Your consultants are faster than they were a year ago, but faster consultants do not mean the firm competes differently. The real shift is agentic AI for consulting firms — AI that runs inside the firm’s own systems and controls, not just at an individual’s desk. That shift hasn’t happened yet for most firms, and the economics of how they win the next engagement haven’t changed.
Nearly everyone has AI at their desk — 92% of professionals now use AI at work — yet only 33% of firms have adopted it firmwide. The gap between those numbers is where the firm’s competitive advantage should come from. For most firms, it hasn’t.
That’s not a technology gap; it’s a firm gap. Individual AI use is nearly universal, but firms struggle to embed AI into the systems, controls, and client work that determine who wins the next opportunity. Getting a consultant to work faster is easy. Getting the firm to compete differently is the real challenge.
So the question for consulting leaders this year isn’t whether AI makes your people quicker. It’s whether it changes how the firm competes. For most firms, it hasn’t yet.
Faster individuals, same firm
Individual productivity was the easy win. A consultant can now turn a client interview into a structured summary, pull key findings from hundreds of documents, build a first-pass analysis, or draft a client-ready deliverable all genuinely faster than a year ago.
But none of that wins the deal. What wins is drawing on everything the firm has ever done in that sector so practitioners arrive already understanding the client. That intelligence lives in engagement history, in client relationships built over years, in the practice patterns that tell a partner which approach worked in a comparable case. Today it gets stitched together by hand, pulled from people’s memory and disconnected systems in the days before a pitch.
The consultant is quicker while the firm is still assembling its own institutional knowledge by hand, one pitch at a time.
Why the gap exists
Firms that stall between pilot and scale usually didn’t move too fast — but rather they built on the wrong foundation and discovered it too late. In McKinsey’s 2026 AI Trust Maturity Survey, only about a third of organizations had reached a mature level in strategy, governance, and agentic AI oversight — even as their technical AI capabilities advanced. Nearly two-thirds named security and risk concerns, not model limitations, as the main thing keeping them from scaling agents. The models are ready. The firm’s ability to govern them isn’t.
Imagine there are two barriers.
The first is organizational: workflows haven’t been clearly defined, so no one knows when an AI agent should hand work back to a person, or who is accountable when something goes wrong.
The second is structural: the firm lacks the audit trails, permissions, and controls needed to govern what the agent can see and do, as it does today with conflicts clearance and information barriers.
These two items are connected. Scale too quickly, and you may automate a process that nobody owns. Add too many controls, and the pilot never leaves sandbox. The pilots that stall are often those that failed to address one, or both, of these potential success barriers.
The consulting-specific stakes
For consulting firms, this gap is expensive in specific ways.
Speed of insight decides who wins the project. When two firms pitch the same client, the one that can already draw on everything the firm has done in that sector arrives with a point of view while the other is still assembling one. Individual speed doesn’t get you there; connected intelligence does.
And that advantage compounds with every senior departure, because institutional knowledge walks out the door with the people who hold it. The judgment they carried — which clients, which approaches, which mistakes not to repeat — leaves with them, unless the firm has captured it somewhere its people can actually use.
What closing the gap looks like
Closing the gap doesn’t mean buying more AI. It means putting AI where the firm’s work and its controls already live — so both of those barriers come down at once. That’s what Firm AI, powered by Intapp Celeste, is built to do.
The starting point is wherever the firm already operates.
For firms running on the full Intapp platform, Celeste connects engagement management, client development, risk, time, and reporting as one system. The work already has an owner, the engagement already has a lifecycle, the conflicts process already has a gate. Celeste works inside all of it rather than asking the firm to stand up a parallel process. And because it carries the firm’s own governance, the structural barrier comes down too. Celeste reasons over engagement history and relationships, inside the firm’s conflicts and confidentiality controls, and leaves an audit trail on everything it touches.
For firms running one or two Intapp products, the value is just as real — it’s just more targeted. If your firm uses Intapp Walls, information barriers extend into the AI layer automatically. No new controls to staff, no parallel governance process to build. If it uses Intapp DealCloud, relationship context, deal history, and coverage data become something the firm can call on before a pitch, governed and traceable to its own data, rather than something someone assembles by hand. Similar advantages exist within Intapp Compliance and Intapp Time.
The payoff scales with what the firm has in place today. You don’t need the full stack to start getting value. But as the firm’s footprint grows, so does the intelligence — and the firm takes on more work without adding bodies.
The economics are changing
The question isn’t whether your people are faster — it’s what your firm becomes when the work is delivered on connected, governed intelligence instead of assembled by hand before every pitch.