INSIGHTS

Building AI Fluency Without Breaking Trust: How to Empower Your Workforce While Protecting What Matters

Artificial Intelligence | Employee Experience
A new year brings fresh focus, renewed commitments, and the drive to become better versions of ourselves. So, let’s channel that energy toward AI—cutting through the noise to find where real progress happens. We will begin with a few numbers.

Here is a statistic that should wake up every executive: 76% of leaders believe their employees are enthusiastic about AI adoption. The reality? Only 31% of individual contributors actually feel that way. According to Harvard Business Review, leaders are more than two times off the mark when it comes to understanding how their workforce really feels about AI.

That perception gap is not just awkward – it is dangerous. And here is why it matters: high-trust companies outperform low-trust companies by 286% in total return to shareholders. Trust is not a nice-to-have – it is a competitive advantage with a measurable ROI.

Welcome to the HR leader’s current dilemma!  You are supposed to drive AI adoption while your employees are considerably less excited about it than you think, and somehow not make everyone feel like they are auditioning for an episode of Black Mirror!

The good news is that the companies that are getting this right are not choosing between AI transformation and employee trust. The are actively figuring out how to do both. Here is what we have observed that works.

What We’re Hearing from Employees

Before we dive into solutions, let’s talk about what is actually happening on the ground. In our conversations with employees across industries, we are hearing three recurring themes that should make every HR leader pause:

  • ‘I feel like I’m training my replacement.’ This one comes up constantly. Every time an employee teaches an AI system how they do their job, documents their workflow, or shares their expertise with a learning algorithm, there is a nagging question (and feeling!) in the back of their mind: Am I just making myself obsolete? It doesn’t matter how many times leadership says ‘AI is here to augment, not replace’ – when employees see headcount reductions happening alongside AI adoption, the messaging rings hollow.
  • ‘I know when I’m being watched, and it’s exhausting.’ The tools might be invisible, but the stress is not. Employees can tell the difference between performance support and surveillance. When people optimize for appearing busy rather than being productive, everyone loses.
  • ‘The trust is just… gone.’ When surveillance changes, the psychological contract between employer and employee changes.  You do not just lose productivity – you lose discretionary effort, innovation, and loyalty. Those are commitments from the employee that do not come back to the flow of work easily.

These are not occasional cases. This is what is happening in organizations right now. The key question is now – How do we address it?

AI Fluency: It is not about the Technology

Let’s start with a truth bomb: most AI training programs are bad.

You know the drill – schedule a two-hour “Introduction to Generative AI” session on Teams or Zoom, complete with a deck explaining neural networks and machine learning fundamentals. Cameras turn off halfway through. Everyone politely acknowledges the details in the chat. After the session, behavior does not change.

We have seen this play out too many times. The problem is not that employees do not get it. The real issue is that they do not see why it matters to them.

We suggest that what works instead is to:  Make it specific, make it safe, and make it theirs.

Your marketing team does not need a lecture on large language models. They need to see how AI can analyze campaign performance in minutes instead of days. Your CX team does not care about transformer architecture. They want to know how AI can surface customer pain points from thousands of interactions to inform product roadmaps. Your contact center team is not interested in neural networks. They want AI that suggests responses in real-time so they can resolve issues faster and stop getting dinged on handle time metrics.

And critically, they need space to experiment without feeling stupid. Top talent does not leave companies because they are bad at AI – they leave because they are terrified of looking incompetent while learning it.

Create learning labs. Pilot programs. Spaces where trying and failing is not only accepted but expected. When your CFO shares their clumsy first attempts at prompting AI tools in an all-hands meeting, you have realized that everyone has permission to be a beginner.

Encourage employees to develop a relationship with their AI assistant. This is not just about learning prompts or mastering features – it is about building a working partnership. Just like any colleague, AI tools have strengths, limitations, and quirks. Employees need time to figure out how their AI assistant “thinks,” what kinds of questions get the best results, and where human judgment still needs to take the lead. The most effective AI users are not the ones who memorized a training manual – they are the ones who experimented enough to develop their own communication rhythm with the technology. Give people permission to personalize their learning approach and discover what works for them.

One more thing we are seeing: cease gatekeeping AI tools. When only senior leaders get access to the premium AI resources, you are not protecting your investment.  Rather, you are sending a message about who matters. Democratize access. The administrative assistant who figures out how to automate scheduling conflicts might save you more time than any executive’s pet project.

The Surveillance Problem: We Need to Talk About It

Let’s address the thing everyone is thinking but few HR leaders want to say out loud: a lot of AI-powered productivity tools are just fancy surveillance dressed up in efficiency language.

Your employees know this. They can tell the difference between a tool that helps them identify bottlenecks in their workflow and one that tracks whether they moved their mouse every 10 minutes. And they are making decisions about whether to stay based on which one you choose.

Here is a framework we have observed that separates the companies people want to work for from the ones who are quietly job-searching while working:

  • Transparency beats everything. If you are measuring something, say so. Explain what, why, and how the data gets used. The second employees discover you have been tracking something you did not mention, you have eroded any trust you had. And trust, unlike productivity metrics, does not come back easily.
  • Measure outcomes, not activity. If someone delivers exceptional work in 30 hours instead of 40, congratulations – you hired someone efficient. Tracking their mouse movements or email response times at that point is not management, it’s paranoia. High performers want accountability for results. They do not want (or need!) a digital hall monitor.
  • Know the difference between support and punishment. AI that helps me see where my time goes? Useful. AI that creates an automated report for my manager when I am “inactive” for 15 minutes? Insulting. Same technology. Completely different message about whether you trust your people.

What This Means for Keeping Your Best People

Your top talent has options. They always do. And they’re not choosing companies based on who has the most sophisticated AI stack. They are choosing based on who treats them like trusted professionals being equipped for the future, not like productivity units that need constant optimization.

The numbers bear this out: high-trust organizations experience 50% lower turnover rates than their competitors. That’s not just about saving recruitment costs – it is about retaining institutional knowledge, maintaining team cohesion, and keeping the people who actually know how to get things done in a high-performance environment.

What do the winners in AI do differently?

  • They involve employees in the decisions. Form working groups that include actual individual contributors – not just management – to shape your AI policies. When people help create the rules, they are more invested in making them work.
  • They show career pathways, not dead ends. Map out how roles evolve with AI. Show people that building AI fluency opens doors. Because right now, a lot of your employees are quietly wondering if they are training their own replacement (the first point we made!)
  • They audit for fairness, and they share what they find. When employees see you catching and correcting algorithmic bias in performance reviews or promotion recommendations, they learn that you are serious about fairness. When you hide that process, they assume the worst.
  • They give people time to learn. Protected learning time is not a luxury – it is how you signal that you are investing in people’s growth, not just extracting their current productivity. And those “AI sabbaticals” often yield innovations you did not see coming.

The Bottom Line

Here is what we are really talking about: sustainable productivity versus short-term extraction.

You can absolutely squeeze more output from people using surveillance tools and AI-powered monitoring. For a while. Until your best people leave, your culture becomes toxic, and you are stuck in an endless recruiting cycle trying to replace the talent you burned through.

Or you can build AI fluency as a foundation, create transparent systems that empower rather than police, and give people the tools and trust they need to do their best work.

The first approach optimizes the near-term. The second approach builds organizations people actually want to be part of.

Your top performers are watching to see which one you choose. And they have already got their LinkedIn profiles updated, just in case!

We Want to Hear from You!

How is your organization approaching AI fluency and employee trust? Are you seeing surveillance creep into your productivity tools? What is working – and what is backfiring?

We are gathering insights from HR leaders navigating these exact challenges. Please share your experience with us at info@cortico-x.com or connect with us on LinkedIn. We commit to publishing what we learn!

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Robyn Gilson

Is a Vice President at Cortico-X and leads our Healthcare and Experience Management practice. She excels at turning customer feedback into useful business insights that produce measurable results while building stronger relationships with everyone involved in your business.

Alyson Daichendt

Is a Vice President at Acquis Consulting, the parent organization for Cortico-X. Alyson specializes in Organization and Talent consulting. She helps clients enhance employee experience, drive engagement, and build great workplace cultures.
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Sources

Lovich, Deborah, Stephan Meier, and Chenault Taylor. “Leaders Assume Employees Are Excited About AI. They’re Wrong.” Harvard Business Review, November 26, 2024. https://hbr.org.

Gleeson, Brent. “5 Proven Ways Trust Is The Ultimate Competitive Advantage.” Forbes, March 19, 2025. (Cites Harvard Business Review research indicating companies with high levels of trust outperform low-trust companies by up to 286% in stock market returns, and Great Place to Work research showing high-trust organizations experience 50% lower turnover rates.)

Great Place to Work. Research on trust and employee turnover rates. Referenced in Gleeson (2025).