What becomes scarce when everything is abundant?
Every economic system you were taught to navigate was designed around a single assumption: there isn’t enough to go around.
Not enough jobs, not enough capital, not enough opportunity, not enough room at the top. Your entire career strategy, your financial planning, your sense of what makes you valuable in a market... all of it was shaped by that assumption. Compete harder. Specialize deeper. Protect your position. Accumulate while you can.
That assumption is breaking apart. Not in some distant, theoretical future. It is breaking apart right now, in ways that most people won’t recognize until the transition is already behind them.
Here is where we’re standing in early 2026.
AI is compressing the cost of production, knowledge, and distribution across every industry it touches. The things that used to be expensive are becoming cheap. The things that used to be rare are becoming common. The constraints that shaped the careers of everyone who came before you are weakening by the quarter.
Manufacturing costs have dropped 40 to 60 percent in sectors where AI optimization is deployed. Research that required teams and months now happens in minutes. A single person with the right tools can produce what used to require a department of twenty.
These are not projections about tomorrow. They are the conditions you are operating in today.
Sam Altman, the CEO of OpenAI, framed this trajectory in terms worth sitting with. He wrote that by 2035, any individual should be able to marshal intellectual capacity equivalent to what all of humanity possessed in 2025. He described a future defined by massive prosperity, where the ability for one person to accomplish dramatically more than they could even five years ago will be, in his words, a striking change. He acknowledged that the long-term changes to our economy will be enormous, while emphasizing that agency, willfulness, and the ability to decide what to do in a constantly shifting world will hold tremendous value.
Elon Musk went further at the World Economic Forum earlier this year. He described a near future where ubiquitous AI combined with ubiquitous robotics creates an economic expansion that has no historical precedent. His framing was blunt: you cannot maintain a system where essential work falls only to some people while abundance is theoretically available to all. The two are incompatible, and one of them gives way.
The economic orthodoxy of the last three centuries insists that abundance is a dream and scarcity is the permanent condition. The people actually building the systems driving this transformation say the opposite. One of those perspectives is wrong. The question that should concern you is which one, and whether you have positioned yourself for the answer.
Here is what most people miss about this shift.
When they hear “post-scarcity,” they picture utopia. Everything is free, nobody works, the whole picture has a science-fiction glow to it. That is not what is happening, and misunderstanding this is where most people’s thinking goes off the rails.
Post-scarcity does not mean scarcity disappears. It means scarcity reorganizes. The constraints do not vanish from the system. They migrate to a different part of it.
A research paper published through SSRN late last year made this distinction sharper than anything I have encountered in mainstream commentary. The author argued that AI delivers what he termed “technological abundance,” meaning cost compression and capability expansion at a scale we have never seen. He then drew a line that most people miss entirely: technological abundance is not the same as economic abundance. The costs drop and the capabilities expand, yet new bottlenecks form at different layers. Infrastructure, institutional trust, organizational know-how, enforcement capacity. The scarcity does not die. It moves to a different floor of the building.
This is the part that most commentary on AI gets completely wrong. The mainstream frames this as a binary: either AI makes everything abundant and we all win, or AI takes all the jobs and we all lose. Neither framing captures what is actually unfolding. The real story is one of migration. Value is moving from the layers AI can handle to the layers it cannot. If you understand where that migration is headed, you can position yourself in its path. If you do not, you will spend the next decade optimizing for a game that no longer rewards the moves you were taught.
Peter Drucker saw this migration decades before AI made it visible.
In 1993, he wrote that knowledge had become the central resource of economic life. Not a resource among others, but the resource. He warned that knowledge only yields value when it is applied toward results, and that it must be improved and challenged constantly, or it vanishes.
Over thirty years later, the vanishing he warned about is unfolding in real time, though not in the way most people would expect. Knowledge is not disappearing. Its scarcity value is. When any person, or any machine, can access domain expertise instantly, knowledge on its own stops functioning as competitive advantage.
An essay published through the Peter Drucker Forum earlier this year extended this line of thinking considerably. The authors argued that we have crossed the boundary of Drucker’s original framework. The knowledge worker, the figure who defined the economic landscape of the 20th century, is no longer the leading edge. What is emerging in that role is someone the authors called “the Value Creator,” a person whose worth comes not from possessing knowledge but from transforming knowledge into new forms of value under conditions of uncertainty.
That distinction carries more weight than almost anything else in this newsletter. The economy of the last several decades rewarded knowledge possession: what you knew, what credentials you held, what expertise you could demonstrate. The economy taking shape right now rewards knowledge transformation: what you can build with what you know when the rules are ambiguous and the path forward is not obvious.
There is a case study that illustrates this migration better than any theory.
In 2016, Geoffrey Hinton, one of the founding figures of deep learning, made a public statement that received widespread coverage. He told people to stop training radiologists because AI would outperform them entirely within a matter of years. By 2017, a model called CheXNet was already beating radiologists on specific diagnostic benchmarks.
That was a decade ago.
Today, demand and wages for radiologists are at all-time highs.
The models did improve. The narrow technical predictions were, in a strict sense, accurate. Yet the humans became more valuable, not less. The reason is that real-world medical imaging involves variation, ambiguity, liability, patient context, and clinical judgment that no current system handles autonomously. AI took over the volume work, the screening, the pattern matching at scale. The radiologist became the person who handles everything requiring judgment under uncertain conditions.
The commodity layer got compressed. The premium layer expanded. This same dynamic is repeating in every industry AI touches. Stock photography collapsed under AI image generation, while editorial photographers who create emotionally resonant, conceptually distinctive work saw their rates climb. Basic legal research is being automated at speed, while lawyers who navigate ambiguous, high-stakes negotiations are commanding higher fees than ever. Content production costs are falling through the floor, while creators who have built genuine trust with their audience are charging more.
The pattern is consistent enough to treat as a principle: when AI compresses the commodity layer of any field, the premium layer, the layer built on human judgment, creativity, and trust, expands to absorb the value that was released.
So here is the question that changes your strategy for everything.
What becomes truly scarce when traditional resources are abundant?
When production is abundant, curation becomes scarce. When information is abundant, trust becomes scarce. When content is abundant, authenticity becomes scarce. When AI handles most tasks, human creativity and judgment become scarce. When access to tools is universal, the ability to know what to build with them becomes scarce.
This is the new scarcity. Not physical resources, not information, not production capacity. The new scarcity is trust, creativity, judgment, and authentic human connection.
If you orient your skills, your business, and your career around these new scarcities, you are not simply adapting to a transition. You are positioning yourself at the center of where value flows next.
Drucker wrote something in 1985 that keeps resurfacing in my thinking as I watch these shifts accelerate from the inside. He said that the greatest danger in times of turbulence is not the turbulence itself, but to act with yesterday’s logic.
Most people are still acting with yesterday’s logic. Not because they lack intelligence or awareness. Because the old logic worked so effectively, for so long, that it stopped feeling like a strategic choice and started feeling like truth. It was never truth. It was always strategy, a strategy adapted to specific conditions. Those conditions are now shifting under everyone’s feet.
Most people will hear this argument and nod along. It makes intellectual sense. Then they will go back to optimizing for the old game the next morning.
They will continue grinding to accumulate skills that AI is already absorbing faster than any human can keep pace with. They will continue chasing volume in a world that is drowning in volume. They will continue competing on speed and output against systems that will always be faster and more prolific than any person alive.
The problem is not a lack of understanding. The problem is that their entire operating system, the mental model they use to make decisions about career, time, and energy, was installed during the scarcity era. That operating system is still running in the background, still whispering the old instructions: specialize narrowly, produce more, compete harder, protect your position. The operating system itself has become the liability.
The replacement is not complicated, but it requires a different kind of honesty than most people are accustomed to.
You have to ask yourself what you are actually good at. Not what your resume says, not what your job title describes, but what you do that creates value in ways that cannot be replicated by a system running on statistical prediction and data matching.
For most people, the answer is closer than they expect. It lives in the judgment calls you make that no playbook covers. In the way you read a room, a conversation, or a situation and understand what is really happening underneath the surface. In the ability to take disconnected information from different domains and synthesize something that did not exist before.
These qualities are not soft skills being polite about their irrelevance. In a post-scarcity economy, these are the hard skills. These are the genuinely scarce resources.
I lead programs building AI models at Google. I work inside these systems every day. I see what they can do, and I see, with equal precision, what they still cannot do. The gap between AI capability and human capability is narrowing rapidly on the production side: generating content, analyzing patterns, executing defined tasks. On the judgment side, the creativity side, the empathy and relational side, that gap is not narrowing. It is widening. That widening gap is where value lives now and where it will increasingly concentrate.
Altman himself acknowledged this dimension in a conversation with Adam Grant. He observed that the mutual care between people, the degree of attention we pay to each other’s actions, and the deep human desire to interact with other humans will become more important in the age of AI, not less. He described AI as an extraordinary tool while making the point that the people directing that tool, their intentions, insights, and empathy, will only become more precious as the tool grows more capable.
There is a practical dimension to this that extends beyond philosophy and into how you allocate your time and energy starting now.
The old economic model rewarded ownership. Buy assets, stockpile, lock in your position. When things are genuinely hard to get, that instinct serves you well. In an abundance economy, ownership becomes weight. It is inflexible, it ties your resources to depreciating structures, and it limits your ability to move when conditions shift, which they will, repeatedly. What is replacing the ownership model is access: computing power on demand, design tools on demand, manufacturing capacity on demand, professional services on demand. The individuals and companies that thrive in the emerging landscape will not be the ones who own the most infrastructure. They will be the ones who maintain the most flexibility to adapt as the environment continues to change.
The same principle applies to your career architecture. Deep specialization in one narrow domain that AI might absorb entirely is a wager against the direction things are moving. Transferable judgment, precise communication, systems-level thinking, and the ability to direct AI tools as force multipliers represents a wager in its favor. The person who can think across systems, communicate with precision, solve ambiguous problems, and use AI to multiply their output is not being replaced by any of this. That person is becoming the most valuable participant in any organization, any market, any economy being reshaped by abundance.
There is one more dimension worth sitting with, and it is the one that receives the least attention despite carrying perhaps the most consequence.
When AI floods the world with content, information, and media at volumes no previous generation could have imagined, attention does not become abundant alongside everything else. It becomes the most constrained resource in the entire system.
We are approaching a world with more content than any human could consume in a thousand lifetimes. The bottleneck is no longer production. It is trust. It is genuine human connection. It is the willingness of another person to give you their time and their focus because they believe you have something real to offer, something that was not generated on a whim and published without thought.
The first iteration of the attention economy was built on volume. More eyeballs, more impressions, more output. That model is reaching its natural limit. When everyone can produce unlimited content with minimal effort, volume stops functioning as competitive advantage. What is replacing it is something fundamentally different: deep engagement over broad reach, authenticity over production polish, community and earned trust over viral mechanics.
If you are building anything right now, whether it is a career, a body of work, a business, or a reputation, this is the shift to absorb completely. The people who define the next decade will not be the ones who produce the most. They will be the ones other people actually trust. That is a fundamentally different game from the one most people are still playing, and the sooner you recognize the difference, the sooner you can stop wasting energy on moves that no longer compound.
Here is what I want to leave you with.
We are not waiting for a post-scarcity economy to arrive. We are already standing in the early innings of one. The economic assumptions that most people operate under, compete for limited resources, specialize narrowly, optimize for the system as it currently exists, are becoming liabilities faster than they are becoming visible.
The shift runs in one direction. From scarcity thinking to abundance positioning. From producing to curating. From volume to depth. From rigid infrastructure to adaptive systems. From competing on what AI does well to investing in what AI cannot touch.
You do not need to see the entire future with precision. You need to see the direction of the shift and begin moving accordingly.
The question is not whether this transition is happening. It is whether you will be positioned on the right side of it, or whether you will find yourself scrambling to adapt after the rules have already been rewritten around you.
Until next Monday,
Guney