Truth Revealed: When AI breaks your business model – What’s Next for Consultancies
- 6 days ago
- 3 min read
In the latest episode of Truth Revealed, host Duart Rankin sits down with AI and communications expert Andrew Bruce-Smith to unpack a question many are quietly avoiding: what happens when AI doesn’t just improve how you work—but fundamentally disrupts the consulting agency model?
This isn’t another conversation about shiny tools or prompt hacks; it’s about something far more existential.
The uncomfortable truth about “efficiency”
For years, consultancies have sold time. Billable hours. Process. But what happens when AI collapses the time it takes to deliver that work?
As Andrew Bruce Smith points out, the industry has been circling this shift for over a decade—but only now is it unavoidable. AI doesn’t just make workflows faster; it challenges the very premise of charging for time.
Yet most organisations are still treating AI like a productivity add-on. A co-piloted email here, a summarised document there. Safe. Incremental. Contained. But beneath the surface, something more disruptive is happening.
Synthetic data, real decisions
Take synthetic data—a concept that still triggers scepticism. Isn’t it just… made up? That’s the instinctive reaction. But as the conversation reveals, that framing misses the point entirely. Synthetic data isn’t about replacing reality. It’s about extending it. Stress-testing it. Interrogating it in ways traditional research never allowed.
From digital twins to message testing at scale, the ability to simulate audiences and scenarios is already changing how insights are generated—and more importantly, how quickly decisions can be made.
There’s a catch, though. More data doesn’t mean better thinking. And when access is democratized, the risk shifts from not having insights to not knowing what good looks like.
Which leads to a bigger problem.
Your organisation doesn’t know how it works
Most companies don’t understand their own workflows. Not really. They assume they do. They have processes, decks, and operating models. But scratch the surface, and you’ll find something messier: undocumented shortcuts, tacit knowledge, inconsistent execution. AI exposes this instantly.
Before you can automate or augment anything, you must define it. And the moment you try, the gaps become obvious. This is where most AI strategies quietly fail—not at the technology level, but at the organisational one. Giving people tools isn’t transformation. It’s distribution.
From prompts to agents: the real shift
If 2023 was about prompts, and 2024 about adoption, then 2026 is shaping up to be about something else entirely: agency.
AI agents don’t just assist—they also act. They plan, execute, and iterate. They operate across tools, systems, and tasks. In effect, they behave less like software and more like junior employees.
Which raises a provocative question: If you suddenly had access to hundreds of “synthetic workers” … could your organisation actually manage them?
Because this isn’t a technical challenge. It’s a leadership one. Briefing clearly. Defining outcomes. Orchestrating workflows. Evaluating quality. The same skills that make great consultants are now the skills required to work with AI.
And most teams haven’t been trained for that.
So, what are clients really paying for?
This is where the conversation lands—and it’s the question every consultancy should be asking itself right now. If AI can deliver faster, cheaper, and at scale… what is the thing that clients will still value?
It’s not time. It’s not process. It’s not even output. It’s judgment. Direction. The ability to define the right problem—and navigate ambiguity when the answer isn’t obvious.
In other words: the very things many organisations have spent years deprioritising. The shift is already happening. Quietly, unevenly—but undeniably. The question isn’t whether AI will change your business model. It’s whether you’ll recognise it in time to redesign it.
Watch the full episode of Truth Revealed to hear the full conversation—and then join the debate.
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