Almost every consulting firm is experimenting with AI right now. The problem is, most of them are approaching it the wrong way.

Standalone copilots, isolated pilots, AI tools bolted onto existing processes without changing how work actually gets done that’s the most common scenario. It looks impressive at first, adoption climbs for a few weeks, and then the momentum fades just as fast as it appeared.

Not because the AI isn’t powerful. Because it’s sitting adjacent to the work instead of inside it. The firms that see real impact don’t just add AI to their tool stack they embed it into the flow of work: into how decisions get made, projects get managed, and revenue gets delivered.

That raises a question more and more leaders in professional services are asking: what actually changes when AI stops being a separate tool and starts becoming part of the firm’s operational rhythm?

Pressure Is Coming From Every Direction

Consulting has always been a margin-sensitive business, but the pressure firms face today feels different. Rates are being squeezed, fixed-fee work is becoming the norm, and maintaining consistent utilization in hybrid environments is harder than ever. On top of that, AI-native competitors are entering the market with leaner delivery models and lower overhead.

Clients are changing too. They expect faster answers, quicker turnaround, and more strategic value from every engagement. Firms are increasingly hearing some version of: “I could’ve gotten that from ChatGPT.”

That doesn’t mean consultants are being replaced. It means firms have to rethink how they deliver expertise and how efficiently they run behind the scenes. And that’s exactly where AI has the potential to become more than just another productivity tool.

The Real Shift: From Productivity Gains to Decision Velocity

A lot of AI conversations focus on time savings faster emails, automated meeting summaries, notes without manual transcription. Useful, but not transformational on their own.

The real value of AI for consulting firms lies in closing the gap between spotting a problem and acting on it. In practice, that can mean:

• catching a project drifting off-budget before it becomes a write-off,
• identifying stalled pursuits earlier,
• proactively flagging utilization gaps,
• automatically pulling together engagement history before a kickoff meeting.

In other words, AI becomes valuable when it helps a firm operate faster and more proactively — not just type faster.

Why So Many AI Pilots Stall Out

Before investing in another AI tool, it’s worth asking a few simple questions instead of chasing whichever model happens to be newest:

• Is the AI embedded where the work already happens?
• Does it use the firm’s actual project and financial data?
• Is access secure and role-based?
• Can you trace where a recommendation came from?
• Is there still human oversight over decisions?
• Can the results actually be measured?

These questions matter far more today than which model sits behind a given tool. Generic AI solutions don’t understand how a consulting firm actually operates they don’t grasp realization rates, project margins, utilization leakage, or engagement profitability. Without project context, even the most impressive AI tool becomes just another disconnected assistant sitting in a browser tab.

Three Stages of AI Maturity in a Consulting Firm

AI adoption in consulting firms tends to follow three stages. Most firms believe they’re further along than they actually are.

Stage One: Ask

At this stage, AI helps answer questions and retrieve information faster using the firm’s own data generating engagement summaries, surfacing prior client work, drafting status emails, or pulling together materials ahead of a kickoff meeting without digging through multiple systems manually. This is usually where firms start to see the value of connecting AI directly to operational data, rather than treating it as a standalone chatbot.

Stage Two: Insight

At the second stage, AI stops waiting for a question and starts surfacing what actually needs attention: projects drifting off course, revenue anomalies, utilization risks, or operational bottlenecks leadership may not have noticed yet. What matters here is separating signal from noise. Most firms already have dashboards what they’re missing is a system that tells leaders which three things actually matter today.

Stage Three: Orchestrate

At the final stage, AI agents begin coordinating broader operational workflows billing, project management, accounting, proposal generation, and delivery operations. Proposal workflows are a good example: instead of manually stitching together past case studies, consultant CVs, compliance requirements, and templates, AI can coordinate much of that groundwork automatically while strategy and final decisions stay firmly in human hands.

The result isn’t replacing consultants. It’s reducing the operational drag that slows a firm down internally. Few firms are fully operating at this level today but this is where the competitive gap will widen fastest.

The Firms Getting the Most Out of AI Do the “Boring” Work First

One of the most important takeaways has very little to do with AI itself it’s about data discipline.

The firms moving fastest aren’t necessarily the ones testing the most advanced AI tools. They’re the firms cleaning up project data, standardizing workflows, and building trust in the outputs first because messy operational data produces unreliable AI results.

That’s also why many organizations are starting smaller than expected. Instead of reinventing the whole firm overnight, they focus on one or two high-impact workflows first areas where the cycle is slow, risk is high, and inefficiencies are easy to measure. That approach tends to deliver faster wins, stronger adoption, and more realistic expectations internally.

AI in Consulting Is Becoming an Operating Strategy, Not Just a Technology Decision

The firms that pull ahead in the next few years likely won’t be the ones chasing every new AI tool on the market. They’ll be the ones redesigning how work flows embedding AI into delivery operations, financial workflows, staffing decisions, and client management in ways that are measurable, governed, and genuinely useful.

At Todis, we’ve spent years implementing Deltek Maconomy at Polish consulting, legal, and audit firms and what we consistently see is that the foundation of every successful AI rollout is a single, well-organized system of project and financial data. Without that foundation, even the best AI tool remains just an add-on, not a real advantage.

Based on the Deltek article: “How AI in the Flow of Work is Changing the Way Consulting Firms Operate”