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Home » AI’s Future Is Real, The Timeline Was Always The Hard Part
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AI’s Future Is Real, The Timeline Was Always The Hard Part

Press RoomBy Press Room17 July 20264 Mins Read
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AI’s Future Is Real, The Timeline Was Always The Hard Part

KJ Kusch is Global Field CTO at WalkMe. A Navy veteran and tech leader, she guides enterprises through their digital transformation journey.

​The industry’s been going through a bit of a reckoning lately. A year ago, everyone was breathlessly predicting autonomous agents would be running your operations and saving you millions as your employees increased their output tenfold. That narrative has taken a decided shift as the numbers roll in from the first half of the year.​

The rumblings began early. In February, the National Bureau of Economic Research revealed that 80% of companies report no impact on productivity from AI. More recently, tech leaders began voicing their doubts, such as Uber COO Andrew Macdonald sharing publicly that the company had already blown through their 2026 AI budget by March, with no gains in output to show for it.​

There is no doubt that the enterprise is evolving toward intelligent, increasingly automated work. The reckoning we’re dealing with is about the pace, and that comes down to the same thing it always has when managing enterprise transformation: your people. ​

Where Most Companies Live​

The fastest version of the autonomous future assumed your organization had already done all of the unglamorous work. The data is clean, your processes documented and all employees are fluent in the systems they work with. That’s where intelligent automation can go to work and have true impact. ​

But there are few, if any, enterprises that are in that state of readiness. PwC’s 2026 Digital Trends in Operations Survey found that 87% of surveyed ops leaders say poor data quality has impacted their organization’s ability to achieve value for their digital transformation efforts. Most of these companies are still working through the digital transformation projects they started three years ago. The systems still don’t fully talk to each other, and the workflows are held together by a senior employee who knows which fields to skip. These are the same organizations now expecting autonomous agents to work on top of these stacks.​

This is why technology readiness and behavioral readiness keep getting confused. They’ve never been the same thing. The capability arrives first, then the behavior catches up later. Even then, the behavior may be partial and uneven. ​

It happened with the move to the cloud, and with every compliance program. It’s happening now with AI. The tech advances are just coming at us faster and with more riding on it. ​

The breakthrough changing this dynamic is the arrival of computer use agents. Because they operate directly at the UI layer, they bypass legacy system bottlenecks, navigating apps and executing workflows right where your people work. ​

Unleashing these agents is just the first step. The real value comes from wrapping visibility and guardrails around the entire process, ensuring workflows stay on track whether an employee or a bot is doing the clicking​

Adopting The New Way Of Working, A Standing Capability​

The most expensive mistake I see leaders make is treating the shift to a new way of working as a training sprint that wraps when the system goes live. In a world where the underlying technology shifts every quarter, that’s like treating “learning to read” as a project you finish once.​

You don’t lock in a return just by crossing a deployment finish line. Value only exists as long as your team is actively and correctly using the software. The companies pulling ahead are those treating change management as a permanent, core capability, with a continuous system in place for guiding their people and processes through constant tech shifts.​

That capability lets you graduate to autonomous workflows at the pace your actual systems and your actual people can absorb, rather than the pace a forecast insists on. It’s what turns a $50,000 monthly bill into something you can connect to an outcome, because the guidance and the guardrails live where the work happens, not in a policy nobody reads.​

For CIOs and operational leaders steering through this reality, the moving goalposts for AI are no reason to retreat. The direction is right. What’s finished is the idea that you arrive by writing a check and flipping a switch.​

So stop buying more capability before you’ve solved how your people interact with what you already have. Stop measuring success by whether the tool is live, and start measuring whether the work and adoption got better. Stop treating adoption as something that ends. Bridge the gap between where your enterprise is and where it’s going, build the path deliberately and the value is yours to capture. Treat it as automatic, and you’ll do what too many companies are doing right now: watch the future arrive on schedule while the return on it stays just out of reach.

Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?

KJ Kusch
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