Byline COO

The Gap between using and Trusting AI (And no one is talking about it)

Companies are adopting AI Tools, productivity is improving, decisions are getting faster, and competitive advantage follows. That story is true for some organizations. But the data suggests it is not the full picture for most.

In June 2026, we surveyed 130 managers and senior professionals at Canadian companies about how they are using AI, what impact it has had, and how much they trust it. The results reveal something more complicated than either the hype or the backlash would suggest.

ADOPTION IS ALREADY THE NORM

85% of respondents said their company uses AI in some form. But when asked to describe the overall impact AI has had on their organization, almost 1 in 2 indicated a moderate or neutral impact (49%). This was followed by those who indicated a significant or transformational impact (31%), and lastly by the group that feels AI has had minimal or no impact within their company (20%).

That gap between how widely AI has been adopted and how much it has actually changed operations is the most important finding in the study. Most companies have cleared the adoption bar. What they have not yet figured out is how to make adoption meaningful.

THE TRUST IN AI

When we asked how much respondents trust AI-generated insights compared to other sources of information, the results were striking.

The majority indicated equal trust in AI and other sources (44%). But 38% said they trust direct sources more than AI. Only 18% trust AI more.

More managers trust direct research and human judgment over AI than the other way around, even though most of them are already using AI to inform decisions. That is not a contradiction. It is a signal. Companies are using AI not because they fully trust it, but because it is available, fast, and increasingly expected. The criteria for when to act on it, and when not to, are still being written in real time.

This is a story about organizations moving faster than their own frameworks can keep up with. Adoption moved faster than the criteria for using it well.

THE QUESTION LEADERS SHOULD BE ASKING

The bigger risk in 2026 is not adopting AI too slowly. Most companies have already cleared that bar. The risk is treating AI output as a conclusion rather than a starting point.

AI handles volume well. It identifies patterns faster than any team can. But the decisions that matter operationally, the ones that affect retention, workforce planning, product direction, and how customers experience your business, require understanding why those patterns exist. And that understanding still requires human judgment, direct research, or both.

The companies getting the most from AI are not the ones with the most tools. They are the ones that have developed clear internal criteria for when AI output is sufficient and when additional validation is needed before acting. For most organizations, that framework does not yet exist.

The data from our study points to a workforce that has adopted AI quickly but hasn't settled on how much weight to give its output compared to other sources of information. For leaders shaping how their organizations use AI, the open question for 2026 is not which tool to adopt. It is how to build the judgment layer that makes those tools actually work.

That is the conversation no one is having. And it is the one that matters most.

This article draws on findings from the AI Reality Check Study, a survey of 130 managers and senior professionals at Canadian companies conducted in June 2026. Full results available here