From Random Acts of AI to a System That Compounds
Spoiler Alert: It requires a lightweight coordination layer
Over the past few weeks I’ve been on a string of calls with the leaders evaluating our Running Hyperadaptive Organizations class. They come from financial services, global tech, payments, all over. Most of them describe similar situations in similar words.
There is AI activity everywhere…a pilot in marketing…a clever workflow someone in finance built over a weekend…a team using Copilot that swears it has changed their week. Real energy, real effort, real wins. And yet, when we explore the impact all of this has on the business, they smile knowingly, and the call goes quiet for a second.
This is the thing I named Random Acts of AI in the book, and was highlighted in Fast Company this week. It represents AI that isn’t tied to strategy, and therefore…isn’t tied to results. We’re at the point where we’re trying to turn a hundred scattered acts of AI to coordinated activity that produces something the business can feel.
Why Is it So Hard to Scale AI?
Here’s how it usually goes (at least according to the Hyperadaptive Journey Map). A company gets excited, hands out licenses, has a few solid wins. The early numbers look good. Then they try to connect the work across functions, and the progress stalls. The marketing team is moving fast, legal is still on its heels, and the handoff between them is exactly as slow as it was a year ago. Ethan Mollick calls this the jagged edge, and it’s the natural result of moving one part of a system while the rest stays put.
I spent a lot of years in the transformation world before this one. The Toyota Production System, Agile, DevOps. Every single one taught the same lesson, which is that progress stalls when you move one dimension and leave the others behind. AI is no different, except the window to figure it out is a lot shorter. With digital transformation, companies had roughly a decade. With AI, it will be a few short years.
So when a leader tells me their AI adoption has plateaued, I’ve learned that they most likely have a coordination problem. The wins fail to scale because nothing connects them to each other or to a goal worth reaching.
Random Acts of AI is a Coordination Problem, Not a Tool Problem
Look at how the companies that are actually getting results set things up. When Schneider Electric wanted to take administrative drudgery off its global sales teams, they didn’t just push Microsoft Copilot for Sales out the door and hope. Audrey Hazak, their SVP of Digital Customer Relationship Management, deployed it on top of an AI hub and a governance framework that were already in place. Because the scaffolding existed, the same tool that would have been a random act somewhere else became a targeted, scalable solution. The pilot grew to five thousand users, and her team called it a game changer, not because the software was magic but because it solved a real problem inside a system built to spread the win.
That’s the part most efforts skip. We treat AI as a tool initiative, so we get tool results: isolated, local, and fragile the moment anyone tries to coordinate across functions.
It’s like handing everyone a drill and telling people to go make some holes. That isn’t going to get the house built.
The work that compounds sits underneath the tool, in the things almost nobody touches. Three of them come up again and again:
Strategic Direction. If your organization lacks an AI-north star - the goals you are trying to achieve with AI - you won’t know how to organize around it.
Incentives. If your reward systems still pay people for being right instead of for learning fast, the experimentation you need will quietly dry up, because nobody wants to be the one whose pilot didn’t pan out.
Decision rights. AI collapses hierarchies. A junior analyst with the right model can now make a call that used to need three layers of sign-off, and if you haven’t rewired who decides what, you leave most of the speed on the table.
How you organize. Most companies are still arranged around the work as it existed twenty or forty years ago. Coordinated AI means organizing around the work as it exists now.
When did your organization last look at its incentives and ask whether they reward learning or just reward being right? That one question tends to explain a lot about why AI isn’t scaling.
How Do You Coordinate AI Across Teams and Functions?
The good news is you don’t have to move everything at once, and you shouldn’t try. The point isn’t a big-bang reorganization. It’s that the dimensions have to move together as a system, even if they move a few at a time. You pick what’s ready, you move it in concert with the pieces it touches, and you keep the connective tissue intact as you go.
The companies doing this build mechanisms, not just enthusiasm. They stand up small cross-functional pods that run experiments and capture what works, then carry that learning to the front lines so the next team doesn’t start from zero. Motor Oil Group runs something they call an AI Garage, where their champions do weekly show-and-tell sessions and hands-on training, so a discovery in one corner of the company actually reaches the rest of it. That’s the difference between a hundred people each learning the same lesson in isolation and an organization that learns once and spreads it everywhere. A North Star gets you pointed in one direction, but it’s the connective tissue that lets the value compound.
Where This Goes
The organizations that win the next few years won’t be the ones with the most pilots or the flashiest tool. They’ll be the ones that turn scattered effort into a system that learns and coordinates faster than the technology underneath it changes. That’s the whole move, from random acts of AI to coordinated activity that actually shows up in the results. It’s slower to start and it’s far more durable, and it’s the work I’d put my money on every time.
If you want help building that connective tissue inside your own organization, that’s exactly what we do in the AI Lead Accelerator: hyperadaptive.solutions/accelerate.
And if you’d like the full five-stage path, Hyperadaptive: Rewiring the Enterprise to Become AI-Native is out now at hyperadaptive.solutions/book.