When organizations talk about “AI transformation,” they usually start with the technology. But as we explored in our recent webinar with David Mattin (founder of New World, Same Humans) and Miro’s Dom Katz, the hardest part of transformation isn’t the software; it’s the “human hardware.”
To put it another way, your AI strategy is a people strategy because it’s employees who will set the tone and the pace of change.
Check out the webinar to get all the insights. Here are just some of the highlights to give you a taste.
Transformation moves at the pace of people
AI companies have made bold promises: It will 10x productivity, accelerate collaboration, and create new kinds of work. Leaders are understandbly frustrated that these gains are yet to materialize, especially as the speed and sophistication of the underlying models is increasing at a frantic pace.
The issue, suggests David Mattin, isn’t with the technology so much as our understanding of how change happens inside organizations.
“You can’t just drop a transformational tool on a thousand people and suddenly expect them to find entirely new ways of working,” he says. “This is about having to change habits that are deeply embedded in the organization, it’s about working relationships, and all this messy human stuff that takes time to figure out.”
While billions are spent on AI deployment, time may be the one thing nobody has budgeted for. David again: “The technology is moving at light speed but human adoption of it will move at the speed of humans. There’s a mismatch of expectations.”
The takeaway
Don’t rush. As Dom points out, “It’s easy to get swept up by influencers and think you’re behind. The reality is, nobody has figured it out. There’s no perfect playbook.”
Listen to employees, take their feedback on board, and figure out what AI transformation should look like for your organization.
Technology can’t fix culture
One of the more misguided assumptions about AI is that the technology itself will wash away any number of organizational sins. As in, “It doesn’t matter if our decision-making processes are broken — AI will fix that.“
But this isn’t how it works. “Technology amplifies culture, it has never solved culture,” explains Dom Katz. “If you’re already struggling with decisions, or with collaboration, or with too many silos, then AI is probably going to make it worse — at least for a while.”
The data bears this out: 69% of leaders say switching between work tools and AI tools causes friction. While only 18% of employees feel their organization provides support to integrate GenAI tools into their daily work.
The takeaway
Technology is a magnifying glass that will reveal the good and bad of an organization with merciless clarity. The best approach is to problem solve ahead of time: Audit your processes, anticipate areas of concern, and fix the root causes before AI exposes the cracks.
Experimentation beats education
The AI skills gap is top of mind for many leaders. According to Forrester, 30% of organizations will run mandatory training courses in 2026. But if that’s the case, something isn’t working. Gartner reveals that only 6% of individual contributors have received guidance on the AI skills they need to develop.
The problem, says David, is that AI challenges our preconceptions about how people learn. The classroom is out. Hands-on “play” is in.
“What you’re going to have to do is give people space to experiment,” he says. “A lot of your AI solutions are going to come from the ground up. What you can do from the top is, over and over again, give people permission to play and experiment. And celebrate that.”
Dom agrees. “The biggest thing people want is peer-to-peer learning,” he says. “Just show me what other people are doing who have a similar problem or role to me.”
The takeaway
Create a space to play and experiment. For instance, Miro runs internal hackathons — and not just for engineers or major projects. “Sometimes it’s just a functional hackathon, or a hackathon at an offsite for our leaders,” explains Dom. “The biggest impact is the room to play around with new tools. That’s been a massive and really fun experiment.”
Leaders need to get their hands dirty
Successful AI transformation strategies start with value. The question they answer is, “How can we accelerate our most important work?” The more clarity you have on what that work is, the quicker you’ll get from AI deployment to ROI.
As David makes clear, this is everyone’s responsibility: “If you can go to your manager and say, ‘I had this problem and now I have this solution for it,’ every manager loves hearing that. Solve a small problem or fix some glitch that was slowing you down. That’s a great way to start,” he advises.
But in Dom’s view, leadership has a bigger role to play. “You need to role model. Show that you’re also playing around with these tools,” he says. “It’s easy to think of transformation as a ‘for you‘ change. But this is an everyone transformation, everyone is impacted, so leaders need to lead and get their hands dirty.”
The takeaway
Be an activist, not just an advocate. Find a process that can be improved then rip it up and rebuild it. It could be project management, onboarding, or your interview process. Then talk to employees about your approach, your learnings, your wins, and your failures.
Remember: Culture eats strategy for breakfast
Whether you’re just starting out on your AI transformation journey, or you’re looking to accelerate from pilot phase to company-wide scale, it’s never too early (or too late) to shift the focus from your tools to your people.
As David concludes: “There’s a tendency to get hung up on the shiny new tools, on the technology, and to not think about the other really crucial side of this picure, which is the people, the culture, the human side of this.
“It’s in this collision of the technology and the humans and the culture that you’re going to find the answers.”
