AI promises speed, scale, and smarter ways of working. However, most organizations are discovering that adopting AI isn’t the hard part — sustaining it is. After the initial excitement fades, AI adoption slows, usage drops, and old habits resurface.
In this #shifthappens episode, Claire Engels, Senior Manager for Collaboration Experience & Productivity at Versuni, shares what she’s learned from leading AI adoption efforts in real, complex environments. Her perspective cuts through the noise. Making AI work isn’t about the technology itself; it’s about how people experience change and whether that change fits with how they already work.
Throughout the discussion, one message stands out: lasting AI adoption is built on behavior, not just riding a fad. The organizations that succeed focus on people first, create clarity at every step, and intentionally build momentum over time.
Below are three insights from the episode that reveal what it truly takes to turn AI adoption from hype into habit.
Drive Growth Through Openness
Every AI conversation starts with excitement — and hesitation. One of the earliest mistakes organizations make is assuming resistance means reluctance or lack of skill. More often, it simply reflects the human response to change.
As Claire explains, people don’t resist technology because they dislike progress. They resist because change feels risky and unfamiliar.
“Everybody, when starting something new, (we as humans) are resistant towards change.”
That insight reframes adoption entirely. Instead of pushing people to “get comfortable” as quickly as possible, effective leaders create environments where curiosity feels safe. Openness becomes a growth strategy, not a soft skill.
In practice, this means leaders actively invite questions, experimentation, and dialogue. It means normalizing learning in public — showing teams that it’s okay not to have all the answers. When people are encouraged to explore AI together, their confidence grows organically.
Openness is also about framing. When AI is introduced as a threat, it triggers defensiveness. When it’s positioned as a tool to support and amplify people’s work, it creates room for engagement. Small shifts in language – what’s in it for you, how this helps your day-to-day work – can dramatically change how teams respond.
Growth doesn’t come from forcing comfort. It comes from giving people space to learn without fear.
Build AI Habits, Not Just Hype
One of the most common patterns in AI rollouts is an initial surge of interest followed by a gradual return to old habits. Teams attend training sessions. A few early adopters experiment enthusiastically. Then, daily work takes over.
Claire is clear about why this happens: people don’t build habits from one-time events. “You have to start small,” she mentions.
Sustainable adoption begins with simple, repeatable actions embedded in everyday work rather than overloading teams with advanced use cases or sweeping transformations. When AI supports tasks people already perform, such as writing, summarizing, preparing, and analyzing, it becomes easier to return to it repeatedly.
Habits form through repetition; that’s why momentum matters more than novelty. Every small success reinforces confidence, and visible improvement strengthens the belief that AI is worth using.
Claire also emphasizes the importance of feedback loops. Teams need time to reflect: Where did AI save me time? Where did it help me see something differently? What worked and what didn’t work for the implementation? These moments turn experimentation into learning.
Recognition plays a role, too. When progress is acknowledged – even informally – it signals that effort matters. It reminds people that learning is part of the job, not something extra they have to fit in.
Hype fades quickly. Habits don’t. When AI becomes part of how work gets done – quietly, consistently – it stops feeling like a project and starts feeling like progress.
Empower Through Accountability
AI adoption often falters when responsibility is unclear. If AI is seen as “IT’s initiative” or “something leadership wants,” engagement stays superficial. Claire highlights a different approach: shared accountability.
“AI is an assistant. So, the better you understand how you can work with it, the greater your success will be,” she shares.
That framing is powerful. It reinforces that AI doesn’t replace judgment, creativity, or responsibility. People remain in control, and the outcomes still belong to them.
Accountability in AI adoption works on two levels. First, individuals must feel ownership over how they use technology. The more people understand how AI fits into their role, the more confident they become in using it responsibly. Clear boundaries, such as what AI is for and what it isn’t, build trust.
Second, leaders play a critical role by modeling behavior. When leaders actively engage with AI and not just endorse it, adoption feels supported rather than imposed. Visibility matters. People notice whether leaders are curious learners or distant sponsors.
Accountability also involves repetition and reinforcement. Change doesn’t settle after one explanation. Messages need to be restated, reframed, and revisited as humans learn through exposure and practice.
When accountability is shared, AI adoption becomes a collective effort. Teams feel empowered to shape how AI is used, rather than simply comply with it.
From Technology Shift to Cultural Shift
What makes this conversation resonate is its honesty. There’s no silver bullet and no single framework guaranteed to make AI adoption effortless. Instead, there’s patience, iteration, and work that people do to implement change.
As Claire notes toward the end of the discussion about AI, “It is indeed a tool, but it’s more about a mindset.”
AI adoption isn’t about staying ahead of trends. It’s about helping people feel capable, supported, and confident in a world that’s changing fast. When organizations lead with openness, focus on habit-building, and foster shared accountability, AI stops feeling overwhelming — and starts delivering real value.
That’s how hype turns into habit, and that’s how change sticks.
Episode Resources
#shifthappens Research: The State of AI Report
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