Artificial intelligence is facing a credibility crisis in the workplace, as new studies reveal that poor implementation and lack of training are producing a flood of low-quality, AI-generated output—what researchers are calling “workslop.”
A recent Harvard Business Review study found that more than 40% of full-time U.S. employees have received AI-generated work that “masquerades as good work but lacks the substance to meaningfully advance a given task.” The report concluded that this “workslop” is actively destroying productivity.
But according to Gene Marks, technology columnist and consultant, the fault doesn’t lie with the technology itself—it lies with the managers using it.
“In the workplace, the buck always stops with the boss,” Marks wrote. “The responsibility for AI’s ‘workslop’ lies fully at the feet of the employer.”
The Reality Behind the AI Hype
The backlash comes amid mounting skepticism toward AI’s real-world impact.
A KPMG survey of 48,000 people found that only 8.5% “always” trust AI search results, while Gartner reported that more than half of consumers have encountered “significant” AI-generated mistakes.
Meanwhile, a McKinsey report revealed that 80% of companies using generative AI have seen “no significant bottom-line impact,” and an MIT study found that 95% of corporate AI pilot projects failed to deliver results.
Still, despite the hype and disappointment, Marks argues that AI’s failure in the workplace often stems from poor planning, limited oversight, and a lack of employee training rather than from flaws in the technology itself.
The Real Problem: Leadership, Not Algorithms
Marks, who has spent over two decades helping small and mid-sized businesses implement digital systems, says the same pattern repeats with every wave of technology adoption: organizations underestimate the investment needed in people, not software.
He challenges employers to ask critical questions before blaming AI:
- Have you trained employees on how to prompt or use AI effectively?
- Does your company have an AI policy outlining what tools can be used and for what purpose?
- Is there a designated person or team overseeing AI deployment and performance?
- Have you established metrics to measure AI’s impact on productivity or revenue?
Without structured guidance, Marks warns, companies end up with chaos—a “free-for-all mess of apps” and no consistent processes to ensure value.
“In most cases, the software is not the problem,” he wrote. “It’s the lack of investment in the people using it.”
The Misconception of ‘Plug-and-Play’ AI
Employers, Marks argues, have been misled by big tech’s marketing into believing AI tools are “plug-and-play” solutions that automatically generate profits.
But AI, like any tool, requires strategy, oversight, and continuous improvement to produce real benefits.
“AI can be a powerful tool if deployed the right way and with the right expectations,” Marks said. “But in the end it’s just that: a tool. And new tools require thought, training, processes, and investment.”
Bottom Line
While AI may be capable of producing “workslop,” the real problem is organizational complacency. Companies that fail to establish training, standards, and accountability structures risk wasting both time and technology.
“AI doesn’t produce ‘workslop,’” Marks concluded. “Employers do.”
