Originally posted on the Rochester Business Journal:
Most companies still use a model of expertise designed for a slower century. Leaders describe the problem, hand it to specialists, and wait for the answer. And wait.
For decades, expertise has been delivered like a finished product. Specialists disappear behind a curtain—into a conference room, a studio, a spreadsheet—and weeks later they return with the solution.
That model sometimes produced brilliant work. But it also produced distance: between decision-makers and the thinking being built; between strategy and execution; between imagination and reality; between the question asked and the answer actually needed. And increasingly, it no longer fits the world we’re operating in. The linear model of expertise is starting to break down. For most of the last century, that model made sense. Research took time. Drafting took time. Iteration took time. The only way to move faster was to add more people — and more hours.
Then generative AI arrived.
Suddenly the economics of expertise began to change. AI doesn’t replace experts. It exposes how inefficient the old delivery system had become. The traditional process is linear: brief → analysis → strategy → creative → presentation → revision → revision → revision → revision → launch. It feels safe because it’s orderly. But it’s also why so much expert work arrives late, over-polished, tangential and disconnected from the messy reality leaders are actually dealing with.
AI turns that line into a series of expanding loops, spirals. Teams can now generate options quickly, pressure-test assumptions in real time, and iterate together instead of waiting weeks for a reveal.
Research increasingly shows the biggest gains come when AI is integrated into team collaboration, not used by individuals working alone. In other words, the technology works best when expertise becomes more collaborative, not more isolated. Consulting firms are starting to say the same thing. McKinsey recently summarized the shift bluntly: “redesigning workflows is a key success factor for capturing the value of AI”.
That sentence is the whole story.
Organizations pulling ahead are the ones that stop treating expertise like a finished product and start treating it like a living capability—built with the people who own the decisions, not performed for them at the end of a long wait.
I’ve seen this shift up close in our work at Truth Collective here in Rochester for powerful regional and national brands. The most surprising change we’ve made isn’t an AI tool choice. It’s a relationship commitment. Instead of disappearing for weeks and returning with the answer, we bring clients into the work early through collaborative, human-led, AI-supported working sessions we call AI Bravestorms.
The goal isn’t to protect some secret creative process behind closed doors. It’s to open the process so better thinking happens faster. We also train teams to use AI in ways that deliberately counter the knowledge-hoarding instinct that defined the old agency or expert model.
The point isn’t to guard expertise. It’s to raise the floor—so more people can contribute good thinking earlier—without lowering the ceiling. Because democratizing premium creativity doesn’t mean lowering standards. It means removing the gates around excellence.
One client described the relationship difference this way: “We could’ve ended up with an agency that was brilliant—and painful to work with. That wasn’t the trade-off we had to make. No matter what the dynamic of the team was, we always had ‘brilliant’ and ‘kind.’”
That observation captures something important: AI doesn’t just change how work gets done.
It changes how expert relationships work. The old model priced time and labor because time and labor were the bottlenecks. In the AI era, the real bottleneck is judgment: choosing the right problem, making the call, and staying accountable for the consequences.
The future of expertise won’t look like a faster version of the old system. It will look more collaborative. More transparent. And far more human. Because when answers arrive faster, the real advantage shifts to something deeper: Who can think best together.
So our new truth is this: the linear model of expertise is ending and that’s not a threat to expertise.
It’s the beginning of a better way to use it.
