Synopsis
For years, the conversation around artificial intelligence has been remarkably predictable. We are told to use AI to save time, automate repetitive work, improve productivity, reduce operating costs, and free ourselves to focus on “higher-value activities.” None of this is wrong. In fact, businesses have been pursuing the same objectives through software, digitalisation and automation for decades. What has changed is the scale of what AI can now do. If our thinking remains limited to saving a few hours of work, we are underestimating the technology. I believe the more important question is no longer, “How can AI help me?” It is, “How much of me can AI replace?” If you are satisfied with protecting your current role, maintaining your present way of working, and avoiding disruption, this article may not be for you. This argument is meant for people who want to break through, even when that breakthrough requires them to dismantle parts of themselves that once made them successful.
1. The AI Conversation Has Become Too Comfortable
Much of today’s AI discussion is still based on an efficiency mindset. A company introduces AI so that employees can prepare reports faster, respond to customers more quickly, automate administrative work, or generate content in less time. The organisation celebrates because a task that previously required three hours can now be completed in thirty minutes. That is useful, but it is not yet transformation. The more disruptive question is what happens after we discover that a three-hour task only requires thirty minutes. Should the task continue to be structured in the same way? Should the same job description remain unchanged? Should the same number of people still be assigned to the same process? Should the same service continue to command the same price simply because that was how the industry operated in the past? AI forces us to confront uncomfortable questions because it does not merely make an existing process faster; it can make parts of that process unnecessary. This is why I believe we need to move beyond the language of productivity and begin discussing replacement, redesign and reinvention.
2. I Want AI to Replace What I Do Today
My personal approach is deliberately aggressive: I want to identify everything I currently do and determine how much of it can be replaced by AI, automation, software agents, knowledge systems or better processes. If I make ten decisions every day, I want to know whether five of them can be systemised. If I repeatedly answer the same questions, I want that knowledge captured so that people no longer need to wait for me. If I perform routine analysis, prepare documents, follow up with people, monitor progress or coordinate information manually, I want to know whether those activities can be handled without my direct involvement. The objective is not to make myself slightly more productive. The objective is to remove myself from work that no longer requires me. Many people are uncomfortable with this idea because their sense of professional value is closely connected to being needed. I see it differently. If a machine can take over something I currently do, then that activity should no longer be the foundation of my value. I would rather discover this myself than wait for a competitor, a younger generation, or a future technology to discover it for me.
3. There Is Value in Reaching the Point Where You Have Nothing Left to Do
One of the greatest fears surrounding AI is the possibility that people may eventually have less work to do. I understand that concern, particularly at a societal level, but at the level of personal growth I see another possibility. What happens when everything familiar has been taken away? What happens when the skills, routines and responsibilities that once occupied your entire day are no longer necessary? That moment can feel like a low point, but low points have an unusual ability to force human beings to change. When life is comfortable, there is little pressure to reinvent ourselves. When the old path disappears, however, we are forced to search for another one. I have always believed that some of the strongest growth comes after difficult falls. The deeper the fall, the more powerful the potential rebound can become, provided the person is willing to learn and rebuild. In that sense, I do not necessarily want AI to protect me from disruption. I want it to expose where I have become comfortable, where I have become dependent on yesterday’s strengths, and where I need to grow again.
4. Success Can Become a Trap When We Try to Preserve It Forever
People naturally want to protect what made them successful. A professional develops expertise and wants to preserve it. A company discovers a profitable business model and tries to extend it for as long as possible. An entrepreneur builds a process that works and becomes emotionally attached to it. The difficulty is that history does not guarantee relevance. A valuable skill can become a commodity. A premium service can become automated. A complex process can become a feature inside a software platform. A business model that once required a large team can eventually be delivered by a much smaller organisation supported by AI. This is why I do not believe in protecting a “magic sword” forever. No advantage remains permanent simply because it was once powerful. Growth requires the willingness to retire methods that still work before the market forces us to do so. In other words, the real discipline is not only learning new things. It is developing the courage to deliberately make old strengths obsolete.
5. The Higher-Level Role of Humans Is to Build Systems, Not Remain Trapped Inside Them
This principle is particularly important for entrepreneurs and leaders. In the early stages of a business, founders usually do everything themselves. They sell, manage customers, prepare proposals, solve operational problems, supervise employees, make decisions and respond to emergencies. This creates a dangerous psychological association: the more things I personally handle, the more valuable I must be. In reality, as an organisation grows, the opposite can become true. If every important process still depends on the founder, then the founder has become the organisation’s bottleneck. The next stage of leadership is therefore to convert individual capability into systems. Knowledge should become organisational knowledge. Decisions should become frameworks. Repetitive actions should become workflows. Monitoring should become automated. AI agents should be able to perform clearly defined functions within proper boundaries. The leader then moves upward, from doing the work to designing how work is done, and eventually from designing individual systems to designing an architecture of systems. That is where I see one of the most important possibilities of AI: it allows an individual to create and coordinate far more capability than one human being could personally execute.
6. If Machines Continue to Improve, Human Thinking Must Continue to Rise
The same principle becomes even more significant when we look beyond software. AI is increasingly moving into robotics, autonomous systems and physical infrastructure. Over time, the ambition will not simply be to create machines that perform isolated tasks. More advanced systems will increasingly monitor, maintain and coordinate other systems. Robots may assist in producing components used by other robots. Autonomous infrastructure may operate in environments where constant human presence is difficult or impractical. One can imagine future industrial or extraterrestrial environments in which machines draw power from available energy sources, inspect themselves, perform maintenance, manufacture tools and expand operational capacity with limited human intervention. Some people will look at such a future and see something frightening; others will see extraordinary human achievement. Either way, it raises the same philosophical question: if machines can perform an increasing share of execution, where should human value move? My answer is upward. Human beings must become better at defining purpose, creating direction, designing systems, making judgments, establishing governance and imagining possibilities that do not yet exist.
Conclusion: Breakthrough Requires the Courage to Become Obsolete
This is why I no longer find the phrase “use AI to save time so that you can focus on more valuable work” particularly inspiring. It is too safe. It assumes that our existing role should remain intact and that AI should merely make us more efficient within it. I believe we should be far more ambitious. We should use AI to challenge our current relevance. We should identify what can be automated and automate it. We should identify what can be systemised and systemise it. We should remove ourselves from activities that no longer require us and allow that temporary emptiness to force us to think again. The goal is not self-destruction for its own sake. The goal is continuous reconstruction.
My own question is simple: how much of Lukas Tan can I replace with AI today? When that version of me becomes unnecessary, I will have no choice but to create the next version. Then, one day, I should be willing to replace that version too. To me, this is what genuine growth looks like. We do not protect one version of ourselves forever. We repeatedly build, challenge, dismantle and rebuild.
That is also the kind of conversation I want to bring to organisations, businesses, universities and communities. I am not interested only in demonstrating the latest AI tools or teaching people how to complete yesterday’s work faster. Through my entrepreneurial journey, technology experience, failures, reinventions and the systems I continue to build, I want to challenge people to reconsider what makes them valuable in the first place.
If your organisation is looking for a conventional AI presentation, there are many people who can deliver one. But if you want a sharing session that challenges people to rethink their comfort zones, their careers, their organisations and the value of their own existence in an AI-driven world, that is a conversation I would be interested in having.
Because perhaps the most important question of the AI era is not how we can avoid being replaced.
It is whether, after everything replaceable has been taken away, we are capable of creating a stronger version of ourselves.