The AI Workplace Isn’t Coming, It’s Already Here.

First, we’re fascinated by it, then we’re suspicious of it and eventually we wonder how we ever lived without it.

McCrindle’s new research into AI, consumers and the workforce suggests we’re somewhere between the second and third stages right now. Australians are using AI at a remarkable rate, but our confidence in what it means for us is lagging behind. We’re not simply living through an AI revolution. We’re living through an AI contradiction – embracing the technology while worrying about what it will do to us.

The numbers are striking. McCrindle found that 63% of Australians use AI in their personal lives at least monthly, while 54% use it at least weekly. Among Gen Z and Gen Y, weekly use rises to 66% and 65% respectively. And yet 70% of Australians see AI as more of a threat than a tool to society.

That’s quite a contradiction. We’re asking ChatGPT to write emails, plan holidays, summarise documents and help us think through problems while simultaneously wondering whether we’re handing too much of ourselves over to machines. Perhaps that’s because adoption and trust aren’t the same thing. We can find something incredibly useful without believing it’s necessarily good for us.

McCrindle’s AI Trust Index puts Australia’s overall trust score at just 44 out of 100. The most positive area is behaviour – how confidently people are actually using AI – with a score of 53. But the lowest score is the future domain, at just 36, reflecting anxiety about work, creativity, relationships and future generations. In other words, we’re getting better at using AI than we are at imagining what AI might do to us.

And the workplace is where that contradiction gets serious.

Technology has always changed work. The Industrial Revolution changed what work looked like, computers changed the office, the internet changed communication and smartphones changed our expectations about availability. But McCrindle identifies something different about AI: previous technological disruption often affected particular industries, whereas AI has the potential to disrupt almost every industry at roughly the same time.

There’s another twist. Historically, technological disruption could hit experienced workers hardest because their expertise was tied to established ways of working. This time, younger workers may be more exposed. McCrindle reports that entry-level job postings have fallen by 29 percentage points since January 2024, while roles requiring more than 10 years’ experience haven’t experienced the same decline. Forty-five percent of Australians are extremely or very concerned that AI will reduce entry-level career opportunities.

That creates a problem we haven’t really solved yet, because junior jobs aren’t just jobs. They’re where people learn how organisations work. They learn how to write, how to present, how to deal with difficult colleagues, how to make mistakes without bringing down the company, how to read a room, how to negotiate and how to build relationships. They become the experienced people we need later.

If AI removes all the entry-level work because it can do it faster and cheaper, where does the next generation of experienced workers come from? You can’t have a senior workforce without giving people somewhere to start.

There’s an uncomfortable irony here. We often tell young people they need experience to get a job, but if AI removes the jobs where they gain that experience, we’ve created a rather impressive circular problem. You need experience to get the job. You need the job to get experience. And now you may need to compete with AI to get either.

McCrindle found that 46% of Australians are extremely or very concerned that relying on AI for basic tasks will hinder the development of future leaders. That should be a leadership issue, not simply an HR issue, because organisations are understandably attracted to the immediate benefits of AI. It saves time, reduces repetitive work, produces a first draft in seconds, analyses enormous amounts of information and can make a small team feel considerably larger.

But organisations also need to ask a slightly harder question: what are we sacrificing in order to achieve that efficiency?

There’s another fascinating shift happening. People aren’t simply waiting to see what AI does to their careers. They’re preparing themselves. McCrindle found that 63% of Gen Z and 59% of Gen Y are taking action in response to concerns about AI-driven job losses. Some are keeping up with how AI is being used in their industry, others are researching careers they believe are more resistant to AI and some are preparing financially for the possibility of losing their jobs.

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That could change the relationship between employees and employers. The next generation of workers may be less interested in staying with an organisation simply because it offers a traditional career path. They may increasingly ask, “Will this organisation help me remain relevant?”

That’s a very different proposition, and the best employers may increasingly be the ones that don’t just offer employment but offer continual learning.

One of the more interesting findings is that Gen Y is emerging as the “hero” of AI integration. McCrindle found that 46% of Gen Y workers frequently look for opportunities to redesign their workflows, compared with 39% of Gen Z and 23% of Gen X. That matters because the biggest productivity gains may not come from simply asking AI to do more tasks. They may come from redesigning how work gets done.

AI isn’t necessarily about replacing a task. It’s about questioning whether the task needs to exist in its current form at all.

That’s a much bigger idea for anyone working in communications, marketing, HR, education, management or pretty much any knowledge-based profession. The question isn’t simply, “What can AI do?” It’s, “What could we do differently if AI handled the things it is genuinely good at?”

That opens up a much more interesting conversation, because there’s a danger in making everything efficient.

This is where McCrindle’s research becomes more than another discussion about productivity. There’s a warning about what happens when efficiency becomes the only measure of success. The researchers use the phrase “cognitive surrender” to describe the danger of outsourcing too much of our thinking to AI.

I think this might be one of the most important ideas in the entire report.

AI can give us back time, but what do we do with that time? If we use it to think more deeply, develop ideas, build relationships and do more meaningful work, that’s a win. If we use it simply to produce more content, more emails, more meetings and more mediocre PowerPoint presentations, we’ve missed the point.

We haven’t made work better. We’ve just made it faster.

And nobody ever put “faster mediocrity” on their organisational strategy.

There’s also a temptation to think that AI makes human skills less important. The research suggests almost the opposite. As AI becomes better at producing information, the ability to judge that information becomes more important. As AI becomes better at writing, having something worth saying becomes more important. As AI becomes better at automating transactions, genuine relationships become more important. As AI becomes better at producing answers, knowing which questions to ask becomes more important.

And as AI makes communication easier, trust becomes harder to manufacture.

That’s particularly relevant given McCrindle’s finding that 78% of Australians would rather prioritise privacy over personalisation, a figure that has risen significantly from 59% in 2021. Consumers want convenience, but they don’t want convenience at any price. They want personalisation, but they also want privacy. They want AI to save them time, but they don’t necessarily want it to replace human relationships.

Almost half of Australians believe AI adoption is negatively affecting human relationships. And here’s the fascinating part: McCrindle’s research also found that the workplace is the place Australians most commonly identify as providing meaningful community and connection.

So the workplace isn’t simply where we’re employed. For many people, it’s where we belong.

That means the future of work isn’t only a question about jobs. It’s a question about community.

Perhaps the most useful way to think about AI isn’t as the end of work, but the end of some kinds of work. Repetitive work will increasingly disappear. Transactional work will increasingly be automated. First drafts will increasingly be machine generated and basic research will increasingly be assisted by machines.

Which leaves us with a rather interesting challenge: what will we do with ourselves?

If we get this right, perhaps the answer is better work – more time to think, more time to create, more time to mentor, more time with customers and more time solving genuinely difficult problems. More time doing the things that require judgement, empathy and imagination.

But that won’t happen automatically. We have to design for it.

And that may be the biggest lesson from McCrindle’s research. The success of AI won’t ultimately be measured by how much work we automate. It will be measured by whether the technology helps people do better work without making us less human in the process.

The AI workplace is already here. The question now isn’t whether we can adapt to it. It’s whether we can shape it.

And perhaps, in the end, the most important thing AI can give us isn’t a more efficient workplace.

It’s the opportunity to decide what a genuinely human workplace should look like and how we want to shape the future of work.