Are workplaces designed to earn our trust in AI?

Millions of people rely on artificial intelligence (AI) to navigate traffic, curate entertainment, recommend purchases, and create personal content. AI is deeply embedded in our everyday lives, helping us be more informed, more productive, more creative. It's hard to remember life before AI.

Yet a very different sentiment emerges with AI in the workplace. According to Kyndryl's People Readiness Report, which surveyed over 1,000 business and technical leaders across 8 markets and 25 industries – while 95% of organizations are actively integrating AI into their business processes, many employees remain unsure about using it. In fact, 45% of CEOs report employee resistance or hostility toward AI adoption.

Trust in AI remains elusive for many organizations. Employees are not only uncertain about how AI will change their work - they're also deeply concerned about job security and the reliability of these new systems. They question: "Is it accurate?" "Is it safe?" "Will it replace me?"

Understanding how to bridge the trust divide – between personal and professional use – is key for leaders to unlock the full potential of AI.  

In our personal lives, the use cases for AI feel controlled and low risk.  We are "opted-in" as consumers because we consent to the hyper-personalized experiences that machine learning can deliver.  If a streaming service recommends a bad movie or a navigation app suggests a longer route – it's irritating but we can live with it (or switch tools). The consequences of failure are minor and often reversible. We don't bear grudges. We trust the AI will do better as it matures and learns more about us over time. 

Conversely, the use cases for AI can feel imposed and high risk in our professional lives. Lack of transparency in the workplace around enterprise AI systems – the scope of data, the guardrails against bias, the decisions being made – can erode employee trust and adoption, especially if it seems like AI is about them, not for them.  Rapidly changing technology, industry standards and regulations adds to the sense of uncertainty. Accountability still rests on people, and the consequences of failure could be detrimental to customers, company performance and careers.  For employees, it seems safer to opt-out and avoid the blast radius, should things go sideways.    

What sets AI leaders apart? How have they bridged the trust gap? 

Kyndryl's research identified a small group of AI pacesetters - just 14% - who are ahead of the curve by focusing on organizational change management and workforce upskilling. They are equally intentional about "preparing the people for the technology" and "preparing the technology for the people". Employees are engaged in continuous learning, and their leadership teams have communicated clear strategies and governance frameworks to position AI as a driver of growth and innovation.  Business processes are revised, workloads are re-distributed, as with any situation where a team gains new members and capabilities. Employees are elevated to higher value work. They benefit directly from the removal of toil, and their organizations can measure the return on investment.  

With 88% of leaders expecting AI to transform roles within the next year, Canadian organizations must act quickly to build both skills and trust by:

• Positioning AI as augmentation, not replacement
• Making accountability shared and explicit
• Engaging with transparency, not just compliance controls
• Empowering employees with choice and feedback channels
• Providing safe spaces for experimentation
• Treating adoption as a user journey, not a technology rollout.  

It's not a paradox that people trust AI in their personal lives and not at work. Rather, it's about designing workplaces that earn employee trust.  Trust is the outcome of transparency, positive reinforcement and most of all, familiarity.  AI use needs to feel easy and rewarding, something we incorporate organically and intuitively into new ways of working.