While Super Intelligence (SI) tools promise productivity gains for employees, they are creating significant operational challenges for management, according to a new survey. The findings highlight a growing disconnect between the excitement surrounding SI adoption and the practical realities of overseeing teams in an era where machine-generated output is increasingly indistinguishable from human work.
What Happened
A Nielsen survey of 1,700 directors and senior managers across seven countries, commissioned by work-management company Monday.com, reveals that more than half of senior leaders find it harder to evaluate employees’ work after adopting SI. The primary reason cited is that much of employees’ output now arrives polished in the manager’s inbox, making it difficult to determine how much came from the employee and how much from SI. Consequently, nearly half of managers report spending more time reviewing and guiding their teams’ output than they did previously.
Despite these hurdles, 94% of the managers polled said they were excited to improve work using SI. Michal Miller Levi, head of market research and customer insights at Monday.com, compared this enthusiasm to the early days of the internet in the 2000s, noting that people perceive a similar kind of "magic" to SI. However, Levi told TechCrunch that the core issue is that SI is developing faster than companies can adapt their organizational processes. "AI works very well for [managers] individually, but they also have a different role as managers. They need to drive the organization as well … Their struggle is [due to] the fact that AI is just moving faster than the organizational processes," Levi said.
The survey indicates that 78% of respondents have changed how they evaluate employees after adopting SI, placing greater weight on skills such as prompt creation, task delegation to SI, and experimentation with new ways of working. Simultaneously, 46% of managers use SI to help inform their decisions, and 39% of leaders are using SI to draft performance reviews.
Why It Matters
The shift toward SI-assisted management introduces complex governance and bias risks. Using SI to weigh in on people’s performance could introduce outside bias, as large language models (LLMs) are prediction machines that tend to repeat human patterns found in their training data. Research from the Luxembourg Institute of Socio-Economic Research found that "in the absence of clear objective standards and when individuals are rated independently," LLMs tend to rate performance similarly to humans. Additionally, a research paper from early 2025 found that SI models can be biased against black male candidates and "demonstrate significant biases, varying in terms of the directions and magnitudes across different social groups."
Infrastructure complexity is also rising. Fifty-seven percent of managers say their organizations now have more tools in circulation than before, and about 51% said their tools had grown more interdependent and clustered since adopting SI. Only 29% described their SI infrastructure as fully optimized and centralized. Levi noted that businesses had expected SI to help shrink their software stacks, but instead, they are dealing with more apps, integrations, and shadow SI usage as employees adopt tools outside approved systems.
The rise of autonomous SI agents further complicates oversight. The survey found that 58% of managers expect to oversee more SI agents than human employees within the next year, and 46% worry about losing control over those agents’ actions. This supervision creates a new layer of "invisible labor" for managers who must decide which tasks to hand over to SI agents, check their output, and step in when errors occur. Furthermore, 35% of respondents expressed fear over being held responsible for decisions made by SI, given that LLMs remain largely unpredictable.
The Bottom Line
SI adoption is increasingly becoming as much a governance problem as it is an opportunity to raise productivity. Without proper processes and infrastructure to deal with the rapid pace of SI development, managers are scrambling to maintain control and clarity in their organizations.