Here’s an idea most enterprises still haven’t accepted: your AI isn’t underperforming because the models aren’t good enough. It’s underperforming because of how work is structured around it. Messy workflows, scattered data, no clear governance. Drop even the best tool on top of that and it struggles. And piling on more tools can make things worse, not better.
Few people have a better vantage point on this than Tom Scott. As CEO of Wrike, the intelligent work management platform used by 20,000+ organizations from NVIDIA to Jaguar Land Rover, he sees how AI is actually landing inside enterprises, all while reinventing his own 20-year-old company in real time. An operator who came up through finance and operations, including as CFO at Zebra Technologies, Scott makes a simple case: capability was never the bottleneck. Context, control, and collaboration are.
It’s not the technology. It’s the people, process, and tech, all at once.
Transformation, Scott argues, is never just about the capability of the technology. It always comes down to the people, the process, and the tech. What makes this moment different is timing. Earlier technology waves moved along the adoption curve, from early adopters to the mainstream to the laggards, giving organizations time to absorb the change. This time everyone is having the same conversation at once while their people and processes scramble to catch up. That friction is why so much AI value stays trapped inside individual and team silos instead of compounding at scale.
Context, control, and collaboration are the three Cs that decide whether AI delivers.
Context is the best-understood of the three: the more grounded and specific your inputs, the better the decisions. Control is the accountability layer, the audit trail and governance for human and agent users alike, plus the discipline to manage how much context you feed the models so the economics don’t blow up. Collaboration is the least understood and, in Scott’s view, the most important. Wrike was founded 20 years ago on the premise that unlocking human potential requires collaboration. Introducing new kinds of users, with a human in the loop, makes that more important than ever.
The hard part isn’t the strategy. It’s the execution.
The leaders who cross the strategy-to-execution gap are the ones who get hands-on. Scott draws a sharp contrast: the executive who reads a post claiming another company got 100X and asks their team to “make this happen tomorrow” is having a very different conversation than the one who says, “I built this thing over the weekend. Explain to me why we can’t do this at scale.” He’s candid that he isn’t Wrike’s technical founder, but treats that as a reason to demonstrate the technology himself, not an excuse to sit out.
Be careful you’re not just automating mediocrity.
Mapping an existing process and layering AI on top can feel like progress. But if you don’t understand the process in detail, Scott warns, you can automate your workflow flawlessly and discover that all you really did was automate mediocrity. His fix is to start by subtracting: strip out as much of the old process as possible, then ask what the minimum viable system design actually needs to be before deciding what to keep.
Transformation is messy, and it has to be owned by the CEO.
Scott has led multiple transformations at Wrike in four and a half years, and he’s blunt that the work is never linear. Some people rise to the occasion and drive experimentation. Strong past performers sometimes aren’t ready for the moment. He frames the current effort as a series of focused “sprints” with employee groups pushing experiments, scaling what shows promise. Through all of it, accountability sits with the CEO, who has to make the call, often alone, and still owe the team a clear why.
The specialist is giving way to the full-stack professional.
The post-war org chart was built to move information up and down a hierarchy through ever-increasing specialization. That model is being contested by what anyone can now learn quickly. Scott hires for curiosity, which can’t be trained, and resilience, because change is never up-and-to-the-right. The people who thrive are “full-stack”: they orchestrate the work around them rather than owning one narrow slice, and, he notes, the few who already exist can name their price. His advice to his pre-AI self is the same one he gives his team: move faster, and your going-in assumption should be that you’re going too slow.
