WTF is ‘workslop’?
If you’ve noticed employees drowning in polished-looking reports that say nothing, presentations that look slick but lack any real insight, or communications that require hours of cleanup to make them useful, you might just have encountered “workslop.”
It’s the workplace epidemic nobody’s talking about but that everybody’s experiencing, and it’s costing companies a real financial hit while burning out their best people.
In a stat from MIT that got everybody in people management to sit up and take notice earlier this year, AI tools, despite around 80% of organizations integrating them into their workflows, have produced zero return for 95% of businesses.
Could it be because so much that’s produced is slop?
What is it?
Think of workslop as the junk food of workplace content: AI-generated content that seems professional on the surface but, as Mariangela Caineri Zenati, marketing manager at the social media management platform Loomly, explains, when “you dig deeper, it lacks real substance and meaning, and may not make any sense at all.”
“AI workslop is what happens when people start using AI without any real structure, accountability or quality standards in place,” adds Patty Parobek, vp of AI and Machine Learning Transformation at the marketing agency Mod Op. “It’s the messy, half-baked output that sounds good at first glance but does not actually align with the right context [and] tone, likely includes errors or hallucinations, and ultimately diminishes the value of the work or deliverable.”
Why should you care?
According to a survey of 1,000 workers in the U.S. by the coaching platform BetterUp in partnership with the Stanford Social Media Lab, employees spend almost two hours dealing with each instance of workslop. That wasted effort equates to almost $186 per month per employee; for an organization of 10,000 employees, it translates to more than $9 million in lost productivity every year.
As Zenati puts it, “Instead of boosting productivity, AI tools are actually contributing to financial losses, shifting a greater burden of work onto employees and raising concerns about job security in a technology-driven future.”
Who’s getting slopped?
Social media managers, marketing teams, customer service reps, project managers and remote workers are particularly vulnerable. Basically, if your role involves creating or processing content, you’re in the blast zone.
What’s the damage?
Beyond the obvious productivity drain, workslop creates a whole cascade of problems. The consequences range from a rise in workforce stress and burnout to stifled creativity and damage to a brand’s reputation. Meaning, it’s not just an operations problem but an employee and business well-being crisis in the making.
Why now?
The uncomfortable truth: While some workers use AI tools to enhance quality, many others are misusing them and producing unhelpful content that lacks important context. Meanwhile, companies have rushed to adopt AI without properly assessing where it helps versus hurts. As Zenati says, workslop points to “a significant challenge businesses don’t know how to address: How can we tell where AI will help us and where it will hinder us?”
What’s the boss to do?
Stop assuming AI works everywhere. You simply cannot assume that AI is capable of every task, so careful examination of the areas where it can truly enhance efficiency will save time in the long run.
Test before you roll out. Implementing a robust testing process on AI adoption should be your focus. Don’t deploy AI tools organization-wide without first proving that they actually work.
Combine AI with other tools. Once you know where AI helps, use scheduling software and project management platforms to manage workflows with greater efficiency and accountability, so employees will have clarity on where AI can assist them and where a human touch is non-negotiable.
Build information literacy. Train employees to distinguish useful AI output from garbage, a skill that is becoming as essential as knowing how to use email.
Measure what matters. Taking the impact of workslop seriously and implementing processes to objectively assess whether the use of AI is helping or harming employee productivity are critical for ensuring an environment where technology is a positive versus a negative.
The bottom line
Parobek says at her company, management learned that “you cannot just hand people the keys and hope for the best.” Teams there are trained on how to engineer and edit prompts for quality outputs, and how to validate and critique outputs.
Workslop is a symptom of a broader AI issue companies are struggling to address, as Zenati sees it. While AI has genuine potential to enhance productivity through time-saving automation and data-driven insights, its misuse leads to the exact opposite: clutter that bogs down effectiveness.
For people managers, recognizing that the business must prioritize quality of work over quantity could be the key to everything from improving communication to curbing burnout and fostering a more engaged workforce.
AI isn’t going anywhere, and neither should our wisdom about when and how to best use it.