AI 'Workslop' Undermines Productivity and ROI in the Workplace

Companies are losing money to AI "workslop" that slows everything down

Serving tech enthusiasts for over 25 years. TechSpot means tech analysis and advice you can trust. Cutting corners: Large language models excel at producing grammatically correct sentences but often stumble on accuracy and clarity. Without human review, their outputs create more confusion than progress. This workslop shifts effort downstream, bogging down the very workplace processes AI is supposed to make faster and more efficient. Modern workplaces are increasingly adopting artificial intelligence, promising speed, efficiency, and innovation. However, the reality is often messier in practice. Many companies feel pressured to adopt AI quickly, worried that failing to do so will leave them behind competitors. Yet work produced by AI can create more correction and confusion than it saves, a phenomenon Harvard Business Review (HBR) has termed "workslop." Research from HBR's BetterUp Labs and Stanford Social Media Lab shows that AI-generated documents that appear polished can lack the substance needed to advance a task. According to Stanford's ongoing survey of US-based full-time employees, 40 percent reported receiving such outputs in the past month. Workers spend nearly two hours per incident correcting or interpreting them, creating significant hidden costs for companies. Multiplied across large organizations, those hours translate into thousands of lost workdays each year and millions of dollars in wasted effort. Harvard Business Review cited one retail director who was less than impressed with his company's implementation of AI automation. "I had to waste more time following up on the information and checking it with my own research," the director said. "I then had to waste even more time setting up meetings with other supervisors to address the issue. Then I continued to waste my own time having to redo the work myself." That manager's frustration isn't an isolated case. The social and emotional toll is real. Over half of respondents said receiving low-quality AI outputs made them feel annoyed (53 percent), while nearly a quarter reported feeling offended (22 percent). Colleagues who sent such work were often seen as less capable or reliable, showing how AI missteps can ripple through team dynamics. Even with AI adoption soaring - Gallup reports that US employees using AI at least a few times a year have nearly doubled in recent years - many pilot programs fail to generate measurable returns. An MIT Media Lab study found that fewer than one in ten AI projects delivered real revenue gains, warning that "95 percent of organizations are getting zero return" on their AI bets. The challenge isn't just the technology itself, but how organizations deploy it. Blanket mandates to use AI everywhere often encourage mindless copy-paste behavior rather than thoughtful application. Researchers recommend clear guardrails, deliberate workflows, and leaders who set the example for using AI effectively. That can mean setting limits on where AI is appropriate, such as early drafts or routine summaries, while requiring human oversight for final outputs. When management models selective, purposeful use, employees are more likely to see AI as a tool rather than a shortcut. Image credit: Harvard Business Review

'Workslop': AI-Generated Work Content Is Slowing Everything Down

AI slop has infiltrated the workplace, costing companies time and money. AI slop isn’t limited to cringey cat videos on Facebook anymore; it has made its way into the workplace. The Harvard Business Review recently coined a term for low-quality, AI-generated work documentsâ€"workslop. The respected business publication argues that this growing pile of phoned-in memos and reports is one reason many companies are seeing little return on their AI investments. The report lands as the AI industry keeps booming. The U.N. recently projected the global AI market will rocket from $189 billion in 2023 to a staggering $4.8 trillion by 2033. In the U.S., the share of employees who say they use AI at least a few times a year has nearly doubled from 21% to 40%, according to Gallup. And Accenture reported that the number of companies running fully AI-driven processes nearly doubled in the past year. But as offices everywhere are scrambling to plug AI tools into their workflows so they don’t get left behind, very few are seeing their efforts actually pay off. Just last month, an MIT Media Lab study found that fewer than one in ten AI pilot projects delivered real revenue gains and warned that “95 percent of organizations are getting zero return†on their AI bets. Based on 150 executive interviews, a survey of 350 employees, and an analysis of 300 public AI deployments, the report triggered a dip in AI stocks. Now, researchers from Harvard Business Review’s BetterUp Labs, working with the Stanford Social Media Lab, are pointing to workslop as a possible culprit behind those disappointing results. “The insidious effect of workslop is that it shifts the burden of the work downstream, requiring the receiver to interpret, correct, or redo the work. In other words, it transfers the effort from creator to receiver,†the report’s authors wrote. The Harvard Business Review defines workslop as, “AI generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task.†This can look like polished presentation slides, eloquent report summaries, and even decent code, but on closer inspection, the work can be missing key context and is ultimately unhelpful. According to the researchers’ ongoing survey, the problem is widespread. Of 1,150 U.S.â€"based full-time employees across industries, 40% said they had received workslop in the past month. The proliferation of workslop could cost companies time, money, and even trust among workers. Surveyed workers reported spending an average of one hour and 56 minutes per incident dealing with low-quality AI outputs. Researchers calculated that, based on respondents’ salaries, workslop carries an invisible cost of around $186 per month. For companies with thousands of employees, that can translate into millions of dollars in lost productivity each year. Workslop also takes a social and emotional toll in the office. When asked, 53% of participants said receiving workslop made them feel annoyed, 38% confused, and 22% offended. Half of the respondents also reported viewing colleagues who sent workslop as less capable and reliable. To steer clear of “workslop,†researchers suggested managers need to set clear guardrails and model thoughtful and purposeful use of AI themselves. Blanket “AI everywhere all the time†mandates just lead to workers mindlessly copying and pasting AI responses into documents. Instead, organizations should develop best practices and recommendations regarding how generative AI can truly add value and help achieve company goals.

AI 'Workslop' Is Killing Productivity and Making Workers Miserable

AI slop is taking over workplaces. Workers said that they thought of their colleagues who filed low-quality AI work as "less creative, capable, and reliable than they did before receiving the output." A joint study by Stanford University researchers and a workplace performance consulting firm published in the Harvard Business Review details the plight of workers who have to fix their colleagues' AI-generated "workslop," which they describe as work content that "masquerades as good work, but lacks the substance to meaningfully advance a given task." The research, based on a survey of 1,150 workers, is the latest analysis to suggest that the injection of AI tools into the workplace has not resulted in some magic productivity boom and instead has just increased the amount of time that workers say they spend fixing low-quality AI-generated "work." The Harvard Business Review study came out the day after a Financial Times analysis of hundreds of earnings reports and shareholder meeting transcripts filed by S&P 500 companies that found huge firms are having trouble articulating the specific benefits of widespread AI adoption but have had no trouble explaining the risks and downsides the technology has posed to their businesses: "The biggest US-listed companies keep talking about artificial intelligence. But other than the 'fear of missing out,' few appear to be able to describe how the technology is changing their businesses for the better," the Financial Times found. "Most of the anticipated benefits, such as increased productivity, were vaguely stated and harder to categorize than the risks." Other recent surveys and studies also paint a grim picture of AI in the workplace. The main story seems to be that there is widespread adoption of AI, but that it's not proving to be that useful, has not resulted in widespread productivity gains, and often ends up creating messes that human beings have to clean up. Human workers see their colleagues who use AI as less competent, according to another study published in Harvard Business Review last month. A July MIT report found that "Despite $30-40 billion in enterprise investment into GenAI, this report uncovers a surprising result in that 95% of organizations are getting zero return ... Despite high-profile investment, industry-level transformation remains limited." A June Gallup poll found that AI use among workers doubled over the last two years, and that 40 percent of those polled have used AI at work in some capacity. But the poll found that "many employees are using AI at work without guardrails or guidance," and that "The benefits of using AI in the workplace are not always obvious. According to employees, the most common AI adoption challenge is 'unclear use case or value proposition.'" These studies, anecdotes we have heard from workers, and the rise of industries like "vibe coding cleanup specialists" all suggest that workers are using AI, but that they may not be leading to actual productivity gains for companies. The Harvard Business Review study proposes a possible reason for this phenomenon: Workslop. The authors of that study, who come from Stanford University and the workplace productivity consulting firm BetterUp, suggest that a growing number of workers are using AI tools to make presentations, reports, write emails, and do other work tasks that they then file to their colleagues or bosses; this work often appears useful but is not: "Workslop uniquely uses machines to offload cognitive work to another human being. When coworkers receive workslop, they are often required to take on the burden of decoding the content, inferring missed or false context. A cascade of effortful and complex decision-making processes may follow, including rework and uncomfortable exchanges with colleagues," they write. The researchers say that surveyed workers told them that they are now spending their time trying to figure out if any specific piece of work was created using AI tools, to identify possible hallucinations in the work, and then to manage the employee who turned in workslop. Surveyed workers reported spending time actually fixing the work, but the researchers found that "the most alarming cost may have been interpersonal." "Low effort, unhelpful AI generated work is having a significant impact on collaboration at work," they wrote. "Approximately half of the people we surveyed viewed colleagues who sent workslop as less creative, capable, and reliable than they did before receiving the output. Forty-two percent saw them as less trustworthy, and 37% saw that colleague as less intelligent." No single study on AI in the workplace is going to be definitive, but evidence is mounting that AI is affecting people's work in the same way it's affecting everything else: It is making it easier to output low-quality slop that other people then have to wade through. Meanwhile, Microsoft researchers who spoke to nurses, financial advisers, and teachers who use AI found that the technology makes people "atrophied and unprepared" cognitively. Each study I referenced above has several anecdotes about individual workers who have found specific uses of AI that improve their own productivity and several companies have found uses of AI that have helped automate specific tasks, but most of the studies find that the industry- and economy-wide productivity gains that have been promised by AI companies are not happening. The MIT report calls this the "GenAI Divide," where many companies are pushing expensive AI tools on their workers (and even more workers are using AI without explicit permission), but that few are seeing any actual return from it.

AI was supposed to boost productivity -- but a new report says 'workslop' is making it worse

If you've used AI tools, you know that they aren't always accurate. A new study even highlighted that ChatGPT is actually wrong 25% of the time. And while some big tech CEOs believe AI will cause mass unemployement, it seems like for now AI is only dragging us down. Companies acrosss the board are deploying AI, but the gains are less than satisfactory. Turns out, much of what these tools produce is useless junk that experts are calling "workslop." Not to be confused with "AI slop," which is all the low-quality AI-generated content you see while scrolling social media. First reported by Harvard Business Review, the term "workslop" describes the flood of AI-generated content that is ultimately of very low value. Instead of soild reports and expert-level presentations, what's generated are sloppy reports, half-baked documents, boilerplate content with little insight or errors that require humans to intervene and fix the job. Basically it's when AI delivers on volume but not quality, which ultimately causes more work. The HBR authors argue that much of this comes down to misplaced incentives. Businesses adopt AI tools to move faster, not necessarily to improve quality. Workers lean on the AI for support, even if the output isn't worth much. Because AI content is so cheap to generate, organizations tolerate "good enough" outputs -- even if employees spend hours cleaning them up later. This doesn't mean we should ditch AI completely. I have a feeling it's here to stay. The key is to learn how to use it properly and in the smartest ways. It's also important to remember that AI is designed for generating ideas and not the whole project. Users should see it as a brainstorming partner or rough-draft generator, but should never rely on it completely to do the entire job. Even if you're not the one using AI at work or haven't uploaded any AI content to social media, chances are you're feeling the ripple effects. Whether it's a report for a client or a video of a cat serving french fries, it wastes time, lowers trust and adds hidden costs. Not to mention there are few things more frustrating than expecting AI to lighten your load only to find yourself babysitting it -- or worse, fixing its mistakes. AI has a lot of potential for productivity support and helping us manage workflows. But only if it actually saves time and produces value. If it's just creating busywork that drags you down, it's not a tool. It's a sloppy trap. Follow Tom's Guide on Google News and add us as a preferred source to get our up-to-date news, analysis, and reviews in your feeds. Make sure to click the Follow button!

Enterprise AI projects aren't producing value. Is 'workslop' one reason why?

Businesses across industries have been betting big on AI in the workplace -- but the results have been, frankly, underwhelming. According to a new MIT Media Lab report, a staggering 95 percent of organizations have seen no measurable return on their investments in generative AI tools. MIT researchers cite several reasons for this adoption/ROI gap. Chief among them: AI doesn't slot neatly into many workplace workflows, and most models still lack the contextual awareness needed to adapt to industry-specific tasks. But a separate team at BetterUp Labs argues there's another culprit: AI workslop. Writing in Harvard Business Review, the researchers define workslop as "AI-generated content that looks polished but doesn't actually move work forward." In practice, it means employees end up spending more time fixing, rewriting, or clarifying AI's "help" than if they'd done the job themselves. The downstream effect is costly. The report estimates that workers spend nearly two hours a day (1 hour, 56 minutes, on average) dealing with workslop -- decoding half-baked ideas, correcting missing details, and reworking content that isn't actually useful. Worse, the burden doesn't just stay with the person who generated the workslop: managers and peers get dragged in, creating a ripple effect across teams. Researchers tie this to cognitive offloading -- using external tools to reduce mental effort. But with workslop, that burden isn't offloaded to a machine; it's offloaded onto a coworker. The phenomenon is most common among peers (40 percent of cases, according to BetterUp), though managers aren't immune: higher-ups throw down workslop to their teams about 16 percent of the time. Overall, BetterUp Labs estimates that companies with 10,000+ employees could be bleeding as much as $9 million a year in lost productivity thanks to the sheer volume of workslop -- roughly 40% of all AI-generated output in the workplace, according to the report. Beyond the financial hit, there's also a cultural cost. Employees in the study reported feeling annoyed, confused, and even offended when handed workslop, eroding trust and reliability among coworkers. While one solution to bad AI output may be to stop using these tools completely, BetterUp Labs argues the smarter path is to set clear organizational guidelines for how employees should (and shouldn't) use AI. That means defining best-case scenarios where AI adds value, and drawing firm boundaries where it doesn't align with company strategy or values. The researchers also suggest a mindset shift: AI should be treated as a collaborator, not a crutch. In other words, it's a tool to support good work -- not a shortcut to avoid doing the work in the first place.

Companies Are Being Torn Apart by AI "Workslop," Stanford Research Finds

AI is supposed to revolutionize workforce productivity, but so far that hasn't been the case. One study from MIT found that a damning 95 percent of companies that gambled on integrating the tech saw no meaningful growth in revenue. Another study exploring one of its most hyped up applications, AI coding assistants, showed that programmers actually became slower when they depended on the AI tools. Meanwhile, a slew of reports tell an increasingly familiar tale of companies firing their workers to replace them with AI, only to scramble to rehire humans once they realize the tech isn't all it was made out to be. But why exactly is AI falling short in the workplace? In theory, shouldn't a tool that can generate essays on the fly, spit out code, hold down a conversation on any topic, and take notes on your behalf be amazing for the economy? A fascinating new report from researchers at Stanford and the firm BetterUp Labs explores that question. In a survey that's still ongoing, the team examined the responses of 1,150 full-time employees in the US across multiple industries to tease out how AI content is used in the workplace and how it affects the dynamics between employees. Their conclusion? People are using it to churn out busywork that needs to be fixed by a human with common sense, undercutting claims that it can boost productivity in the labor force. "Employees are using AI tools to create low-effort, passable looking work that ends up creating more work for their coworkers," wrote Kate Niederhoffer, a social psychologist and vice president of BetterUp, in a writeup for Harvard Business Review with her colleagues. The team calls this low quality work "workslop," in a play on "AI slop," the slang used for describing the shoddy AI text and imagery that pollute social media. They define "workslop" as AI-generated work that "masquerades as good work, but lacks the substance to meaningfully advance a given task." Sure, some employees can use AI to produce polished work. But many simply hit "enter" on their prompt and pass along whatever messy output an AI spits out -- because, on a very surface level, it does seem passable. "The insidious effect of workslop is that it shifts the burden of the work downstream, requiring the receiver to interpret, correct, or redo the work," the team wrote. "In other words, it transfers the effort from creator to receiver." It's an evolution of "cognitive offloading," the term that psychologists use to describe outsourcing your thinking to a piece of technology, be it a calculator or a search engine. AI content, however, "uses machines to offload cognitive work to another human being," Niederhoffer and her team argue. According to the survey, 40 percent of employees say they've received workslop in the past month, with just over 15 percent of all the content they receive at work being AI-generated. Most of this, 40 percent, is from their peers -- but 16 percent of the time it comes from up the chain of command. Wherever it's originating from, the very presence of AI content creates a testy workplace dynamic, because "when coworkers receive workslop, they are often required to take on the burden of decoding the content, inferring missed or false context," the authors wrote. "It created a situation where I had to decide whether I would rewrite it myself, make him rewrite it, or just call it good enough," explained one survey respondent who works in finance. "I had to waste more time following up on the information and checking it with my own research," recalled another respondent who is a director in retail. "I then had to waste even more time setting up meetings with other supervisors to address the issue. Then I continued to waste my own time having to redo the work myself." The survey results also found that employees who received workslop made them think less of the colleague who sent it. In numbers, 54 percent of respondents said they viewed their AI-using colleague as less creative, 42 percent said they viewed them as less trustworthy, and 37 percent said they viewed them as less intelligent. "The most alarming cost may be interpersonal," Niederhoffer and her team wrote. Even if there are some limited applications where careful AI usage could boost productivity or polish without affecting quality, this nuance is at odds with how breathlessly and rapidly many business leaders are adopting the tech -- not to mention the deafening buzz coming out of the AI industry itself.

An anti-workslop workshop to save your employees from AI-created chaos and time wasting | Fortune

Research scientists have just issued a warning, of sorts, about a stealthy new threat to productivity across corporate America: Employees are creating and sharing time-wasting and reckless "workslop." The official description of workslop, per researchers from Stanford's Social Media Lab and BetterUp, an online coaching platform, is "AI-generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task." But, let's be honest, most office workers won't need a definition. We've all encountered examples of workslop in the wild. It's the memo jammed with stuffy words like "underscore" and "commendable" that leaves you scratching your head, or the report littered with em-dashes that, upon a close read, feels hollow. It's one thing to get a clumsy AI-created marketing email or solicitation from a vendor; it's another to get one from your colleague or boss. We used to complain about meetings that could have been an email; now we receive confusing workslop emails that require meetings to be decoded. Managers who shared workslop horror stories with the Stanford and BetterUp team also described redoing a direct report's project or sending it back for heavy revisions. So while companies may be spending hundreds of millions on AI software to create efficiencies and boost productivity, and encouraging employees to use it liberally, they may also be injecting friction into their operations. After surveying full-time employees at 1,150 companies, the researchers found that workslop is flowing in all directions inside firms. Mostly it spreads laterally between peers, but managers are also sending slop to their reports, and employees are filing it to their bosses. In total, 40% of respondents said they had received a specimen they'd define as workslop in the past month from a colleague. Does this mean companies should cut back on AI? Probably not. In a competitive marketplace, it's hard to ignore a technology that even the study authors say "can positively transform some aspects of work." What companies can do, however, is set up guardrails. They may even consider building an anti-workslop workshop for employees. Here's what it might include: By the way, you'd better schedule your anti-workslop workshop soon. The researchers say that "lazy" AI-generated work is not only slowing people down, it's also leading to employees losing respect for each other. After receiving workslop, staffers said they saw the peers behind it as less creative and less trustworthy.

AI-Generated Workslop Is a $9 Million Productivity Problem, Say Stanford Researchers

A new research report has coined a new term for inadequate AI-generated content at work: workslop. The word refers to content that looks polished but lacks substance. It applies to AI-generated slideshows, lengthy reports, summaries, and code. While the content looks good on the surface, it ends up being incomplete, missing context, or unhelpful to the task at hand. And a new study released on Monday found that 40% of workers have reported receiving workslop in just the past month. "Rather than saving time, it leaves colleagues to do the real thinking and clean-up," the report reads. Related: 37% of Employers Would Rather Hire a Robot or AI Than a Recent Grad: 'Theory Alone Is No Longer Enough' To write the study, Stanford Social Media Lab researchers partnered with AI coaching platform BetterUp to conduct an online survey of 1,150 full-time U.S. desk workers this month. Employees who reported encountering workslop said that it caused them to take extra time and mental energy from their day to figure out how to appropriately address the work with the colleagues who had submitted it. Over half (53%) of respondents were "annoyed" to receive AI-generated work, and 22% were "offended." Close to half said they thought of their co-workers as "less creative and reliable" after they submitted the workslop. It also took an average of two hours to resolve each incident, making the invisible tax of workslop about $186 per month, based on the salaries the workers reported receiving. That means that the average annual cost of workslop for a 10,000-person organization is about $9 million per year, the study found. Related: Employers Say They Want to Hire Candidates With AI Skills, But Employees Are Still Sneaking AI Tool Use in the Office The difference between workslop and sloppy work is that workslop doesn't require any effort to create, while sloppy work still requires a little bit of effort, Stanford Professor of Communication and one of the authors of the study, Jeff Hancock, told CNBC. "Now that [the effort] piece is gone, I can generate a lot of useless or unproductive content very easily," Hancock told the outlet. Hancock recommended that business leaders give guidance to employees about when and how to appropriately use AI at work. Workers should be clear about when they're using AI, so colleagues aren't surprised by it, he said. Related: Almost 100% of Gen Zers Surveyed Admitted to Using AI Tools at Work. Here's Why They Say It Is a 'Catalyst' for Their Careers. Another study author and Vice President of BetterUp Labs, Kate Neiderhoffer, told CNBC that managers should give workers specific reasons for why they should use AI to complete certain tasks. They should offer clarity about the policies and training that go along with using AI, she added. AI can provide "incredible" use cases, Neiderhoffer told the outlet, but not when used in a "copy-and-paste mode" where you "just let the tool do all the work for you."