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1. AI is not entering an empty room. People's experiences, economic realities and cultural attitudes shape how they respond to technological change.
2. People can find AI useful while remaining uncomfortable about what it means for their jobs, identities and futures.
3. The organisations that succeed will not simply adopt AI fastest. They will solve meaningful human problems and bring employees, customers and stakeholders along for the journey.
1. AI is not entering an empty room. People's experiences, economic realities and cultural attitudes shape how they respond to technological change.
2. People can find AI useful while remaining uncomfortable about what it means for their jobs, identities and futures.
3. The organisations that succeed will not simply adopt AI fastest. They will solve meaningful human problems and bring employees, customers and stakeholders along for the journey.
Something is brewing in culture right now. Something new, but also familiar from a historical standpoint. Unease. Resistance. Contradiction.
The AI backlash is not simply a rejection of usefulness. People can use AI while still feeling uneasy about what it means for their work, identity and future. That tension matters for organisations because adoption data shows behaviour, but sentiment shows permission.
For years now, we’ve heard that AI is going to fundamentally change everything. Not slowly, but quickly. If people think their job is safe, they’re wrong. But in the same breath, people are told not to worry because everything will work out in the end.
This message would be unnerving during times of stability, but it’s particularly risky when it lands in an unstable culture already buckling under pressure.
Culture matters because it shapes how people make sense of change. The same innovation introduced at different moments in time can be met with excitement, resistance or indifference. AI is not arriving at a time when many people feel economically and socially secure. Against that backdrop, conversations about replacing jobs, increasing efficiency and automating work inevitably land differently.
Historically, Australia and Aotearoa New Zealand have enjoyed stronger social cohesion than many other countries, supported by stable governments, shared norms and some distance from global geopolitical tensions. Today, however, both countries are experiencing the same pressures on social cohesion seen across the globe.¹
This is driven, in part, by growing inequality. Many people no longer feel like they can achieve the basic goals of previous generations: a stable job, a home, enough money to support a family and the ability to take holidays for respite. It’s not a lot to ask for, but it feels increasingly out of reach.
As a result, many people don’t feel like they are making progress. New Zealanders’ perception of the progress they are making in life has significantly decreased compared to last year. TRA’s recent research found that the average rating dropped from 61% in April 2025 to 56% this year, reflecting a further dip in personal optimism.
Given this cultural backdrop, and the fact that AI is likely to affect many roles, it is unsurprising that people see the technology as a threat to their livelihood.
There is an ethos in Silicon Valley that people don’t want to work those “menial” jobs, so there should be little concern about replacing them. This reflects a naive assumption that the vast majority of people who rely on employment to survive – and thrive – will be comfortable losing work because it will all work out in the end. But the lived reality of the past few decades tells them otherwise.
A job offers more than a pay cheque. It provides routine, purpose, and connection. For many people, work is not only about income. It's also about identity, contribution and belonging.
This narrative is especially problematic when there is no clear political consensus on what comes next, should large-scale disruption occur, and no obviously viable solution being offered by many of the organisations creating this technology. If that lack of foresight exists in the countries where the technology is being built, it is especially unnerving for people in countries like Australia and Aotearoa New Zealand, which have limited influence over its trajectory.
People rarely resist technology for the sake of it. More often, they resist what they believe it might take away from them.
Despite the unease, fear and the backlash, many people are using AI.
AI adoption is accelerating across the globe.2 People are adopting it in their personal and professional lives – to get a task done quicker, to understand the cause of a symptom or to help navigate personal issues.
There are many beneficial use cases, and people are flocking to them. But usage does not equal smooth adoption for companies. People can find something useful while remaining uncomfortable about what it means for their future. Culture does not simply shape conversation. It shapes adoption.
People don’t want AI to take away their income, and they don’t want it to replace the people they love. Beneath much of the resistance are deeply human concerns about security and purpose. AI may be the technology of the moment, but the questions people are asking are timeless ones. Will I be okay? Will my children be okay? What kind of future are we creating?
That fear is feeding resistance, and it has implications for brands across the globe.
The resistance is real, it is growing, and it requires consideration from local and global brands. But this doesn’t mean the answer is to avoid AI altogether. Regardless of sentiment, progress will continue unless regulation or other intervention changes its trajectory. Brands cannot control all of that, but they can control how they proceed.
Move too slowly and you risk being left behind. Move too quickly and you risk internal and external backlash.
Businesses often adopt AI through one of two paths: jumping at it because competitors will, or proceeding with so much caution that they lock themselves into stagnation.
The problem with the first path is that moving quickly without understanding the readiness of internal and external audiences increases the risk of serious mistakes. In Aotearoa New Zealand, Huffer recently replaced a human model with an AI-generated version that closely resembled him – the backlash was swift and significant. The problem with the second path is that remaining competitive is not optional, and current economic pressures mean others will readily adopt solutions that promise greater efficiency and growth.
The path forward sits somewhere between these two paths. Organisations should consider AI adoption across products, services, operations and marketing, but not reactively. It should be in service of solving a real problem for employees, stakeholders or customers.
Efficiency and cost savings matter. But they should not be pursued without considering the impact on people, trust and the brand.
Sentiment should not be treated as a secondary concern. It is part of the environment that any AI product, service or output enters into. Ignore the signals from inside and outside your business, and the response may not be what you hoped for.
This doesn’t mean relying only on data uptake. Adoption by itself won’t tell you how something is being received, or what impact it may have on your brand. Understanding adoption data tells us what people are doing. Understanding sentiment tells us how they feel about it. Organisations need both. This requires proper listening and testing early on.
Start with the problem, not the technology. Look for the points of real friction in how the business works today, including the things that make life harder for employees or customers. This will surface opportunities where AI might actually help.
Not everything needs to be automated, just as not every inefficiency is worth a quick solve. If an application does not meaningfully improve something people already value, it is not solving a real problem.
Change can feel threatening when people do not understand what is happening, why it is happening or what it means for them. Start small, but with clear intent. Explain the purpose, build feedback into the process from the beginning and be prepared to change course based on how people respond.
Pushing ahead in the face of serious resistance may deliver a short-term result, but it can create longer-term damage to trust. Once that trust is lost, rebuilding it is much harder than taking the time to earn it in the first place.
Technology changes quickly. People don't.
Every innovation enters a culture that already exists. It arrives with hopes, fears, expectations and tensions attached to it.
Organisations that overlook this cultural context risk treating innovation as a technology challenge alone, when it has always been a human one.
The organisations that navigate this period most successfully will not necessarily be those that adopt AI first or fastest. They will be the ones that best understand the people experiencing it. Because people do not simply adopt technology. They decide whether they trust what it means for their future.
If your organisation is exploring how AI should show up in products, services, marketing or customer experience, TRA can help you understand the people it needs to work for. Learn more about our approach.
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