However, as experts like David Mattin (founder of New World, Same Humans) and Miro’s Dom Katz explore, the hardest part of transformation isn’t the software; it’s the “human hardware”.
To put it another way, your AI strategy is essentially a people strategy, because it’s the employees who will set the tone and the pace of change. Here are four key perspectives to achieve success in this transition:
1. Transformation moves at the pace of people, not technology
AI companies have made bold promises: they claim it will 10x productivity, accelerate collaboration, and create new kinds of work. Seeing the speed and sophistication of the underlying models increasing at a frantic pace, many leaders are understandably frustrated that these gains are yet to materialize immediately. The issue is not with the technology so much as our understanding of how change actually happens inside organizations. As Mattin points out, you can’t just drop a transformational tool on a thousand people and suddenly expect them to find entirely new ways of working. Changing deeply embedded habits, working relationships, and all this messy human stuff takes time to figure out. While billions are spent on AI deployment, time may be the one thing nobody has budgeted for, leading to a mismatch of expectations.
The takeaway: Don’t rush. It’s easy to get swept up by influencers and think you’re behind, but the reality is, nobody has a perfect playbook. Listen to your employees, take their feedback on board, and figure out what AI transformation should look like specifically for your organization.
2. Technology can’t fix a poor corporate culture
One of the more misguided assumptions is believing that AI will wash away any number of organizational sins, assuming, for example, that it will fix broken decision-making processes. The reality is that technology amplifies culture, it has never solved culture. If your team is already struggling with decisions, 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: Understand that technology acts as a magnifying glass that will reveal the good and bad of an organization with merciless clarity. Problem solve ahead of time: audit your processes, anticipate areas of concern, and fix the root causes before AI exposes the cracks.
3. Hands-on experimentation beats traditional 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 the traditional “classroom” approach is out, and hands-on “play” is in. Gartner reveals that only 6% of individual contributors have received guidance on the AI skills they need to develop. A lot of your AI solutions are going to come from the ground up. Therefore, leaders must give people constant permission to play, experiment, and celebrate those attempts. Furthermore, employees deeply value peer-to-peer learning; they just want to see what other people with a similar problem or role are doing.
The takeaway: Create a space to play and experiment. An excellent example is running internal hackathons. These shouldn’t just be for engineers or major projects; functional hackathons or offsites for leaders have a massive impact by giving room to play around with new tools in a fun way.
4. Leaders need to get their hands dirty and role model
Successful AI transformation strategies start with value: “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. A great way to start for any employee is to solve a small problem or fix some glitch that was slowing them down. However, leadership has a bigger role to play: they need to role model. It’s easy to think of transformation as a “for you” change, but this is an everyone transformation, so leaders need to lead and show that they are also playing around with these tools.
The takeaway: Be an activist, not just an advocate. Find a real process (like onboarding, interviews, or project management), rip it up and rebuild it using AI. Then talk to employees about your approach, your learnings, your wins, and your failures.
Conclusion: Culture eats strategy for breakfast Whether you’re just starting out on your AI transformation journey, or 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. There’s a tendency to get hung up on the shiny new tools, but you will always find the true answers to transformation in the collision of the technology, the humans, and the culture
