AI Highlights Your Workforce’s Wasted Potential

By Iliya Rybchin

Every executive leadership team is talking about it. The memos have been sent, task forces have been formed, the town halls have been held, and the mandates are clear: Everyone must embrace artificial intelligence. Leaders are eager to solve the crisis by closing the skills gap, reskilling the workforce, and racing to teach a generation of employees how to prompt-engineer their way to productivity.

They are unfortunately focusing on the wrong crisis.

The real crisis was there all along, hidden in plain sight. It’s not an AI problem; it’s an organizational and philosophical one. Generative AI doesn’t just automate tasks. It performs a brutal, unblinking audit of a company’s work design, its training programs, and the very value of its human capital. The story isn’t that robots are taking jobs. The story is that AI is revealing how many of those jobs were never designed to harness human potential in the first place.

For decades, organizations were built on a foundation of low-value, repetitive tasks, politely calling it “paying your dues.” Now, AI is holding a mirror up to organizational structures, and the reflection reveals not a need for reskilling but a long-overdue reckoning with what constitutes “work.”

One only needs to look at any entry- to mid-level job description. The verbs tell the story: compile, review, summarize, track, format, update, coordinate. These aren’t strategic activities. They’re biological API calls—humans serving as middleware between disconnected enterprise systems.

Employers have come to accept a system where people spend 60% of their time on repetitive work that exists primarily to compensate for fragmented technology and bloated processes.

This isn’t new. When the internet arrived, companies layered digital tools onto analog processes, creating more bureaucracy. When cloud computing emerged, they moved servers to AWS but kept the same approval workflows that require printing and processing of paper documents. Each technological wave exposed the same misalignment between tools and organizational design.

Despite trillions of dollars invested in digital transformation, cloud computing, automation, and enterprise software over the past 15 years, white-collar productivity growth has effectively flatlined over the same period. Companies gave their workforces Slack, Zoom, SharePoint, Workday, and Salesforce, yet output per hour barely budged.

Why? Because companies didn’t use technology to eliminate low-value work; they used it to accelerate low-value activity.

The real shock isn’t that AI can do a lot of white-collar work. The real shock is realizing how much of a company’s headcount was focused on work that never should have required a human in the first place.

THE MYTH OF “GRUNT WORK” AS APPRENTICESHIP

For generations, leaders justified the corporate rite of passage known as “paying your dues.” They told themselves, and their new hires, that years of mind-numbing, repetitive tasks were a necessary apprenticeship—a crucible that forged judgment and built character.

• You “learn the business” by doing reconciliations.
• You “build judgment” by drafting versions 12 through 27 of the same slide.
• You “earn your stripes” by staying late to assemble reports no one will remember reading.

In reality, this was a convenient fiction. It was hazing by spreadsheet.

Grunt work was never a deliberate or effective training strategy. It was a symptom of organizational inertia and a failure to properly design roles and workflows. Everyone knew this work was questionable, but it was easier to hire another body than fix the underlying problem.

There is always great enthusiasm to hire more staff. Leaders are eager to build large organizations because at many companies, one’s gravitas, seniority, and standing are measured by team size.

The data backs up what many employees quietly knew long before large language models entered the boardroom. Multiple studies have found that knowledge workers spend more than half their day on repetitive, low-value tasks.

AI AS AN X-RAY FOR JOB DESIGN AND THE BUSYWORK ECONOMY

Companies normalized inefficiency and built entire career paths around it. Each new system, process, regulation, or compliance requirement added a little bit of manual glue work.

Entry-level roles have become manual interfaces between broken systems—endless cycles of copying data, summarizing documents, and tracking information that should have been automated years ago.

The single biggest productivity prize from AI may not be deploying virtual assistants to glamorous use cases. It may be eliminating this invisible tax of busywork.

THE REAL WORKFORCE CRISIS: A FAILURE OF IMAGINATION, NOT TECHNOLOGY

The real crisis isn’t about teaching employees to write better prompts. It’s about a fundamental failure of leadership.

Even when companies do invest in training, they often miss the point. Employees become masters of a tool with no strategic problems to solve.

This is the predictable result of a system that has never valued efficiency.

THE PATH FORWARD: FROM AUTOMATION TO AUGMENTATION

AI’s arrival has created a temptation to respond with familiar tools: task forces, training programs, transformation roadmaps. Those will be necessary, but they are not sufficient.

The path forward is not to simply layer AI on top of broken processes. This moment requires leadership courage.

Before launching his own AI-native consulting firm, Iliya Rybchin was an operating executive (most recently at BDO USA as principal, strategy and innovation), an entrepreneur, and an investor. He turns disruption into unfair advantage not by parroting best practices, but by challenging them.