A unique survey of 105 bosses, managers, and senior leaders reveals the gap between AI optimism and organizational reality, and how leaders can close it.
Remesh, an AI-powered conversational research platform built to understand humans at scale, today announced exclusive research examining how AI is reshaping organizational culture across industries. The survey of 105 supervisors, managers, and senior leaders using the Remesh platform revealed that employees are overcoming a wide range of perception gaps. Three-quarters of organizations report expanding or widespread adoption of AI, but less than half have clear policies in place to guide it.
AI is shifting expectations from quantity to value. We are now expected to spend less time on repetitive execution and more time on creative problem solving. ”
— Research Participant, Remesh AI and Organizational Culture Report
This report, Exploring the Impact of AI on Organizational Culture, was produced in collaboration with Dr. Patrick Hyland, director of workforce research at Remesh, and Dr. Elissa Gurman, principal at MacPhie.
“AI is shifting expectations from quantity to value. We are now expected to spend more time on creative problem solving rather than repetitive execution.”
— Research Participant, Remesh AI and Organizational Culture Report
Adoption is accelerating, but governance is not keeping up
Three-quarters of leaders surveyed report that AI adoption in their organizations is increasing (62%) or pervasive (13%). Manufacturing and healthcare lead with near-universal adoption rates, while education and research together report the lowest adoption rates at 46%. Despite this momentum, 56% of respondents operate with inconsistent, unofficial, or non-existent AI guidance.
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Governance gaps have tangible effects. Organizations with clear and well-communicated AI policies are six times more likely to describe the cultural impact of AI as “very positive” compared to those with little or no guidance (41% vs. 8%). For leaders managing AI transformation, data is immediate. How well you manage AI is more important than how quickly you deploy it.
Leaders seize the opportunity, employees feel the pressure
While 74% of leaders say the cultural impact of AI is positive, the picture beneath that heading is more complex. Employees’ top concern was turnover (37% of open-ended comments), followed by data privacy and security (24%) and concerns about inaccurate AI output (21%). Middle managers, caught between the executive mission and the realities on the ground, are the most likely to report having mixed emotions at 36%.
The study found that when employees are afraid to move, open AI adoption stalls and the efficiency gains organizations are hoping for are hampered. The distinction between AI as a support and AI as a threat is not determined by the technology itself. It depends on how leadership communicates, trains, and governs.
What leaders need most: Training, policy, and transparency.
When asked what would best improve the employee experience during AI integration, leaders identified clear priorities. They were AI training and education (50%), clear usage policies (30%), and transparent communication from senior leaders (18%). These are not technical requirements. These are people and culture demands that point to fundamental change management challenges for successful AI transformation.
Applying the SCARF framework: Understand when AI helps and when it hurts.
This report applies neuroscience research from David Rock’s SCARF model (Status, Certainty, Autonomy, Relatedness, and Fairness) to explain why the same AI tools can feel empowering to some employees and threatening to others. This finding provides an accurate diagnosis. Benefits are realized when AI increases speed, information, and human empowerment. When pressure to perform, ambiguity, or a sense of displacement arises, it becomes a threat.
The report concludes that this change is driven solely by leadership actions, not by technology itself.
“Leaders need to be upfront with people that AI is not a replacement for their positions. We are not training AI to take their jobs; we are using AI to make their jobs easier and more efficient.”
— Research Participant, Remesh AI and Organizational Culture Report
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