How a Psychology Background Makes for Better AI Adoption

If your LinkedIn feed is like mine, 80% of the content is gushing about how the latest AI model will revolutionize their business. But for me, this matters almost zero – folks have got it backwards. The thing that will most significantly determine the extent to which a business will benefit from AI is their culture – it’s a change-management issue, not an issue of using this AI model or that.

More accurately, it’s a change-management opportunity. It’s an exciting time in history when people at every level can be empowered by technological changes – and you, as a business leader, can be the one motivating your organization and helping navigate this change process successfully. To do that, I’ve found, means going back to basics.

My own “basics” include a degree in psychology from well before I started building AI products, and I’ve increasingly been drawing on foundational psych concepts to drive better results as customers I work with adopt AI in their business. Here are the principles of change management that can also empower your organization as it undertakes the AI transformation.

Turning uncertainty into understanding

One of the biggest hurdles faced by organizations implementing AI is fear. The fear of needing new skills, of innovating faster than one can keep up, and above all of AI making roles redundant – these are all understandable and worth tremendous empathy. But re-framing how these feelings about AI arise and are conceptualized is crucial to future success.

As the school of Positive Psychology has established, human concerns need a human approach: more than simply alleviating negative emotions, it’s most effective to emphasize strengths, well-being, and growth. In other words, shifting your messaging from pathology to compassion, from pessimism to optimism, is the only way to address very real fears and get genuine buy-in to new ways of thinking.

I honestly believe the most effective communications strategy now is to put AI in the context of earlier points in time like the Industrial Revolution or the early internet. It’s unpredictable, but it’s exciting: people are gaining new skills and achieving new things no one on Earth has ever done before. Your genuine passion for doing new things and making real society-wide progress will be the basis of a company culture that embraces experimentation without fear and with enthusiasm – setting the tone for all the following AI transformation efforts your team undertakes.

The most underrated link in AI adoption

Those efforts, though, will need to build on your positive company culture by grasping the nuts and bolts of how individuals learn new skills and habits. Giving your company the base set of skills that everyone needs in the AI era can’t just be a PowerPoint; measuring outcomes can’t just be a survey. Your adoption plan has to be a fleshed-out, long-term initiative driven by observational learning and leveraging principles of conditioning.

Familiarity breeds contentment

Observational learning is social learning, how children to top athletes model behaviors based on what they’ve already seen others do. Simply put, show me things I can relate to, and I’ll adapt – maybe not flawlessly, but comfortably. We, as humans, are built to work this way.

This is how our company, Make, constructed our in-house AI adoption program. We sent a detailed questionnaire to each employee – Which tools are you already familiar with? What are the pain points you’d like to address? Who do you already come to with questions about AI? The responses formed the basis for individually tailored learning plans, giving every team member an actionable roadmap for building useful AI skills in a way familiar to them.

From concept to habit: Making AI stick

Ensuring skills actually take root requires showing real value to the learner. For this, AI needs to be ingrained in existing tools and processes – it can’t be some burdensome “separate thing”. For example, built-in AI capabilities in Slack can do wonders to supplement my thinking and maximize results in an application where I’m already spending my time.

Ultimately, identifying where AI will produce the most value needs to be determined by how specific roles see maximum usability – giving everyone the latitude to identify individual bottlenecks and the AI skills to solve them, either on their own or collaboratively. This positive reinforcement will confirm the thinking that AI actually does let you accomplish tasks quicker, better, or entirely new.

Showing this value in day-to-day processes consistently will go even further: with time, classical conditioning will automatically make AI top of mind whenever a complex or unfamiliar task needs solving.

Trust but verify

AI agents should be go-to tools, but they can’t run on autopilot; AIs citing nonexistent legal cases or columnists recommending fake books are two recent examples of the risks that come with removing the human element altogether. Assessing risk appetite for every AI use case is crucial to implementing the best solution.

Yet, as any parent of a teenager can assure you, humans come with built-in unconscious biases that make accurately assessing risks difficult. The availability heuristic, for example, pushes us to overestimate the likelihood of particularly memorable events; its near-opposite, the optimism bias, leads us to believe that negative events are less likely to happen to us than to others. And these are just two of a very long list.

Tools that help you verify your AI agents’ outputs and orchestrate how they work together is one step toward cutting through biases and managing risks, and forward-thinking AI companies are developing these. But knowing which biases exist in the first place and how they work will be how you make sense of issues that pop up and safeguard against them.

Conclusion

In the end, navigating the AI transformation isn’t going to be much different from the digital transformation many of us have already lived through. As we found then, coming out better, faster, and stronger actually means mastering the low-tech principles of change management: understanding how the human mind works will help us adapt to – and get the most out of – this brave new world.