8 in 10 Workers Are Still Doing AI’s Job for It

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IN THIS ISSUE: New Workday research reveals that most employees are still spending their days manually bridging broken systems, even as AI adoption spreads. Then, a new Gallup survey finds most Americans don’t want AI data centers in their backyards, putting a number on the public resistance threatening the industry’s $700 billion infrastructure push.

The Prompt

AI’s promise was that employees would stop doing the boring stuff. Software vendor after software vendor has touted their offerings as the key to freeing workers from repetitive tasks so they could focus on strategic tasks. New research from Workday released this week suggests most organizations forgot to tell their systems. While nearly all employees believe AI can improve their work, more than 8 in 10 report spending significant time as the glue between tools—moving information, reconciling conflicting data, and bridging systems that were never designed to talk to each other.

Workday’s research surveyed 6,100 HR, finance, IT, and operations professionals, all active AI users in their roles. Nearly all (97 percent) report having a positive day-to-day work experience, countering a prevailing narrative that workers are disengaged, distrust AI, or are resentful following layoffs. Still, despite this cheerful outlook, in reality, less than half are using AI to eliminate friction (43 percent) or reduce their manual work (46 percent)—a closer look at the data explains why.

The villain, as it turns out, is the computer systems themselves. Employees are frustrated because they’re forced to play traffic cop between teams, tools, and data. System incompatibility is what’s wasting significant portions of an employee’s day, which only “creates friction, slows decision-making, and contributes to unnecessary stress.” And it turns out to be a far-reaching problem: Just 27 percent of organizations have embedded AI directly into core workflows. That means the vast majority of companies are applying AI as an add-on, something that operates at the edge of business and doesn’t touch the workflow directly.

“Organizations have the ingredients they need—engaged employees, trusted systems, and advanced AI capabilities—for workforce transformation,” Workday wrote in its report. “Now is the time to close the gap and build a trusted, dependable, deterministic, AI-powered enterprise.”

Employees Are Tired of Gluing Work Together

Credit: Workday
Credit: Workday

So, what exactly are employees wasting their time on? The answer is mundane, repetitive, and almost entirely avoidable. They’re not struggling with complex strategic problems. Instead, they’re losing their days to the kind of administrative busywork that AI was supposed to eliminate. Workday’s research shows that 1 in 5 employees lose more than seven hours a week moving information and reconciling data. For IT professionals, it’s even worse with a quarter of them saying this kind of grunt work is basically what their job has become.

Looking at the data more closely, the majority of workers report spending significant time coordinating or translating work between teams and systems (82 percent), constantly shuffling information between platforms that don’t communicate with each other (81 percent), and reconciling conflicting data from different business systems (77 percent). Another 70 percent are either wrestling with administrative friction or re-entering the same information into multiple tools repeatedly.

Organizations are failing to address the root cause. Nearly two thirds of employees (61 percent) say core systems are too rigid to keep pace when change happens, and the human cost of that rigidity is real. Four in five identify having to navigate those same processes and systems as a direct source of workplace stress. In practical terms, every time a company reorganizes, launches a new product, or shifts strategy, employees are left manually bridging the gap between where the business is going and what its systems can actually support.

Credit: Workday
Credit: Workday

Employees want better ways to do work, including using AI and also having systems communicate with one another. Eighty-three percent report AI having improved their day-to-day work experience, while 61 percent attribute task completion time to the technology. And 54 percent claim AI has accelerated work in a productive way.

The problem isn’t that employees don’t want or aren’t using AI—we’ve known that for a while. It’s that they’re too buried in coordination work today to unlock its full value. 

How Organizations Are Responding

While employees push for better system integrations, companies aren’t being bold enough to deliver it. “They’re not asking, ‘How can AI work with the systems that run the business, instead of alongside it?’” Workday said. The result is a workforce using AI within the constraints of the same broken infrastructure, patching gaps rather than closing them. 

The barriers to why organizations aren’t prioritizing embedding AI in workflows vary but are consistent. Uneven skills, training, and access to AI tools top the list (27 percent), tied with too many approval and governance hurdles. Rigid systems and workflows follow at 23 percent, with unclear guidance on when to use AI and poor data quality each cited by 22 percent. Rounding out the list: murky accountability on AI use and AI outputs that conflict with existing policies (both 21 percent), and a lack of trust in AI altogether (18 percent).

Credit: Workday
Credit: Workday

It’s worth noting that several of the cited reasons—rigid systems, poor data quality, and AI outputs misaligning with existing rules—are exactly why organizations need to better system integrations in the first place. The consequences of inaction are already showing up in the data. More than two-thirds of employees (68 percent) say missing or unclear information has delayed decisions, and nearly as many report (64 percent) that teams regularly disagree over whose numbers are actually correct.

While Workday’s report focuses on outdated systems, it also highlights that management shoulders some of the blame for inaction. Having too many approval and governance hurdles, unclear guidance on when to use AI, and murky decision-making and AI accountability are not technological problems—they’re leadership ones. The data echoes reports from other companies that cite executive paralysis for sluggish enterprise AI adoption.

When companies do embed AI, they’re nearly twice more likely to report “meaningful” time savings than those that haven’t yet made the switch.

“AI can reduce friction, but it cannot compensate for fragmented systems, weak governance, or poor operating design on its own,” Workday writes in the report. “This is a call to action to organizations to evolve their architecture, integrating AI in their end-to-end processes.”

Workday makes a compelling case for why interconnected systems are essential in the AI era, but the report is notably vague on how organizations should get there. Modernizing core infrastructure isn’t a software decision—it’s an organizational one, requiring executive commitment, governance reform, and a willingness to retire systems that employees have worked around for years. Buying a new system is the easy part. Redesigning how an entire organization operates around it is another matter entirely.

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A Closer Look

The AI infrastructure buildout is running headlong into a wall of public resistance. As tech giants race to expand compute capacity to power their models, a new Gallup survey finds that seven in 10 Americans oppose building AI data centers in their backyard. Among those opposed, half believed the data centers would negatively impact natural resources. Less than a quarter (22 percent) were worried about the impact on the quality of life, 20 percent were afraid of rising costs, and 16 percent thought pollution levels would rise.

American supporters of data centers cite the economic benefits (66 percent) that would be created, from job growth, tax revenue, and community development. Seventeen percent touted the technology benefits, while ten percent believed it would help them personally.

Credit: Gallup
Credit: Gallup

Every community is in the middle of this conversation, and the mere hint of a tech company acquiring land in a rural area is often enough to ignite fierce local opposition. The financial stakes are significant: according to Data Center Watch, local activism led to $64 billion in U.S. data center projects being blocked or delayed between May 2024 and March 2025. Yet the industry shows no sign of slowing, as Big Tech companies are reportedly on pace to spend nearly $700 billion on AI infrastructure this year alone. That gap between community resistance and corporate momentum is what makes this fight so hard to resolve.

One of the most consequential battlegrounds has been Prince William County in Virginia, where developers proposed the Prince William Digital Gateway—a 23-million-square-foot data center complex planned across 2,100 acres near Manassas National Battlefield Park. The project would have become the largest data center campus in the world. Residents and historic preservation organizations pushed back hard, but in December 2023, the county board voted 4-3 to rezone the land. Lawsuits followed, and the courts sided with opponents. The Virginia Court of Appeals ruled that the Board of Supervisors had sped up the approval process without giving the public a fair chance to weigh in. The decision led the county and one of the project’s developers, Compass Datacenters, to not appeal. However, the other developer, QTS, has petitioned the state’s Supreme Court to consider the case.

There have been similar situations happening in states like Pennsylvania, Maine, Louisiana, and most recently in Utah. The project in Box Elder County in the Beehive State is backed by “Shark Tank’s” Kevin O’Leary. The 40,000 9GW data center received approval from county commissioners this week, much to the dismay of opponents. In some cases, like in Saline Township in Michigan, local leaders deny permits, but somehow construction begins anyway. And even if data centers get built, that’s not the end of the story—lawsuits are being filed against companies over the dangers being inflicted on communities.

Politically, there’s bipartisan anger towards new data center development. That said, Gallup’s data shows that Democrats are more opposed than Republicans, 56 percent vs. 39 percent. Nearly half of independents (48 percent) are strongly against. Women are also more likely than men to register strong opposition (55 percent vs. 43 percent).

Gallup finds that Americans have adopted a “not in my backyard” (NIMBY) attitude to data centers. It will certainly continue to be a hotbed issue in the coming years, especially as AI usage grows. As opposition hardens on the ground, some in the industry are already looking up. Google and SpaceX are reportedly in talks to put data centers into orbit—a sign that the search for compute capacity with fewer neighbors may eventually leave Earth altogether.

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Quote This

“These days, one of the biggest challenges—and this is the part that people don’t realize about AI—the first thing that AI is doing right now is creating an enormous number of jobs. AI creates jobs. AI is [the] United States’ best opportunity to re-industrialize ourselves.”

— Nvidia CEO Jensen Huang, speaking at the Milken Institute Global Conference, on May 4, 2026, disputing the idea that AI is disrupting the workforce.

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