Hey friends,

I spoke to someone who has spent years getting very, very good at one job. Not a glamorous job. Not a headline job. The kind of job most people never notice until it is gone.

They told me, quietly, that they were worried. “What happens to my job if AI can do what I do?”

That question has been sitting with me ever since, because it is no longer theoretical. The job shed is real, it is spreading, and most people are still treating it like background noise.

We talked about the big news coming out of Amazon, with figures being discussed like 30,000 roles linked to AI. We also discussed reports like Tata Consultancy Services in India laying off around 80,000 people, even though they had a reputation for being a “job for life” employer.

And it is not just tech. There are estimates floating around that point to hundreds of thousands of jobs being cut globally across sectors like government, retail, manufacturing, logistics, finance, media, and more.

Here is the part that worries me most. For years, we all heard the comforting line: AI will not take your job, people using AI will. I believed that at first too. But the obvious question is: where are those new jobs right now?

If the layoffs are happening at scale, and the “new jobs” are coming, why are so many people still looking around wondering where the door went?

Every major shift in history created disruption, then new industries, then new work. Electricity created an entire ecosystem of engineers, operators, builders, manufacturers. The internet created websites, digital services, new platforms, and whole new careers.

Even mobile apps created jobs everywhere, including ones that required humans in the loop. Uber still needed drivers. Airbnb still needed hosts. Entire economies formed around those platforms.

But AI is not just a tool. AI is becoming a doer. That is the shift.

If you can generate the design, write the copy, draft the legal document, summarise the case law, build the presentation, write the code, analyse the spreadsheet, and run parts of customer service, the number of humans required to produce the same output changes dramatically.

And that is before we even get to what comes next. We used a simple example in the conversation. My wife drives a Tesla. The full self drive capabilities are improving fast. In the US there is movement toward unsupervised modes. Then you hear ideas like robotaxi mode where the car can earn money while you are not in it.

That is not just a cool feature. That is a direct threat to millions of people whose income depends on driving, delivery, transport, and logistics. The same pattern is now hitting knowledge work too.

From a pure business perspective, if a company can maintain quality with fewer people, it is hard to argue that they will choose higher costs out of kindness.

Most consumers do not ask whether a product or service was delivered by a human or a machine. They ask one thing. “Was it good?”

So the temptation is obvious: reduce staff costs, keep output steady, boost profits. But there is a second question that matters just as much. What happens if you get it wrong?

We talked about CommBank letting customer service staff go, then hiring them back. Whatever the exact cause was, it highlights something important: rushed automation can backfire.

AI can go rogue. AI can be wrong with confidence. AI can create real-world damage when there is no oversight.

Poor implementation is expensive. It creates customer problems, brand problems, legal problems, and operational chaos.

So yes, businesses will automate. They have to if they want to stay competitive. But the ones who do it recklessly will learn the hard way.

Even if a company “wins” in the short term by cutting costs, there is a question that sits underneath all of this. If money becomes concentrated into fewer hands, and less money circulates through the broader economy, who is buying the stuff? If unemployment rises and incomes fall for a large portion of society, the customer base shrinks.

That is not politics. That is basic economics. And the hardest part is this: there is no single governing body controlling the direction of AI. Every major player is looking out for themselves.

We talked about the race happening between companies and figures like Elon Musk, Sam Altman, Microsoft, Google and others, all pushing toward more powerful systems, more capable agents, and eventually super intelligence.

The incentives are clear. Whoever gets there first holds enormous power. But what is the incentive to slow down and ask what it does to society? That is the predicament.

One thing I feel strongly about is transparency. In our organisation, we have adopted a transparency charter. We say no to projects where organisations are not willing to be open about the impact AI will have on humans.

If you are rolling out a program designed to replace roles, people have a right to know. Not because it will stop the change. But because trust matters.

You cannot ask people to give you their best work while quietly building the system that removes them, without a conversation. That silence creates fear, resistance, and long-term damage.

And this is not just a business responsibility. Government has a role here too. If leaders do not understand what is coming, they need to get curious quickly. Talk to technologists. Talk to futurists. Talk to the people building it and deploying it.

Then inform people. Educate people. Up-skill people. Not with vague statements, but with tangible pathways into real work.

I said something in the conversation that I want to repeat here because it matters. The next five years are likely to be extremely chaotic. Not because people are lazy. Because the technology is racing ahead and the systems around it are not prepared.

We have people trained for knowledge work. Excel work. Admin work. Basic analysis work. Standardised process work. At the same time, we have shortages in essential human services like healthcare, nursing, aged care, childcare, psychology, and emergency services.

Reskilling does not happen overnight. But here is the hopeful part. AI is also fantastic at training people. In many cases, the same force disrupting work can become the bridge into new work, if we use it properly.

I do not have a perfect solution for everyone. But I do have a clear direction for anyone who wants to stay employable in the messy middle. Move toward being a generalist.

For a long time, specialists were rewarded because businesses were built on silos. You had a content writer, a designer, a strategist, a coordinator, a producer. Everyone had a narrow lane.

AI is smashing those walls. The person who thrives is the one who can think across the workflow.

In marketing, that might mean one person who can shape the message, draft the content, generate the visuals with AI, understand distribution, and tie it back to commercial outcomes.

In law, it might mean someone who can use AI tools to remove grunt work, but also understands strategy, client psychology, negotiation, risk, and how to make themselves genuinely useful.

In any field, the question is simple: If AI can do 60 percent of the tasks in your lane, what is the bigger value you can create above that?

Curiosity and imagination still matter. Problem solving still matters. Connecting dots across silos still matters.

People who widen their horizons and learn how to use these tools become the ones who lead teams that include both humans and AI. People who stay in one narrow function and hope the world stays the same are on a timer.

The easy win is cutting costs. The harder win is using AI to remove the grunt work and then redeploying your people into innovation, new ventures, and solving bigger problems.

Every industry has problems we have not solved. Banking, insurance, law, healthcare access, compliance, service delivery, public sector processes.

If you free up capacity, you can either shrink your organisation, or you can build new value. The companies that think beyond the spreadsheet will be the ones that survive long term.

This conversation can spiral into fear very quickly. We even joked about the Terminator future, because everyone is thinking it.

But fear does not help. Curiosity helps. Honest conversations help. Transparency helps.

If you are a business owner, ask yourself what happens to your people when you automate. If you are an employee, ask yourself what skills make you useful across the system, not just inside one task. If you are a leader in government, get close to the people doing real work in this field and start building pathways for citizens now, not later.

AI is here. It is accelerating. None of us are going to stop it. But we can choose whether we sleepwalk into it, or we face it with open eyes.

-Aamir

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