An overwhelming majority (85%) of respondents agreed that their organization's executive leadership is more enthusiastic about AI than its employees are. That is a significant gap between the people setting AI strategy and the people expected to execute it every day, and it has real consequences for how quickly and efficiently AI scales across the enterprise.
Enthusiasm without AI alignment
Respondents, who are uniformly senior leaders, were asked which of two hypothetical leaders they most identified with:
- Smith, who is "all-in" on AI, using it to automate and streamline work while shifting human effort to higher-value skills
- Jones, who is more cautious, emphasizing people investment and expressing skepticism about heavy AI deployment
By a 2-1 margin, respondents preferred Smith, with 61% identifying with the all-in leader. Just 30% identified with Jones.
Leaders see AI’s potential, are tracking the competitive landscape and want to move forward. But enthusiasm at the top does not automatically translate into adoption on the ground.
For employees, the gap is felt differently. Many remain uncertain about how AI will affect their day-to-day responsibilities, job security and long-term career paths. Without clarity on those questions, organizations encounter resistance or underutilization of AI tools, even when leadership commitment is high.
"Workers are being asked to reenvision new roles. So there has to be a lot of empowerment training, a lot of answering 'What's in it for me?'" says John Huyette, AI risk leader for RSM US.
AI workforce disruption is expected. AI readiness is not.
The majority of respondents (88%) either completely or somewhat agreed that their workforce size and composition will look fundamentally different in the next two to three years because of AI. And 91% agreed that humans and AI systems will work together as integrated teams within the same time frame, with 54% completely agreeing and 37% somewhat agreeing.
Those numbers reflect a leadership consensus that AI is not just a productivity layer. It is a structural force that will reshape job responsibilities, required skill sets and potentially the organization itself. Routine and administrative tasks will continue to be automated, while employees are likely to spend more time on judgment-based, creative and relationship-driven work.
"As a society, we still need human relationships, and we need validation from other people," says Diego Rosenfeld, a principal at RSM US. "It's easy to get answers from AI. But humans have to be centered on the solution, more than we ever have before."
The transition represents an enormous opportunity for middle market firms—one that will demand significant investment in reskilling, particularly for middle management and knowledge-worker roles that workflow automation most often affects.
The Canadian perspective
Most Canadian respondents (52%) said their organization will invest less than $1 million on AI in the current fiscal year. Canadian respondents were also significantly less likely than U.S. respondents to report that they expect their organization’s AI spending to increase in the next fiscal year (69% vs. 87%).
But employees need more than reassurance that AI will not replace them. They need a credible vision of how their roles will evolve, what new skills will be valued and where the opportunities are.
Change works only if the people responsible for execution believe in it, understand it and are equipped to carry it out.
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