On AI: Closing the AI Adoption ROI Gap: A Leadership Crisis
- Cori Harding
- May 19
- 3 min read
76% of executives believe their employees are enthusiastic about AI adoption. Only 31% of employees actually feel that way.
That 45-point gap is not just a survey result. It is an early warning sign of AI adoption ROI failure. And if you are in a senior leadership role, it is the most important number you are not tracking
93% of Canadian organizations are now using AI. Only 2% are seeing measurable returns.
So what is the problem? It is not the technology. It is the distance between leaders and their people.
Most employees are not resisting AI itself. They are trying to understand what it means for their value, their workload, and their future.
Why AI Adoption ROI Is a People Problem, Not a Technology Problem
The top 5% of organizations pulling measurably ahead follow a deliberate resource allocation: 10% of effort on algorithms, 20% on data and technical infrastructure, and 70% on people, process, and cultural transformation.
Most organizations invert this entirely. 70% of energy goes to tool selection and 10% goes to the human system underneath it.
That inversion is not a minor inefficiency. The data shows that organizations prioritizing employee-centricity are nearly four times more likely to reach advanced AI maturity than those relying solely on technical infrastructure. It is the single biggest statistical driver of adoption success...mattering more than your industry, your budget, or your tech stack combined.
And when organizations deploy AI to replicate what they already do, faster and at scale, they are paving the cowpath... in other words they are digitizing the status quo instead of questioning it. The result is efficiency gains stacked on top of broken assumptions, and a workforce executing against a strategy they were never part of building.
The Workforce Advantage Most Strategies Are Missing
Millennials are now the largest segment of the workforce, representing roughly 36% of the labor force. They are digitally native, systems-aware, and wired to interrogate process rather than simply execute it. In an era that rewards rethinking the business over automating it, that orientation is a structural competitive advantage.
The data on their engagement, however, should stop every senior leader cold.
From 2023 to 2024, engagement across Millennials and Gen Z fell from 40% to 35%, while active disengagement grew. Disengaged employees cost the global economy $8.8 trillion annually in lost productivity... the equivalent of 9% of global GDP.
Most people want to contribute meaningfully and do work they can feel proud of. The problem is many leadership systems were built for consistency and control, not curiosity, adaptability, and reinvention. The issue is that legacy leadership approaches, designed for a different era, do not unlock what this group is actually capable of. Add a persistent underinvestment in upskilling, and you have the generation most naturally suited to AI-era thinking operating well below their potential.
The organizations that change this will not just adopt AI better. They will use it to rethink their businesses entirely. That is the difference between measurable ROI and an expensive experiment.
Where to Focus First
Audit your resource allocation. Are you investing in leadership development at the same level you are investing in the technology? Protecting your AI adoption ROI requires following the 10/20/70 rule—it is not aspirational, it is what the top 5% are actually doing.
Map your adoption gaps honestly. Where are people working around the tools? Where has Shadow AI already filled a vacuum your formal strategy has not addressed? A follow-up article on exactly this: why your people are not adopting, and what they are not telling you, is coming soon.
The Leaders Who Close the Gap
The organizations pulling ahead are not treating AI as a technology deployment. They are treating it as a leadership transformation.
Two conversations I am having with organizations right now:
The first is about leadership. Engaging and unlocking a multi-generational workforce in the AI era requires a fundamentally different approach than most leaders were trained for. The Millennial engagement data is not an HR problem. It is a revenue problem. Developing that leadership capability is one of the highest-return investments an organization can make right now.
The second is about transformation. If you are navigating AI adoption and sensing that the human system underneath it needs attention, that is exactly the work Compass Performance Group does. Embedded, sustained, and focused on producing the ROI the change was intended to deliver.
These are some of the most important conversations organizations are navigating right now. If any part of this resonates with what you are seeing inside your business, I’d genuinely love to chat.
Sources
Aon (2026): Human Capital Trends Study
Boston Consulting Group & Columbia Business School (2025): Harvard Business Review, November 2025
Boston Consulting Group (2025): The Widening AI Value Gap, September 2025
Gallup (2025): State of the Global Workplace Report
KPMG in Canada (2026): Beyond AI Adoption, March 2026
World Economic Forum (2025): The Future of Jobs Report 2025
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