AI adoption fails when workers fear being left behind
A global transformation specialist says listening to workers' fears is what determines whether AI actually takes hold
Fear of job displacement and confusion about the scale of change are the two biggest reasons workers resist artificial intelligence (AI), and companies that fail to address these concerns before rolling out new technology are setting themselves up for failure.
Acknowledging the fear is not enough. The real challenge is listening to what that fear is actually saying, and then breaking the change into pieces small enough for people to swallow.
“The question we need to be asking is why, and we have to listen to their why,” Jena Miller, a specialist in global transformation and adoption, told TechJournal.uk in an interview in London. “Are they afraid they are going to be replaced, or do they think the change is too big?”
“When we break it down and simplify it, and say this portion of AI is what we’re trying to introduce, you’re not swallowing the elephant, you’re eating a piece of mandarin. It becomes a lot easier to swallow,” she said.
Miller said the answer lies not just in communication but in ownership.
“When people as a collective believe in what you are trying to do and they own it themselves, your audience and your message become bigger,” she said. “There is a lot more power in a voice of 10 than in the voice of one.”
The pattern holds across sectors. She has spent her career in manufacturing, consumer goods and automotive industries. Companies are always trying to optimize and compete, but how they get there matters as much as the destination.
She said the most common mistake is trying to drag a team along rather than creating conditions that make the team pull leadership forward with their own ideas.
Clarity, alignment, inclusion
Miller was speaking at the AI & Big Data Expo, part of the TechEx event series, held in London. Her presentation, titled “Designing Transformation People Will Actually Adopt,” drew on her experience delivering large-scale change programs across global organizations.
The central argument of her talk was that technology is rarely the problem. Research from McKinsey, Prosci and the Harvard Business Review all points to the same finding: adoption, not technology, is the number one indicator of transformational success. McKinsey found that 70% of all change programs fail to meet their goals, not because the technology does not work, but because people cannot or will not use it.
“When people don’t trust or understand the change you are trying to introduce, technology can’t even begin to scale to its potential,” Miller said.
To address this, she introduced what she calls the adoption equation: three conditions that must exist simultaneously for change to stick. They are clarity, alignment and inclusion.
(1) Clarity is not about key performance indicators (KPIs) or deadlines.
“It’s the meaning. Meaning answers a very personal question: how does this affect my life, how does this affect my work, and how does this connect me to something larger than myself?” She used the example of an airport delay: being told a flight is 90 minutes late is just a metric, and passengers adapt by waiting.
But when a gate agent explains the delay is caused by a cabin pressure issue found during safety checks, the same wait feels entirely different. Passengers understand the why and may even feel relieved.
“People don’t resist change,” she said. “They resist meaningless change.”
(2) Alignment ensures that the proposed solution actually fits the environment in which it has to operate. She described rolling out a standardized workstation: the desk, chairs and core software are the standards. But engineers need adjustable monitor arms, finance needs secure document storage and human resources (HR) needs ergonomic flexibility.
Alignment invites the people closest to the work to help shape how change shows up in their day-to-day environment. It is not a redesign but a local integration that replaces friction with cooperation.
(3) Inclusion goes further.
“People will adapt under pressure,” she said. “People will adopt when they’re included, and ownership replaces resistance.”
She used the car purchase analogy: the engine, frame and safety features are non-negotiable, but inclusion lives in the options.
The long-distance commuter picks comfortable seating and a better sound system; the parent picks easy-to-clean materials and extra storage. Neither buyer is redesigning the vehicle. They are choosing how it shows up in their lives, and that choice creates ownership.
“Clarity gives people the why, alignment gives people the how, and inclusion gives people the ownership,” she said. “When you have all three, change doesn’t just show up, it sticks.”
Hammer on the floor
The clearest illustration of the adoption equation in action came from Miller’s own career. While leading a global rollout of a new manufacturing component she described as standardized, efficient and scalable, she visited a shop floor expecting to see her design working smoothly.
“I saw something that no report would have ever captured. The people responsible for loading that perfect part into the machinery were physically beating it in with a hammer, and that hammer was not part of the process,” she said.
“These weren’t people trying to make the process difficult. They were trained technicians with years of experience,” she said. They were the true experts, desperately trying to make a solution work within constraints that the designers had never considered. Those designers had been working from computer simulations and had never visited the fixture in person.
Rather than defending the standard, Miller brought the technicians together and asked one question: if you could change one thing, what would it be? The group combined their tools, lived experience and expertise to arrive at a solution that was better than the original design. That solution was subsequently rolled out across three other sites that had been quietly struggling with the same problem.
An audience member asked how to manage situations in which employees know a disruption is coming but the details have yet to be announced. She said starting the conversation early is critical. Even when it is too late to alter the solution, giving people a voice in how it will affect them creates a sense of inclusion and makes the transition easier to accept.
On the question of cultural differences, she drew on her global experience to note that not all workforces respond to change in the same way. Her colleagues in Asia tend to want more detail and more of the underlying logic. Americans want the backstory and the why. German colleagues want facts, clear cause-and-effect and a concrete sense of the reward.
Taking time to understand not just the individuals involved but the culture in which they operate is, she said, itself part of the adoption equation.
As AI transforms industries at an accelerating pace, Miller’s framework points to a persistent gap between what technology can do and what organizations actually manage to change, and suggests the solution lies less in better tools than in better listening.