Millions of people rely on artificial intelligence (AI) to direct traffic, curate entertainment, recommend purchases, and create personalized content. AI is deeply integrated into our daily lives, helping us become more informed, more productive, and more creative. It’s hard to remember what life was like before AI.
But when it comes to AI in the workplace, very different feelings emerge. Kyndryl’s People Readiness Report surveyed more than 1,000 business and technology leaders across eight markets and 25 industries. While 95% of organizations are actively integrating AI into their business processes, many employees remain nervous about using it. In fact, 45% of CEOs report employee resistance or hostility to AI adoption.
For many organizations, trust in AI remains elusive. Not only are employees worried about how AI will change their jobs, they are also deeply concerned about job security and the reliability of these new systems. They wonder, “Is that accurate?” “Are you safe?” “Would you be willing to take my place?”
For leaders to realize the full potential of AI, it is important to understand how to bridge the trust gap between personal and professional use.
In our personal lives, AI use cases feel controlled and low risk. As consumers, we “opt in” to the hyper-personalized experiences that machine learning can provide. It’s frustrating when a streaming service recommends a bad movie or a navigation app suggests a longer route, but you can live with it (or switch tools). The consequences of failure are minor and often recoverable. We hold no grudges. We believe that AI will perform better over time as it matures and learns more about us.
Conversely, AI use cases can feel forced and high risk in our professional lives. A lack of transparency in the workplace around enterprise AI systems – the scope of the data, guardrails against bias, and decisions being made – can undermine employee trust and adoption, especially if the AI is perceived to be theirs and theirs. Rapidly changing technology, industry standards, and regulations increase uncertainty. Accountability still lies with humans, and the consequences of failure can negatively impact customers, company performance, and careers. It seems safer for employees to opt out and avoid the blast radius in case things go the wrong way.
What are the characteristics of AI leaders? How have they bridged the trust gap?
Kyndryl’s research identified a small group (just 14%) of AI leaders who are staying ahead of the curve by focusing on organizational change management and employee upskilling. They have similar intentions for “giving technology to people” and “preparing technology for people.” Its workforce is committed to continuous learning, and its leadership team has communicated a clear strategy and governance framework to position AI as a driver of growth and innovation. Just as when a team acquires new members or capabilities, business processes are reviewed and workloads are redistributed. Employees can move on to higher-value jobs. The reduction in effort provides direct benefits and allows organizations to measure return on investment.
With 88% of leaders expecting AI to change their roles within the next year, Canadian organizations need to act quickly to build both skills and trust by:
- Position AI as an augmentation, not a replacement
- Share and clarify accountability
- Commitment to transparency, not just compliance management
- Give employees choice and feedback channels
- Providing a safe space for experimentation
- Treat adoption as a user journey rather than a technology rollout.
It is not a contradiction that people will trust AI in their personal lives rather than their work lives. Rather, it’s about designing a workplace that earns your employees’ trust. Trust is the result of transparency, positive reinforcement, and above all, friendliness. Using AI needs to feel easy and rewarding, and we’re embedding it organically and intuitively into new ways of working.
