AI tools have long promised to free up employees’ time by automating routine communications. Yet, growing evidence suggests they are doing the opposite – flooding inboxes and communication platforms with machine-generated noise that nobody trusts, few people read, and everyone pretends to engage with.
Across the modern enterprise, a familiar scene is playing out. Monday morning arrives, and with it a cascade of AI-generated strategy updates, alignment memos, and meeting summaries packed with em-dashes and questionable emoji choices. The tools responsible for generating them were sold and bought on the promise of efficiency. However, the end result of this increased communication is a workforce that has quietly learned to tune most of it out.
Organizations have rushed to adopt generative tools in their workflows. Yet, the long-term consequences for productivity, employee engagement, and organizational trust are only beginning to be understood.
What is “Workslop” – and How Did it Take Over the Office?
“Workslop” is a term now used to describe a specific, and increasingly familiar, breed of workplace content: AI-generated material that looks professional at a glance but, on closer reading, says very little. Anyone who has spent time on LinkedIn recently will recognize it on sight, and their eyes will likely glaze over beyond the first em-dash.
In theory, AI frees people from busywork. In practice, it often converts busywork into an elegant PDF with a slightly haunted executive summary.
The scale of the phenomenon is significant. According to research cited by The Independent, 40% of U.S. workers report receiving workslop from a colleague in the past month. The question emerging is what sort of long-term impact this overload of internal communication will have on a workforce that, surprisingly enough, prefers to read something written by a human.
IS AI Actually Saving Employees Time?
The productivity case for AI in enterprise communication rests on a simple premise: lower production costs, take away ‘busywork’, and employees will reinvest the time saved in higher-value work.
This theory isn’t holding up…
A survey of 5,000 white-collar workers by AI consulting firm Section found that the average employee is not saving time with AI and is instead overwhelmed by the task of finding use cases for generative technologies.
A separate WalkMe study found that whilst 80% of employees believe AI improves productivity, nearly 60% admit it often takes longer to figure out how to use the AI than it would to just do the task manually.
Nick Renner, Skills Intelligence Partner at BPP, commented on the phenomenon:
“When an hour is saved producing a first draft, but 40 minutes is then spent verifying, correcting, or rewriting it… is time genuinely being saved, or is the constraint just moving downstream?”
The assumption that AI will always increase productivity and free people from repetitive administrative tasks is based on flawed logic. As Forbes observed, most organizations simply do not have sufficient volumes of high-value strategic work lying in reserve. Furthermore, verifying and amending AI-generated outputs may take longer than performing the task manually, particularly in content creation.
What Is AI Overdrive Syndrome – and Should Leaders Take It Seriously?
Researchers at The Open University Business School have coined the term ‘AI Overdrive Syndrome’ (AIOS). Defined as “the state of mental, physical, or emotional exhaustion arising from the excessive use or relentless pursuit of productivity facilitated by artificial intelligence tools,” AIOS captures the cognitive toll of an always-on, always-generating workplace.
AI tools provide “a seemingly infinite reservoir of insights, suggestions, and solutions.” The machine generates; the human processes. But human processing capacity is finite. Microsoft’s Work Trend Index has already documented how digital collaboration erodes traditional work-life boundaries. AI amplifies this dynamic by making continuous productivity appear not just possible but implicitly expected.
Furthermore, 32% of employees are now reporting “AI burnout” – mental fatigue directly linked to engaging with and checking AI output, presenting a significant employee engagement issue as enterprises undertake AI rollouts.
Why Don’t Employees Engage with AI-Generated Internal Communications?
Trust is the invisible infrastructure of internal communication. Without it, even well-crafted messages fail. AI-generated communications may be eroding that infrastructure, quietly undermining the very structures organizations depend on.
With 74% of workers confident they can spot AI-generated content and 49% reporting encountering it at least weekly, the question is no longer whether employees can spot it – it’s whether they’ll engage with it at all. A good internal message should feel like someone had a thought. Too often, AI makes it feel like someone had a subscription.
Research in this area remains limited, but the underlying dynamic isn’t hard to read. When employees receive a message that feels machine-produced, many interpret it as a signal: this wasn’t worth the sender’s time.
After all, if it wasn’t worth their time to write, why should it be worth yours to read?
Brand strategist Rosie Wilkins outlined her frustrations in The Independent:
“You didn’t write this, you definitely haven’t read it back, and it’s taking me longer and longer to make revisions and changes.”
Who Should Control How AI Is Used in Workplace Communication?
The governance question is one that the enterprise technology sector has been slow to confront. AI communication tools have been rolled out predominantly from the top down – selected and implemented by executive teams, with limited input from the people who experience their consequences daily.
AI technologies undoubtedly offer significant productivity gains for many enterprises. Yet, the human impact is more complicated…
One in five workers says AI has made their job worse – precisely matching the proportion who say it has improved things. Furthermore, a 2024 academic study found no credible evidence that AI tools reduce employee burnout, with participants instead reporting feeling more closely monitored and less able to exercise creativity.
For enterprise technology buyers and IT leaders, these are real retention and performance risks with significant financial implications.
The Case for Human-Led, AI-Assisted Communication
The answer is not to abandon AI communication tools. It is to use them with the kind of intention that, at present, most organizations are not applying. AI is genuinely useful as an editorial aid – it can accelerate first drafts, improve consistency, and remove blank-page paralysis. What it cannot do is supply the authorial voice, the editorial judgment, or the human accountability that make internal communications worth reading.
As Bonnie Moss, President of Moss Networks, observes:
“While AI might make things look and sound pretty, you’ll lose the unique value you bring if you give it too much ownership over your content and strategy.”
In the age of AI, the communicators who thrive in this environment will be those who lean into the distinctly human skills AI cannot replicate – presence, persuasion, trust-building, and the ability to connect people to organizational purpose.
The inbox is already full. The challenge for enterprise leaders is to make the next message worth opening.
FAQs
What is “workslop”?
“Workslop” refers to AI-generated workplace content that appears polished on the surface but is hollow in substance – identifiable by its generic tone, excessive bullet points, and absence of genuine human voice.
Is AI actually improving workplace productivity?
For most workers, the evidence is mixed at best: surveys show that time saved on generation is largely offset by time spent verifying and correcting AI output, with 66% of workers reporting that AI does not help them work faster.
What is AI Overdrive Syndrome?
Coined by The Open University Business School, AIOS describes the mental and physical exhaustion caused by the relentless pace of AI-enabled productivity, where the machine’s infinite output capacity exceeds what employees can meaningfully process.
Why don’t employees trust AI-generated internal communications?
Employees increasingly recognize AI-generated content and interpret it as a signal that the sender didn’t consider the message worth their own time – eroding the trust that effective internal communication depends on.
How should organizations use AI in internal communications?
AI is most effective as an editorial aid rather than as a wholesale replacement for human voice, judgment, and accountability.
What are the risks of unchecked AI communication tools in the enterprise?
The risks include employee disengagement, communication overload, declining trust in leadership, burnout among communications professionals, and productivity loss from time spent reviewing unreliable AI output.
