – they want measurable impact tied to their biggest transformation mandates, and they expect their consultants to be accountable for results.
McKinsey’s rapid internal adoption of AI shows just how quickly the industry is evolving. Since the firmwide rollout of Lilli, its enterprise AI tool, in July 2023, 72 percent of McKinsey colleagues have become active users.
Employees report up to 30 percent time savings in knowledge retrieval and synthesis, and the firm now runs more than 500,000 AI prompts each month. This scale has shifted how teams work and what clients expect in return.
Against this backdrop, McKinsey told Business Insider that AI is changing both what it offers clients and how it prices its services.
The firm now generates about a quarter of its global fees from outcomes-based pricing – a notable departure from the billable-hours model that has defined consulting economics for decades.
Outcome Over Effort
According to Business Insider, a McKinsey managing partner explained that clients are increasingly bypassing traditional scoping conversations and instead starting with the outcome they want to achieve. Rather than asking what a project might cost, clients are tying compensation directly to whether McKinsey can deliver those results – reflecting a broader shift toward shared-risk, performance-driven partnerships.
“This is one of the clearest signals that clients are no longer just willing to pay for effort – they want to pay for certainty,” said Leo Cummings, an associate at Hunt Scanlon Ventures. He added that AI compresses analysis time and increases pressure on firms to deliver results rather than research.
BI reported that McKinsey leaders view AI as a major accelerant of this pricing evolution. Multi-year, multidisciplinary transformations – especially those involving AI deployment – naturally align with outcomes-based structures where advisors are rewarded for measurable progress.
AI Redefines the Work Itself
AI is also reshaping the nature of consulting engagements. Strategy work, once McKinsey’s defining offering, now represents less than 20 percent of the firm’s global business.
Clients are instead turning to consulting firms for deep implementation support across data, technology, operations, and workforce transformation.
Business Insider also reported that McKinsey executives emphasized that they now serve as long-term transformation partners rather than traditional advisory vendors. Their work spans the full lifecycle of a project– from data infrastructure and AI enablement to workforce redesign and operational integration.
“Consulting is moving from advice-driven to operations-driven. Organizations need leaders who can implement at scale – not just recommend a path forward.”
“Consulting is moving from advice-driven to operations-driven. Organizations need leaders who can implement at scale – not just recommend a path forward,” said Mr. Cummings.
As AI becomes embedded across industries, clients increasingly want partners who can integrate new systems, redesign processes, and upskill workforces – not just diagnose problems, he said.
A Commercial Model Under Pressure
McKinsey’s pricing shift reflects a broader disruption across professional services. Leaders at EY have expressed similar expectations, predicting that AI may push consulting toward a “service-as-software” model where clients pay for outcomes rather than hours.
This evolution places pressure on the traditional economic model of consulting. If AI tools like McKinsey’s Lilli reduce research and synthesis time by 30 percent, then billable hours become a weaker measure of value. Firms must now demonstrate operational progress – not activity levels – and doing so requires a different leadership profile.
“This is where AI becomes more than a productivity tool – it starts to reshape the entire commercial model of consulting,” said Mr. Cummings.
Firms will need leaders who can tie their work to measurable business outcomes and guide clients through transformations that span technology, operations, and workforce strategy.
Leadership in an AI-Accelerated Advisory World
As consulting firms lean into AI-enabled delivery and performance-linked pricing, the talent they need changes with it. Firms require leaders who can own measurable outcomes, guide clients through operational and workforce redesign, and deploy AI tools internally at the pace the market now expects.
“We’re watching consulting evolve from a knowledge business into a capability business,” said Mr. Cummings. That shift favors partners with deep operational experience, transformation backgrounds, and the ability to convert AI-driven insights into sustained impact.
For executive search and talent leaders, the takeaway is clear: consulting’s next generation of leaders will be defined by their ability to execute, not just advise – and by their fluency in a world where AI is now central to every major transformation mandate.
Article By
Leo Cummings
Leo Cummings is Editor-in-Chief of ExitUp, the investment blog from Hunt Scanlon Ventures designed for professionals across the human capital M&A sector. Leo serves as an Associate for Hunt Scanlon Ventures, providing robust industry research to support the firm’s investment group.
