One of the mantras most repeated by the apostles of AI automation is that AI-assisted work was going to boost productivity in companies that apply it, but the data shows that the reality is very different and depends on How is that productivity measured?.
For example, the study data ‘Forrester Consulting’s Total Economic Impact 2023′ from IBM, highlight an increase in productivity based on a 30% reduction in the time it takes to manage an incident, but it does not measure the quality of that management. It is at that point where AI, more than boosting productivity, is sinking her.
The effect “Workslop“. As and how do they count in Harvard Business Reviewin many companies, the mass adoption of AI tools translates into enthusiasm and apparent advances, but behind these figures lies an increasingly evident problem: the proliferation of mediocre content generated by AI, known as “workslop” or work garbage. The phenomenon occurs mainly when AI is used to produce documents, reports and materials that are very apparent at first glance, but are superficial at their core and end up generating more work in reviewing and correcting them than it would have taken a person to do it from the beginning.
A recent study conducted by BetterUp Labs together with Stanford Social Media Lab reveals that 40% of US employees reported having received content “workslop” in the last month. Data indicates that 15.4% of all the content they received at work falls into this “Workslop” category. BetterUp Labs estimates put the cost of reviewing AI-generated work at $186 per employee, or about $9 million per year for a large corporation with 10,000 employees.
It is useful to get rid of “paperwork”. AI is proving useful in routine tasks, such as email automation, simple summaries or basic content generation, allowing the employee release cognitive load. That is, freeing your brain from work that, although necessary, does not really represent progress in tasks or projects. The report GenAI Divide (MIT, 2025) confirms that 70% of employees prefer to use AI to compose quick communications and perform simple analyses, noting that “AI has already won the battle of easy work.”
However, for complex projects and jobs that require memory, continuous adaptation and deeper analysis, 90% still prefer to turn to human professionals. The investigations from Carnegie Mellon University (CMU) and Duke University point out that AI can serve as a starting point for developing an idea, but it fails in 70% of the cases in which tasks are asked to complete unattended.
The invisible “tax” of AI. Every time an employee receives AI-generated workslop content, the process requires an additional investment of time and resources to unravel and correct any errors or inaccuracies that come with it.
The aforementioned BetterUp Labs study estimates that each employee wastes an average of one hour and 56 minutes analyzing or reviewing this “junk” content. So much so that it has even given rise to the birth of a new professional niche in which professionals who previously carried out that work now charge for analyzing it and fix your mistakes.
The biases of AI. The study also analyzes the social and labor impact of this type of content. His conclusion: it is as harmful as the economic impact. 53% of employees say they feel upset after receiving these texts and 38% say they are confused. According to published Forbes, approximately half of those surveyed consider their colleagues who submit workslop work to be less creative, less capable. Furthermore, 42% say they see them as less trustworthy, generating a deterioration in reputation and collaboration within the team.
This social impact does not have its origin in the fact of using AI to generate documents, code or graphics, but in the fact of not having taken the trouble to check if the content generated by AI is correct before sending or using it in his work.
Use AI with common sense. Researchers at MIT and BetterUp Labs agree that using AI indiscriminately, only following the mandate to adopt the technology, like some big technologies they want to do at all costsis not a good idea to increase productivity.
According what was published by CIOdespite the fact that the CEO of Google beats his chest assuring that 25% of your code It is already generated with AI, that work is not free nor does it result in notable improvements in productivity of its engineers. Before they were dedicated to generating code, and now they use that time to review it or repair the errors produced by the new integrated code. Therefore, using AI on complex tasks that must then be supervised by engineers does not improve productivity, but rather displaces it at best and even can reduce it depending on the use case.
Image | Unsplash (Sigmund)
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