In the wake of MIT’s infamous “95% of AI projects fail” study, headlines exploded with stories of wasted billions and dashed promises. The study was methodologically shaky — interviews with just 52 execs, with “failure” defined as anything not explicitly tied to revenue growth in earnings calls — but it struck a nerve.
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Now the latest buzzword is Workslop. And unlike the MIT study, which framed AI as failing, Workslop has resonated because leaders everywhere recognize it.
BetterUp and Stanford’s Social Media Lab recently put numbers behind what many managers have suspected: AI is producing a tidal wave of polished but hollow output. Harvard Business Review warns that “AI-generated Workslop is destroying productivity.” Fortune says it’s the “scourge of the 21st-century office.” CNBC calls it a “multi-million-dollar problem killing teamwork.”
As someone who coaches mid-sized business owners and runs PR agencies on two continents, I’ve seen this first-hand. Teams buried under slick AI-generated decks, glossy reports, and endless “summaries” that don’t move the needle. In my Strategic Business Blueprint sessions, I’ve literally calculated the cost of fake work — and it’s staggering.
But here’s the twist: Workslop isn’t an AI problem. It’s a human and organizational problem. AI is just the mirror that’s exposing it. And if you’re a leader, this is both a warning and an opportunity.
What on Earth Is “Workslop”?
BetterUp defines Workslop as “AI-generated content that looks good but lacks substance.” It creates the illusion of progress: slick slides, lengthy reports, tidy summaries, or even code without context. The kind of output that makes you nod for two minutes before you realize you’re no closer to a decision.
Their survey of 1,150 U.S. desk workers found that 40% had received Workslop in the past month. Each incident took an average of two hours to resolve. At scale, that’s $186 per employee per month — or $9 million annually for a 10,000-person company.
That’s not pocket change. That’s an entire innovation budget, gone.
Academic researchers are trying to define the phenomenon too. VrasserX pointed to work from Northeastern, Stony Brook, and Meta: slop isn’t bad grammar — it’s verbosity, vagueness, repetition, and incoherence. The fingerprints that scream “AI wrote this.”
Now, let’s be honest. Humans are guilty of those sins too. But AI’s ability to pump out infinite amounts of it at scale? That’s the dangerous multiplier.
Nick’s anecdote: A client once proudly handed me 40 AI-generated slide decks. Forty. They looked amazing. Fonts aligned, stock images on point, bullet points as smooth as butter. But not a single one advanced the project they were meant to serve. Forty decks, zero progress. That’s Workslop in its purest form.
Why This Isn’t an AI Problem
Here’s where I break from the panic headlines. The problem isn’t AI. The models are good enough to create value.
The problem is human incentives.
Too many organizations reward activity instead of outcomes. People learn fast: if success means showing you’ve been “busy,” AI is your new best friend. It will generate more slides, reports, and updates than you could in a lifetime.
But volume ≠ value.
Nick’s anecdote: I coached a marketing team where the KPI was “number of reports delivered.” Guess what happened? They discovered AI. Productivity skyrocketed — reports doubled. And yet client satisfaction dropped, because no one actually read them. Once we reoriented around outcomes (“did this lead to client decisions or revenue impact?”), the flood of Workslop dried up overnight.
The Research Spotlight
Let’s zoom in on the BetterUp study. It’s no surprise it got so much press. Forty percent of workers saying they’ve been hit with Workslop? That’s watercooler-level relatable. The $9M annual cost for a 10,000-person org? That’s boardroom-level scary.
Compare that to MIT’s “95% of AI projects fail” study. That one grabbed headlines but collapsed under scrutiny. The BetterUp numbers, even though they’re marketing-driven, resonate because they feel true to managers slogging through endless AI-generated status updates.
Nick’s anecdote: In my Strategic Business Blueprint workshops, I often run a “fake work audit.” We tally every task a team does in a week and ask: did this move us toward our stated goals? In one session, we discovered that 60% of weekly tasks were “reporting” — much of it AI-assisted — that nobody used. Multiply that across salaries, and the cost was seven figures annually.
That’s not inefficiency. That’s Workslop.
Workslop as a Mirror of Broken Incentives
Workslop thrives in environments where inputs are rewarded over outputs. “How many slides did you create?” instead of “Did we close the client?”
This misalignment creates two problems:
Fake work gets rewarded.
Necessary work gets ignored.
Chris O’Dell put it perfectly: a teacher says, “Don’t use AI, use your brain.” Students reply, “But the assignment is unnecessary — AI can do it faster.” The same dynamic plays out in offices every day. Managers hand out busywork. Employees dutifully AI-ify it. Nobody asks, “Why are we even doing this?”
Professor Ethan Malik added another dimension: managers often demand productivity gains from AI without redefining what “good” looks like. So teams churn out more PowerPoints, because that’s the proxy for progress. The result? More slop, not more strategy.
Three Root Causes of Workslop
From my perspective, Workslop boils down to three root causes:
Incentives misaligned — rewarding busyness over results.
Legacy processes — outdated rituals (status decks, weekly memos) that survive out of habit, not utility.
Lack of training/space — leaders say “use AI” but don’t give teams time, models, or examples of what “good” looks like.
If you don’t fix these, no AI strategy in the world will save you.
How Leaders Can Fight Workslop
The good news? Leaders can beat Workslop. Here’s the playbook I coach my clients on:
Shift incentives → reward outcomes, not volume.
Eliminate fake work → run audits, cut legacy tasks.
Model quality → show examples of “good vs. bad” output.
Give structured space → create time for teams to practice AI use.
Build a culture of iteration → teach teams that first drafts are raw material, not final product.
Nick’s anecdote: I run “Workslop audits” with exec teams. Half a day in a boardroom. Everyone lists their recurring tasks. Then we vote: mission-critical, supportive, or Workslop. The last category usually accounts for 30–40% of time. Cutting it frees resources instantly.
Lessons from Coders
Developers were the first to face this adaptation. Google Cloud’s study of 5,000 devs found AI boosted output and quality — but also increased code instability.
Rune from OpenAI joked: “I’ve forgotten how to program. I just beg GPT-5.” Funny, but telling. The danger isn’t AI incompetence. It’s human complacency.
Nick’s anecdote: When I coach agency leaders, I tell them to think like editors-in-chief. Let AI draft. But don’t stop there. Your job is refinement — sharpening until it’s truly fit for purpose. That mindset shift separates leaders from laggards.
My Framework for Eliminating Workslop
Here’s how I apply my Strategic Business Blueprint lens to kill Workslop:
Define outcomes clearly. Teams can’t hit fuzzy goals. Spell out what matters.
Prune fake work. Audit ruthlessly. Kill tasks that don’t serve outcomes.
Train and give space. Block calendar time for teams to practice AI use.
Build an editing culture. Celebrate refinement, not just raw output.
Nick’s anecdote: One client had a ritual of producing 30-slide weekly update decks. We cut it to a single KPI dashboard. The result: faster decisions, happier clients, and 25 reclaimed hours per week. That’s Workslop turned into efficiency.
The Future — Agents and Workslop
Will autonomous agents kill Workslop? Maybe.
If agents handle low-value tasks, Workslop could vanish. But if they churn out more polished nonsense, it could multiply. The deciding factor is leadership. Tech won’t save you if your incentives are broken.
Nick’s anecdote: I tested autonomous agents for client reporting. The result? Gorgeous, data-filled PDFs. Problem was, half the data was irrelevant. Without human oversight, they produced beautiful garbage.
Conclusion: Leading Beyond Workslop
Here’s the truth: Workslop is real, but it’s not AI’s fault. It’s ours.
Leaders who cling to outdated incentives will drown in it. Leaders who redefine outcomes, prune fake work, and coach their teams on AI use will thrive.
This isn’t about prettier slides. It’s about reclaiming productivity, purpose, and progress.
And if you’re a mid-sized business owner, this is your wake-up call. Your competitors are already asking: are we measuring activity, or are we creating impact?
That’s exactly the work I do with clients through my coaching practice, Exactly Where You Want To Be. If you’re ready to cut through Workslop and build a business that thrives in the post-AI era, let’s talk. Book a strategy session. Let’s make sure your output actually matters.
Want to talk? Lets connect.