Some of these points relate to personal values and preferences — in other words, how individuals are accepting (or not) the shift toward new frameworks and processes.

I’ve heard a lot about this recently, so it makes sense to look at a recent Imagination in Action panel discussion. The conversation included my friend and colleague Jeremy Wertheimer, Amy Edmondson from Harvard Business School, and Johnny Ho of Perplexity, who likely needs no introduction. Alisa Cohn moderated the session.

How Do We View Our AI Journey?

The group focused on some general themes around AI adoption, particularly based on what could be called “personal thinking” — how each person individually approaches this new technological reality.

Here are some overarching ideas that influence what companies are doing today:

The Idiosyncrasies of Personal Use

One topic the panelists discussed was people using AI without openly talking about it. Cohn categorized adopters (and non-adopters) into three groups — one includes those using AI but hesitant to speak publicly about it for various reasons. Another group consists of people who avoid AI because they dislike it, while the third group involves leaders enforcing AI use within their organizations. Cohn referenced Toby Lutke’s well-known Shopify memo as an example, discussing how companies are limiting headcount unless a human role clearly adds value.

“The two takeaways I have were, ‘I've suggested that everybody use AI, but suggestions are not enough. I'm now going to (have to) force it.’ And (the second takeaway is) again, you won’t be able to get head count, unless you can prove to that person that job can't be done by AI. So, like, that's a big sea change, obviously.”

Edmondson commented on people finding their own path, distinguishing between mandatory adoption and a more encouraging approach. “There are two ways to close that gap broadly speaking. One is to just require people to close the gap, which is more or less what that message implied or sent, probably not intentionally. And the other is to make it appealing for people to close the gap,” she said.

Panelists also touched on the process of trial and error connected with AI use in the current environment.

Edmondson explained, “What people misunderstand about psychological safety is that it's not about being nice or feeling comfortable. It's about embracing discomfort because learning is uncomfortable. Psychological safety creates a space where being wrong isn’t catastrophic. You can ask for help, suggest wild ideas, admit mistakes, or report bad news. These things won’t feel easy, but you know they’re welcomed — much like in a great scientific laboratory.”

Times of Change

Jeremy Wertheimer, in particular, spoke about how things evolve during unstable times.

“Most of us are used to relatively stable conditions and practices that work under them,” he noted. “But right now, that mindset is completely outdated.”

He shared a story about people trying AI half-heartedly before giving up entirely.

“I’ll talk to an academic and ask if they’ve looked into this,” he said. “They reply, ‘Oh yes, I tried AI six months ago. It didn’t work, so I wrote a paper about it.’ Then I politely tell them they might want to try again.”

He emphasized the importance of mindset.

“Things keep changing, so we need to redefine our approach constantly,” he said. “Success isn’t just saying ‘we tried it, it didn’t work’ anymore. What didn’t work yesterday may work today. This openness is essential now.”

In periods of change, Wertheimer argued, there are no guarantees. People must innovate and stay aware of that reality.

The Entrepreneurial Mindset

At Perplexity, Johnny Ho stated that AI is already part of daily operations.

“For us, expectations continuously rise over time, creating a persistent gap. We see AI growing stronger exponentially. Whether that trend continues for the next five years remains uncertain, but for now, we expect continued growth. Each individual contributor will naturally have broader responsibilities as we expand across multiple platforms.”

Edmondson added, “Even leaders in long-standing, seemingly stable organizations can benefit from shifting their mindset. Think like a scientist — a completely different approach. You set directions freely, but don’t have all the answers. You guide people in forming better hypotheses.”

Human Skill Sets

Another key point I’ve written about repeatedly over the past six months is the evolving demand for human skills, including management-related competencies such as:

1. Analytical thinking
2. Resilience, flexibility, and agility
3. Leadership and social influence
4. Creative thinking
5. Motivation and self-awareness
6. Technological literacy
7. Empathy and active listening
8. Curiosity and lifelong learning

During the IIA panel, participants discussed emerging in-demand human skills (paraphrased below):

• Cracking the code – interpreting often mysterious AI outputs for practical application
• Oversight – ensuring AI efforts align correctly with goals
• Changing course – redefining strategies for both individuals and organizations
• Overcoming friction – breaking down barriers like data silos that slow progress

They suggested analyzing project success rates to develop better performance metrics.

The Outcome?

Ultimately, the panelists addressed the emotional aspects involved in the AI adoption journey. You can watch the full video for more insights.

Regardless, each of these perspectives highlights how people are engaging with AI in the 21^st century. Since we’re only a quarter into this century, every year brings rapid advancements in technology, demanding quick adaptation. Some of these concepts will surely aid in navigating this transformation.

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