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.
