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The primary perceived benefit of AI: increased productivity. And indeed, our research found that 79% of leaders are excited about AI's potential to dramatically improve their team's productivity, seeing AI as a lever to augment their teams' capabilities, accelerate decision-making, and free their people to focus on higher-value work. Yet for all this enthusiasm about productivity gains, a crucial question remains unaddressed. In the rush to embrace AI’s speed and scale, are leaders inadvertently training their teams to prioritize volume over value?
Leaders now face a new challenge: "workslop"—AI-generated content that threatens to undermine the very gains executives hope AI will deliver. ‘Workslop’ is broadly defined as AI-generated content that masquerades as good work but lacks the substance to meaningfully advance a given task. This phenomenon is manifesting across every level of organizations—from the C-suite to the front lines. It's the strategy deck with impressive sounding but ultimately hollow recommendations. It's the market analysis that reads well but misses crucial nuances. It's the email that says everything and nothing at once.
This isn't just a theoretical concern for leadership teams. Research published in Harvard Business Review found that employees spend an average of one hour and 56 minutes dealing with each instance of workslop. When scaled across a large organization, this "workslop tax" translates to more than $9 million per year in lost productivity for a company of 10,000 workers, HBR estimated.
For leaders who are AI skeptics, this data might seem to validate their concerns. They're looking for reasons why AI adoption will prove more problematic than useful.
But the problem isn't AI itself. When used for the right reasons, by the right people, in the right way, we know that AI can add tremendous value to organizations. The emergence of ‘workslop’ shouldn't halt AI adoption—it should refine it. AI isn't appropriate for all tasks all of the time. While it can be transformative, it still requires thoughtful human guidance to produce useful outputs for complex or ambiguous work.
So, how do CEOs and C-suite executives balance the implementation of AI across their organization while minimizing instances of ‘workslop’ in their teams and broader organizations? The answer begins with a fundamental question: Do you have the right leaders for an AI-prevalent world?
Here, we share three key qualities you need to look for in your leaders to avoid ‘workslop’.
In an era where everyone can produce content and can appear to be an expert, the ability to distinguish genuine expertise from AI-augmented mediocrity becomes paramount. Our H1 Global Leadership Monitor research found that 54% of leaders are concerned about individuals failing to develop critical thinking skills and judgment due to over-reliance on AI. This concern is well-founded.
As Brad Smith, Microsoft's Vice Chair and President, shared during Redefiners when discussing AI: "None of this should ever be used as a tool to encourage people to stop thinking. It is a tool to help people think better. And I appreciate it when people expect a machine to yield an answer that's 100% accurate, but if you walk out of your office building and you ask the first person you meet for directions to go somewhere, then you're going to ask yourself, okay, that sounds good, but is it right? I know something about this neighborhood. In the same way, always ask yourself, does this make sense? How do I use it? How do I make it better?"
The leaders that organizations need to thrive today are those who question AI outputs, who recognize what good looks like, and who can spot when seemingly impressive content lacks substance. They understand that AI is a tool, not an oracle. As one CEO attending our recent CEO AI Labs in APAC commented, "We need to be asking, 'Do we have people who can ask the right questions, interpret the results, and then ask the obvious next question and drive that dialogue forward iteratively?'"
The skills that make someone effective at building connections and orchestrating strong working relationships with humans translate directly to working with AI tools. These leaders know how to provide proper feedback, refine outputs, and engage in iterative improvement—with both team members and algorithms. They understand that AI collaboration—like human collaboration—requires patience, clarity, and the ability to guide better outcomes.
Making the right judgment call is becoming increasingly important in an AI-saturated environment. Is this work good enough? Does it meet our standards? Does it advance our objectives? It’s the role of the leader to craft the output, put it into context, and ensure that it drives valuable outcomes. Leaders who can make these determinations prevent ‘workslop’ from infiltrating an organization's bloodstream.
Beyond hiring and developing the right leaders, executives must create the right leadership environments to minimize ‘workslop’. This requires more than good intentions—it demands structured intervention from the top.
Training becomes non-negotiable. Every leader will need to understand not just how to prompt AI tools, but how to provide feedback that refines outputs, how to recognize when AI is the wrong tool for the task, and how to blend AI capabilities with human insight. The focus here shouldn’t be technical training; it's about developing new leadership skills. As one CEO participant in our CEO AI Labs noted, "You need to understand how to think differently—and carry thousands of people on the learning journey."
This represents a fundamental challenge. Organizations are not just asking their leaders and employees to use new tools; they’re asking them to reimagine how work gets done. It requires leaders to shift mindsets, evolve cultures, and change the way people view their own value in an AI-augmented workplace.
Equally important is how leaders define and model productivity. If an organization continues to reward volume over value, if it celebrates those who produce the most rather than those who produce the best, then we’ll all drown in the ‘workslop’. CEOs must explicitly model quality over quantity, reward critical thinking and creativity over pure output, and celebrate instances where team members choose not to use AI because human insight was more valuable.
What the ‘workslop’ phenomenon reveals is the need for more intentional leadership in how organizations integrate AI. Organizations that successfully navigate this challenge won't be those that resist AI or those that embrace it uncritically. Success will come to those with leaders who approach AI with clear eyes and strong values.
This means understanding that AI amplifies both capabilities and shortcomings. If your organization lacks critical thinking, AI will accelerate shallow work. But with the right leaders, training, and values, AI can become a powerful lever for transformation.
The workslop phenomenon serves as an early warning for leaders everywhere. It reminds us that technology without human wisdom leads nowhere good. But with the right leadership and systems, organizations can harness AI's power while maintaining the substance that drives real value.
Fawad Bajwa leads Russell Reynolds Associates’ AI, Analytics & Data Practice globally. He is based in Toronto and New York.
Amy Scissons is Russell Reynolds Associates' Chief Marketing and Communications Officer. She also co-leads the firm's AI Transformation, overseeing activation and implementation efforts from change management, onboarding, and training to the integration of AI capabilities across the organization. She is based in New York.
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