AI-generated 'workslop' is here. It's killing teamwork and causing a multimillion dollar productivity problem, researchers say

New research identifies 'workslop,' AI-generated content lacking substance, as a significant and costly drag on corporate productivity and trust. A recent survey indicates 40% of workers received workslop in the past month, with recipients spending nearly two hours addressing its aftermath, translating to an estimated $9 million annual productivity loss for a 10,000-person organization. This phenomenon, particularly prevalent in professional services and technology, undermines the anticipated ROI of AI adoption and necessitates structured organizational approaches, clear guidelines, and transparency to mitigate its financial and interpersonal impact.

Analysis

New research from BetterUp and Stanford has identified "workslop"—AI-generated content that lacks substance—as a material drag on corporate productivity and a key factor explaining the lack of measurable return on investment from AI technologies. According to a survey of 1,150 U.S. workers, 40% have encountered such content in the last month, with an estimated 15% of all received work qualifying as low-quality AI output. The financial impact is significant; employees report spending nearly two hours per incident addressing the issue, which researchers calculate as a $9 million annual productivity loss for a 10,000-person organization. This finding provides a potential explanation for a recent MIT report noting that 95% of organizations see no measurable ROI from their AI investments, despite a doubling in AI adoption at work since 2023. The phenomenon is most pronounced in the professional services and technology sectors and carries hidden costs beyond financials, including eroded team trust and a decline in perceived colleague capability. The research suggests that mitigating this productivity tax requires a structured organizational approach, including clear governance, training, and transparent communication regarding AI usage, shifting the focus from mere adoption to effective, quality-controlled implementation.

Key Decisions for Investors

• Investors should intensify due diligence on portfolio companies' AI implementation strategies, scrutinizing governance, quality control protocols, and employee training programs rather than just the headline investment in technology.
• When evaluating companies, particularly in the technology and professional services sectors, consider the risk of this productivity drag as a potential headwind to margin expansion and operational efficiency.
• Favor companies that can articulate a clear framework for measuring the net productivity impact of AI, demonstrating a focus on augmenting human capabilities and maintaining quality standards, as they are better positioned to achieve a tangible return on their AI investments.
• Monitor human capital metrics and management commentary on corporate culture, as the erosion of trust and collaboration resulting from 'workslop' represents a significant, though intangible, risk to long-term value creation.