Every CEO is grappling with the same problem: You need AI to stay competitive. Boards are demanding it, competitors are implementing it, and you’re investing millions in the technology. Yet despite your own personal enthusiasm, your employees aren’t adopting these tools at the pace you expect. That’s costing you money—and momentum.
This is the “messy middle” of AI adoption, when organizations shift from experimentation to integration. People and culture, not tools, are what will help companies get ahead.
After talking with customers around Asia-Pacific, I’ve found that the most successful teams are looking at how AI enhances, not replaces, human potential. This matters as AI adoption varies widely by role and seniority. Entry-level workers experiment freely and the C-suite sees strategic value, yet middle managers often struggle to bridge the gap.
This uneven approach means leaders can’t take a one-size-fits-all approach. They have to meet people where they are, which makes aligning around people even more critical, especially for leaders trying to manage talent and build trust.
After leading LinkedIn’s APAC business and managing sales teams for over a decade, one lesson has stood out to me: Pushing adoption, without clarity, leads to costly detours. Sustainable transformation isn’t achieved by a mandate; instead, it’s driven by leaders who focus on people first.
For leaders struggling with AI adoption, the answer isn’t to push harder to mandate its use. Instead, they have to focus on the human side of the equation; they must bring employees on the journey of transformation by creating a culture that supports adaptability and rewards learning and innovation.
Middle managers are the missing link
Middle managers sit at the heart of AI adoption. They face pressure from above to deliver on initiatives they may not fully understand, while reassuring those below about their job security. They’re the ones tasked with making AI work day-to-day. They juggle performance targets, team concerns and adoption mandates, often without a playbook.
They ask themselves: How do I explain these changes to my team? What happens to the career paths we’ve built? How do I remain confident when even I’m uncertain about how AI will affect my own role?
In a recent LinkedIn survey, nearly half of companies expected employees to start using AI, yet 41% of professionals already feel overwhelmed by how quickly they are expected to master it. Meanwhile, 84% of APAC professionals aged 18–24, and 77% of those aged 25–34, believe AI cannot replace human judgement at work.
Middle managers don’t need to have all the answers. Instead, their value comes in acting as trusted coaches, helping teams connect the dots between new technology, shifting requirements, and long-term career goals.
Companies that successfully implement AI start with a people strategy before they deploy the technology. They’re brutally honest about what AI cannot do, and create space to gradually integrate it into their operations.
From automation to reinvention
LinkedIn’s research shows that while 45% of professionals use AI regularly for routine tasks, only one in three of those AI users apply it to high-level work like strategy or data analysis. What’s holding them back isn’t technical skill, but instead their sense of control over the technology.
In Singapore, where I’m based, one in four people use ChatGPT on a weekly basis, which is among the highest usage rates in the world. That’s true AI readiness: Singaporeans are going beyond exploration and experimentation to embed AI into daily work. This high adoption rate demonstrates that when people feel they have agency over how they use AI tools, they engage with them more deeply.
Adoption accelerates naturally when professionals understand that AI is amplifying their capabilities, rather than replacing them. That requires companies to move beyond simply using AI to automate tasks, but rather to explore what new possibilities it opens up.
Change management in action
Leaders are being pressured to move faster, and do more with less, at the same time. But they mustn’t lose sight of the need to invest in foundations that set employees up for success. For example, they should give middle managers the time and tools to become confident AI users themselves, before asking them to lead others to adopt AI. Leaders need to reward progress, not perfection.
This is what I call “thoughtful change management:” Aligning people to a shared vision, enabling collaboration, learning from experience, and then relocating resources. Employers can create weekly forums where employees can share both AI successes and failures without judgment, then reallocate budgets away from underperforming AI experiments to pilots that are showing success.
When people see concrete evidence that leadership is investing in their capability–and not just deploying technology for its own sake–they’ll shift from feeling threatened to feeling empowered.
Companies shouldn’t rush through the messy middle; those that win the AI race in the long run may not be those that deployed the technology first, but those that built the strongest collaboration between humans and AI. A firm’s edge will be how well their employees work alongside this technology.
Leaders need to be transparent about where they will use AI, where it falls short, and when human judgment remains paramount. Employees have to see their leaders learning alongside them: That builds the trust needed for meaningful transformation.
The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.
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