Every organization is scrambling to adopt AI, but many are missing out on one of its most transformative benefits: the ability to increase creativity within and across teams.
Part of the challenge is that AI rollouts often focus primarily on automation without emphasizing ways to safeguard the human side of work. Miro's recent AI survey found that nearly half of global knowledge workers (46%) say that there's a lot of talk but no action at their company when it comes to AI, and 39% report that their company often abandons AI efforts. This highlights how, when organizations go all in on productivity and efficiency, they can inadvertently sideline creativity, strategy, and the true power of teams.
To carve a better path forward, organizations should approach AI rollouts in a strategic way that keeps people at the center of work. Here, I share three ways to build better rollouts that can help organizations harness AI as a creativity multiplier.
1. Prioritize "Thinking Space" for Team Insight
Sparks of creativity tend to come when team members can pause, reflect, challenge assumptions, and connect dots in new ways — not when they're going through the motions of automated, rigid processes. Creative "aha" moments are vital for organizational innovation, resilience, and strengthening a sense of connection between knowledge workers and their work.
Organizations should design AI rollouts that nurture this space for reflection and ideation. For instance, building workflows where automation accelerates routine tasks shouldn't just mean more work. Instead, leaders can earmark that extra time for team brainstorming, strategy sessions, and creative reviews.
Another option is to position AI as a sparring partner rather than just another tool. Use it to test ideas and examine new angles that competitors have not yet tried. This way, AI is supporting, rather than replacing, the foundational creative thinking that gets teams fired up.
A third approach is to encourage and preserve dedicated time for teams to step back from automated AI outputs to question, reframe, and refine. This provides an opportunity to explore what's working and where support is needed, which can inform future rollouts.
Smart, strategic adoption is a continuous process and requires ongoing attention. When done well, AI reduces wasted effort on outdated approaches and empowers teams by enabling meaningful collaboration.
2. People-First Adoption Requires Training and Support
Over one in five U.S. employees receive little to no training on AI tools, yet nearly half would like their companies to help them upskill, according to Miro's survey. Not training your teams on AI doesn't just set adoption back; it also sows seeds of doubt about the tools themselves, leading to inefficient use or even avoidance.
It's important to remember that different rollouts will have different needs. If AI is introduced through a net new platform, teams will need targeted training on the technical basics of the tool along with confidence-building exercises. However, if AI is embedded into existing platforms, training should emphasize discovery and experimentation. This means enabling team members to recognize new AI features in tools they already use and then practice to refine their skills.
Organizations should invest in AI onboarding that adapts to the type of rollout and user needs. Small, team-based training sessions that connect directly to daily workflows can determine whether AI becomes a productivity multiplier rather than another unused feature in the tech stack. Moreover, all trainings should be accessible and inclusive to accommodate diverse learning styles and needs.
By lowering the barriers to adoption and showing employees how AI can integrate into their existing practices, companies can help transform AI uncertainty into confidence.
3. Train for Curiosity to Maximize Impact
Too often, employee training focuses on teaching which buttons to push or what steps to follow. This formulaic approach stifles outside-the-box thinking. Workers are eager to learn AI and our survey found that 76% believe it can benefit their role, yet over half struggle to know when to use it.
Cultivating an experimental mindset is a tremendous asset when working with AI. When teams feel empowered to test, question, and push back on AI outputs or recommendations, it sparks creativity and exploration. In contrast, overly prescriptive training can unintentionally reinforce passive use which is important with AI, since outputs are not always correct. This is part of what makes the human touch so valuable.
Companies need to shift their training lens from compliance and rule following to curiosity. For example, encourage team members to refine AI prompts and then thoroughly evaluate the outputs. Take it a step further by creating space for people to share their experiences, offering on-the-job insights, strategies, and tips.
What's more, organizations should recognize and reward this experimentation. Challenging assumptions and playing around with AI can reveal new possibilities, so signal to your teams that this exploration is not just allowed — it's expected. As leaders, we can reinforce these values by sharing our own stories of AI trial and error.
When teams see AI as a peer to collaborate with rather than a tool to passively rely on, it can become a real partner in driving innovation.
Successful AI Rollouts Support Creativity as the Human Differentiator
In an AI world, organizations that thrive won't be those that automate the fastest. Speed is only part of the puzzle. The real differentiator is the ability to spark creativity by building the conditions where teams feel connected, motivated, and empowered to innovate with purpose. This means carving out space for human insight, tailoring training to existing workflows, and cultivating a culture of curiosity and exploration when rolling out AI.
As a tool on its own, AI is great. As a strategic partner and creative multiplier, it can be transformative. A strong, strategic AI rollout is the difference between stalled adoption and genuine innovation. This is why companies that implement these three tactics for adoption will empower their teams to think bigger, challenge assumptions, and shape what comes next.