The job displacement conversation is missing the point—it's not about whether AI will replace workers, it's about how fast you can adapt to what comes next.

Let's Stop Pretending This Isn't Happening

"If there is a fear that AI will replace jobs. It's already, it's already happening. It's not a fear, that's a fact. And ignoring that is ignoring reality." The job displacement has already begun, and pretending otherwise is just delaying the inevitable conversation about what comes next. Google and other tech companies have been refreshingly honest about this. "Google and other companies, they have publicly, Google and some other companies, they've mentioned publicly already that up to thirty percent of their code is created by AI." Thirty percent. That's not a pilot project or an experiment—that's a fundamental shift in how work gets done. The question isn't whether AI will replace jobs. It's which jobs, how fast, and what replaces them. And the answer is more complex than the doom-and-gloom headlines suggest.

The Junior Developer Problem

Here's what's actually happening in the trenches: "I would say to my experience, especially people that are junior because those are easier to replace." Junior positions across multiple industries are becoming automated first. Think about it logically. Junior roles typically involve tasks that are:

• Repetitive and rule-based

• Well-documented with clear procedures

• Lower-stakes if mistakes happen

• Easier to replace without major business disruption

  
  

These characteristics make junior positions perfect candidates for AI automation. The career ladder that used to start with "paying your dues" in entry-level roles is being fundamentally restructured.

The Productivity Multiplier Effect

But here's where the story gets interesting: "On the other hand, as well, you have a lot of companies that are creating a lot of things that wouldn't have been created if there wasn't for AI, because AI now has made it viable for them." AI isn't just replacing human work—it's making new types of work economically viable. "So the difference in between input versus output is just becoming greater and greater and greater. We can look that as a productivity measure." A single developer can now build applications that would have required a team of five. A marketing professional can create campaigns that would have needed an entire agency. A designer can produce variations and iterations at a pace that was previously impossible. This productivity multiplier effect creates opportunities for new projects, new services, and new business models that weren't economically feasible before AI.

The Transition Phase Reality

"So I think the immediate impact will be, yes, a lot of people will be displaced of their jobs, but the long term impact will be that the expectations of what one human being can produce will also be higher." We're in a transition phase, and it's going to be messy. In the short term, displacement will outpace job creation. Some people will lose their jobs before new opportunities emerge. Some industries will contract before they expand in new directions. But the long-term trend is clear: "Therefore companies will be able to grow more and hire more people because they can adopt. So I think we are in a transitional phase and the best that we can do is try and is trying to go after the right skills to be competitive and relevant to the market."

The Skills That Matter Now

So what are the "right skills" to develop? Based on what we're seeing in the market, they fall into several categories: AI Orchestration Skills: The ability to effectively prompt, guide, and refine AI outputs. This isn't about being technical—it's about understanding how to get quality results from AI systems. Strategic Thinking: As AI handles more execution, humans need to focus on strategy, planning, and decision-making. The question shifts from "how do we do this?" to "what should we do?" Creative Problem-Solving: AI excels at pattern recognition and known solutions. Humans excel at novel approaches and creative connections between disparate ideas. Emotional Intelligence: Customer relationships, team management, and complex negotiations still require human empathy and understanding. Quality Control and Judgement: As AI produces more content and solutions, the ability to evaluate, refine, and improve those outputs becomes critical.

The Incumbents Are in Trouble

"But one thing that AI has done or is doing now is allowing small and medium businesses to punch way above their weight." The established players who built their competitive advantages on resources and scale are discovering that AI has democratised many of their traditional strengths. "Because what's going to happen is that they will see much smaller companies with much smaller teams outdoing and outpacing everything that they do. And the incumbents are at the incumbents today. I think they are at a much greater risk than any incumbent that there has ever been before." A two-person startup can now compete with capabilities that previously required a team of twenty. The barriers to entry in many industries are collapsing, creating opportunities for nimble competitors to challenge established players. "So being a big company today with AI definitely doesn't guarantee that it's still going to be in the same position... But with AI, the pace of innovation is much, much faster. And it's just more democratic in terms of you can do a lot more with smaller teams, the right tool and creativity than you once could do."

The New Job Creation Engine

New jobs are already emerging, though they look different from what we're used to: AI Trainers and Prompt Engineers: People who specialise in teaching AI systems and optimising their performance for specific use cases. AI Ethics and Compliance Officers: As AI becomes more widespread, companies need people who understand the legal, ethical, and regulatory implications. Human-AI Collaboration Specialists: Professionals who design workflows that optimise the combination of human and AI capabilities. AI Product Managers: People who understand both the technical possibilities and business applications of AI tools.

These roles didn't exist two years ago. They're growing rapidly, and they pay well because the skill set is rare.

The Adaptation Imperative

The harsh truth is that adaptation isn't optional. "It is really difficult to get the skill set that we need to keep up with technology evolving." The pace of change is accelerating, and the skills that make you valuable today might be obsolete in two years. But this also creates opportunity. "Some of them benefit from it because they don't need to have to invest so much money, time and energy into catching the next shiny new thing. But on the other hand, they are exposed to more risk." You can choose to be a fast follower rather than a first adopter. You can let others make the expensive mistakes and then learn from their experience. But you can't choose to ignore the changes entirely.

The Historical Perspective

Every major technological shift has created job displacement followed by job creation. The industrial revolution eliminated agricultural jobs but created manufacturing jobs. The computer revolution eliminated typing pools but created the entire software industry. AI is following the same pattern, but faster. The displacement phase is measured in years, not decades. The new job creation is happening simultaneously, not sequentially. The winners will be those who can navigate this transition period effectively—upskilling fast enough to stay relevant while positioning themselves for the opportunities that are emerging.

What This Means for You

If you're reading this, you're probably not a junior developer whose job is at immediate risk. But you're also not immune to these changes. The question is: are you preparing for the transition, or are you hoping it won't affect you? The smart move is to start experimenting with AI tools in your current role. Understand how they can amplify your capabilities. Identify which parts of your job could be automated and which parts require human judgment. Position yourself to be the person who knows how to get the best results from human-AI collaboration. The jobs AI destroys will be tasks. The jobs AI creates will be roles. The difference matters, and it's where your opportunity lies.