"You won’t lose your job to AI…" Debunking the biggest myths about artificial intelligence at work

This is the granddaddy of AI fears. And it’s been around for a while. You can probably trace it back to English textile workers in the early 1800s, the original Luddites, who thought automated looms were coming for their jobs. 

Yes, AI is automating certain tasks – but automation has always been part of the workforce. What AI does, or at least what it should do, is shift the demand from repetitive, low-value work to higher-order, human-centered roles. According to the World Economic Forum, while 85 million jobs may be displaced by AI, 97 million new roles could emerge that are better suited to the new division of labour between humans, machines and algorithms. 

As Ginni Rometty, former CEO of IBM, put it: “AI will change all jobs once it is in the workflow, and that is the most meaningful kind of AI. Yes, some jobs will be replaced, but that is a red herring. It’s about getting people to work at the intersection of this.

“This is all a game about skill, and having people with the right skills.”

That’s something we’ve always believed here at RMIT Online.  

Rather than replaceent, the real trend we’re seeing is job transformation. A data analyst, for example, might spend less time cleaning spreadsheets and more time interpreting patterns and advising leadership. That’s a shift, not a disappearance.

AI is making waves across all industries, not just tech. But that doesn’t mean only coders and engineers are safe. In fact, tech leaders have already flagged that low-level coding jobs could be at risk. And soon. 

The fact is, with the rise of AI, creative, strategic and emotionally intelligent roles are becoming even more valuable. Because they still represent a level of human expertise untouched, and unmatched, by machines. Things like design and branding, education and counselling, sales and customer experience, people and project management. These fields should all be getting a boost as AI takes over more technical, mundane, data-heavy tasks. 

The future likely belongs to those who can work alongside AI – not just those who build it.

It’s tempting to think of AI as this hyper-logical, mistake-free machine – but it’s only as good as the data it’s trained on. And if you’ve ever tried to verify quote-unquote “quotes” from ChatGPT, you’ll know all about AI mirages. 

The fact is, large data sets are often riddled with bias. And so are any AI models trained on those datasets. In the last few years, AI has made headlines for reinforcing discrimination in hiring, facial recognition, and even credit scoring.

That’s why human oversight is still essential. We need people to audit these algorithms for bias, set ethical frameworks, interpret the outcomes in context, and make final calls based on lived experience. 

As the saying goes: AI doesn’t have a moral compass; it borrows yours

There’s a lot of pressure on businesses and professionals to adopt AI instantly. Like, yesterday. But integration and digital transformation has never been one-size-fits-all. The best results come from intentional, phased, human-led adoption. 

It’s like Dan Clancy, the CEO of Twitch, said at SXSW Sydney: there’s a fundamental difference between human and machine intelligence. One wants to connect, while the other just wants to optimise. “I think we undervalue the complexity and sophistication of human intelligence,” he said, “and what we can do in this world.” 

Jumping on the AI bandwagon without understanding the goals, risks, or fit for your work can do more harm than good. The smartest organizations are already asking:

• What problem are we solving?

• Is AI the right tool?

• How will it support and empower, not replace, our team?

Just like any other tool, success with AI is about how you use it. Poor AI integration is arguably worse than none at all. Without the right success metrics, goals, training and stakeholder buy-in, artificial intelligence is just another meaningless system or layer of tech bureaucracy.  

Instead of fearing AI, the real challenge is preparing for a new kind of workplace.

That means:

• Upskilling: Build your competencies in areas like critical thinking, communication and digital literacy.

• Co-creating: Learn how to use AI tools like copilots, assistants and analytics platforms to enhance and speed up your work.

• Humanizing: Double down on the qualities that make us uniquely human – curiosity, empathy, leadership and imagination. All the usual soft skills. 

AI doesn’t have to be a threat to your job. Think of it instead as a catalyst for change. There are so many great AI tools emerging onto the market that, odds are, one of them can help you do your job better, faster, more efficiently.  

The biggest danger isn’t that AI will replace you; it’s that you won’t adapt to the changes it brings. The future of work will belong not to those who fear AI, but to those who partner with it – guiding it with human values, emotional intelligence and strategic purpose.

In other words, the robots aren’t coming for our job. They’re coming to our job. The rest is up to us.