Don't Panic!—The AI Job Apocalypse Is Coming (But Humans Will Always Have Work)
With AI stealing jobs, we need to prepare for the Great Automation Event.
Two billion years ago, a new technology emerged that killed almost everything on Earth—and created the conditions for a sprawling new ecosystem of biological innovation.
The greatest cataclysmic event on Earth happened two billion years ago. Our planet teemed with life in ways unimaginable today. Ancient seas churned with organisms that had thrived for eons in a methane-rich atmosphere. These early inhabitants had perfected their existence, efficiently processing nutrients and reproducing in a stable chemical environment that had sustained life since its very beginning.
Then something changed. A new type of organism emerged—blue-green pioneers that possessed an unprecedented ability. They began harnessing energy in a revolutionary way, splitting apart water molecules and releasing a waste product into the atmosphere. At first, this byproduct seemed harmless, even negligible.
But as these revolutionary organisms multiplied, their toxic emissions accumulated. The invisible poison spread through oceans and atmosphere alike, fundamentally altering the planet's chemistry. For the established life forms, this was an apocalypse. The very air became lethal. Ancient species that had dominated Earth for millions of years began dying en masse, unable to adapt to the rapidly changing environment.
And yet, amidst this devastation, new life forms emerged—organisms that not only tolerated the toxic atmosphere but actually thrived in it. These survivors developed sophisticated mechanisms to harness the deadly gas, transforming poison into power. They grew larger, more complex, more energetic than their predecessor life forms ever could.
The toxic waste that had triggered the greatest extinction event in Earth's history became the foundation for an explosion of biological innovation and diversity that continues today. That deadly poison was oxygen.
Let's be thankful to the anaerobic organisms that dominated our planet before the Great Oxygenation Event (GOE). Without them, we'd never be here.
The Next Apocalypse?
We must now prepare for the Great Automation Event (GAE).
Welcome to my explorations at the intersection of AI leadership, algorithmic management, and the future of work. In this age of AI, I focus on how networked and decentralized organizations can thrive with agentic AI, gig work models, and new approaches to AI management. If you're curious about the evolution of networked organization structures and the role of gig workers in tomorrow’s economy, you’re in the right place. Subscribe to my Substack now.
The global panic about artificial intelligence stealing everyone's jobs has reached fever pitch. News articles report mass layoffs, and younger generations cannot find jobs. Tech evangelists breathlessly predict mass unemployment while economists scramble to model scenarios where machines make humans obsolete. But this hand-wringing misses the deeper story.
Yes, AI will transform work. Yes, entire job categories will vanish. We are facing a job apocalypse. But the idea that we're heading toward a jobless future betrays a fundamental misunderstanding of what it means to be human in an economic system—and why that humanity creates value that no algorithm can replicate.
I was already aware of two foundational arguments that contribute to this conversation. First, the concept of comparative advantage suggests that even if AI outperforms humans at everything, resource constraints will force the strategic deployment of AI where it delivers maximum value, leaving plenty of work for humans. Second, the scarcity principle: as AI commoditizes products and services, inherently scarce elements like human connection and attention become more valuable.
But digging deeper with my buddies Gemini and Claude, I found additional compelling reasons why human work isn't disappearing anytime soon. These reasons are rooted in the irreducible nature of human cognition, our essential role in ethical and social contexts, evolving consumer preferences, and the psychological imperative for purpose and meaning.
Let's examine why a future populated by humans will always be a future that includes human jobs.
Perhaps more innovative jobs than ever.
1) The Creativity Trap
AI's creative output looks impressive until you examine it closely. Research from Wharton found that people using generative AI tools produce "overlapping responses, often using strikingly similar language." In one experiment, nearly all AI-generated toy concepts clustered around the same idea—only 6% were considered unique, compared to 100% uniqueness from human-only groups.
This isn't a bug; it's a feature. AI creativity is fundamentally recombinatorial, averaging the most likely completions based on that input. AI excels at sophisticated mimicry but struggles with genuine novelty. Human creativity, by contrast, thrives on disagreement, divergence, and a bit of creative mess.
The implications are profound. If AI's creative process optimizes and recombines existing patterns, it's inherently limited in generating truly novel paradigms. Human creativity—with its capacity for breaking free from established patterns—provides the initial spark for scientific breakthroughs, artistic movements, and societal shifts. The machines can refine and iterate, but they can't imagine what doesn't yet exist. Claude can help me write some articles, but it cannot write what I would write.
2) The Common Sense Problem
AI systems trained on massive datasets still struggle with something every human takes for granted: common sense. They miss subtle emotional cues, stumble over figurative language, and fail spectacularly when faced with novel situations outside their training distribution.
Common sense reasoning remains a long-standing challenge in AI—trivial for humans but nearly impossible for machines. AI's reasoning is typically discriminative (categorizing from predefined labels) rather than generative (inferring causes, predicting events, understanding motivations on the fly).
This brittleness creates permanent niches for human adaptability. Strategic leadership, crisis management, complex legal interpretation, and personalized education all require the kind of flexible, intuitive reasoning that humans navigate effortlessly but machines find intractable. Jobs are safe when they rely more on "duh" than on data.
3) The Consciousness Question
Perhaps the most fundamental barrier is consciousness itself. AI demonstrates problem-solving and information processing, but lacks subjective experience or qualia (the subjective, experiential qualities that constitute what it is like to have conscious experiences). AI can perform highly intelligent tasks without actually experiencing them.
Consciousness requires self-referentiality—the ability to observe and process one's own states, leading to self-awareness. This is an emergent architecture that can't be programmed from the outside. For genuine self-perception, you need a perceivable boundary (such as skin) to separate 'I' from 'non-I'—something AI systems fundamentally lack.
The Chinese Room Argument reinforces this: symbol manipulation doesn't equal genuine understanding or subjective experience. AI cannot feel, desire, suffer, or experience the world as humans do. Even when machines achieve superintelligence—and I assume they will—any job requiring genuine emotional understanding, moral intuition, or the subjective experience of being human remains exclusively in our domain. My buddy Zed cannot do any job that requires an understanding of being human.
4) Empathy as Competitive Advantage
Jobs requiring high emotional intelligence, empathy, and interpersonal skills remain stubbornly human-centric because these qualities resist algorithmic replication. The data bears this out across sectors:
In healthcare, empathy significantly improves clinical outcomes and patient satisfaction. Teachers foster emotional intelligence and connect with students in ways that enhance learning and psychological well-being. In customer service, most customers prefer speaking to real people, highlighting the critical role of human interaction in building trust and loyalty.
Psychology, social work, public relations, wedding and funeral planning all involve managing complex emotional landscapes that AI cannot navigate. These aren't just preference-based distinctions—they're functional necessities that create measurable value. I can let an AI make my presentation slides, but I will never send it on stage to deliver the keynote.
5) The Ethics and Oversight Imperative
AI systems cannot assess and prioritize ethical considerations. They perpetuate biases in their training data, sometimes catastrophically. For example, Amazon's AI recruiting engine developed a bias against women, penalizing resumes containing the word "women" and downgrading graduates from all-women's colleges. Despite correction attempts, the discriminatory risk led Amazon to abandon the project entirely.
This isn't a temporary problem waiting for better algorithms. Human oversight is critical for AI systems to operate transparently, accountably, and aligned with human values. Regulatory frameworks like the EU's AI Act explicitly require human intervention mechanisms, especially where fundamental rights are at stake.
As AI becomes more powerful and integrated into healthcare, finance, and legal systems, the risks of unchecked automation become intolerable. This creates entirely new job categories focused on AI governance, ethics, auditing, and strategic oversight—roles that aren't about managing technology but ensuring its responsible deployment.
6) The Authenticity Premium
Consumers increasingly seek "authenticity" and "meaningful connections with brands," moving away from hyper-curated content toward "less produced media with more human touches." This isn't mere preference—it's economic reality.
The luxury market exemplifies this trend. Hermès emphasizes "uncompromising standards of quality and craftsmanship" achieved by "skilled artisans." Tiffany & Co. offers bespoke jewelry services. These brands succeed because they offer something AI cannot: the story, connection, and trust that only human involvement can genuinely convey. But the same applies to the low end of the market: people happily pay a bit more for artisanal ice cream over whatever comes out of a factory.
For the same reasons, physical-world expertise may prove more durable than knowledge work in an AI-abundant future. Customers pay premium prices for skilled artisans and craftspeople who offer intricate human skills and expertise that no robot can replace.
As AI drives abundance and commoditization, the market places increasing premiums on goods and services carrying the authenticity of human creation, effort, or verification. This creates persistent demand for artisans, bespoke service providers, and human authenticators—roles that exist specifically because people value the "real thing."
It is precisely why some subscribers pay for Substack subscriptions: they value the authentic human touch. (Hint, hint. 😉⬇️ )
7) The Meaning-Making Imperative
Work serves fundamental human needs beyond economic necessity—identity, purpose, social contribution. The automation of routine tasks doesn't eliminate these needs; it amplifies them.
As machines handle repetitive work, roles emphasizing empathy, critical thinking, and personal growth become more vital—and ultimately more satisfying for humans. The definition of meaningful work shifts from task execution to the value and impact we leave behind and the passion and intention behind it.
Even in a highly automated future where AI makes many goods and services abundant, humans will retain deep psychological needs for purpose, contribution, and social engagement through work. This suggests that humans will choose to work—not for survival, but for self-actualization, social status, and belonging.
This redefines work itself, shifting from efficiency-driven tasks to roles fulfilling intrinsic human needs: community building, artistic expression, philosophical inquiry, curiosity-driven scientific exploration, and social care. Payment becomes a secondary concern as long as our basic needs are met and we can do something interesting.
8) Comparative Advantage
Finally, as mentioned earlier, the principle of comparative advantage means both humans and AI will specialize where they're most efficient. Comparative advantage means countries, companies, or individuals should specialize in producing goods or services where they have the lowest opportunity cost relative to others—even if they're not the absolute best at it. This specialization and trade benefits everyone by maximizing overall efficiency and output.
Critically, AI systems consume enormous resources—energy for training, water for cooling, and rare minerals for GPUs. International or regional regulations that address environment sustainability will only drive up the price of compute. Such resource constraints mean AI should only tackle tasks where its value justifies the environmental cost. Even when AIs are superior to humans at performing certain tasks, it doesn't mean that they should. The limited available processing power will force the deployment of AI where it delivers maximum value. And humans might still have plenty to do.
OK, Maybe It's Time to Panic
For centuries, human civilization has built a complex economic ecosystem that sustained billions of livelihoods. Workers across every industry have mastered their trades—from factory floors to corner offices, from farms to financial centers. These established systems have evolved over generations, creating intricate networks of employment that seemed as permanent as the foundations of society itself.
But now, something has emerged. A new technological capability has appeared, first in laboratories and research centers, then in well-funded corporations—digital entities that can process information, recognize patterns, and execute tasks with unprecedented speed and accuracy. At first, this innovation seemed like just another tool, promising to augment human capabilities rather than replace them.
But as these systems multiply and improve, their impact spreads across entire industries. There may come a disruption that will be swift and merciless. Jobs that had existed for generations will begin vanishing overnight. Traditional roles become obsolete as the new technology proves faster, cheaper, and more reliable than human workers. Entire professions will face extinction as the economic landscape transforms beyond recognition.
And yet, from this upheaval, new categories of work will appear—roles that require uniquely human creativity, emotional intelligence, and complex problem-solving. Fresh industries will sprout around managing, training, and collaborating with the transformative technology. Those who adapt will discover opportunities for more meaningful, higher-value work than ever before.
The technological force that will trigger the greatest economic disruption in human history may also become the foundation for an entirely new era of prosperity and human potential. That transformative technology is artificial intelligence.
The Great Automation Event
I am a short-term pessimist and a long-term optimist. The transition we're entering will be genuinely painful for millions of workers whose livelihoods disappear faster than new opportunities emerge.
Yes, AI is predicted to "create more jobs than it replaces"—new roles in AI development, maintenance, ethics, and entirely new fields emerging from AI-enabled capabilities. While AI assists with coding, design, and research, what remains for humans is genuine creativity, complex problem-solving, human interaction, and human oversight. The human-AI relationship is evolving into a symbiotic ecosystem where AI handles data-intensive, repetitive, or pattern-recognition tasks while humans provide critical thinking, ethical judgment, and contextual understanding. This doesn't preserve existing jobs—it disrupts them, transforms them, and generates entirely new categories centered on managing, guiding, and collaborating with AI.
The persistence of human jobs isn't optimistic thinking—it's economic and psychological reality.
But the transition will be painful.
Unlike the ancient organisms that simply vanished, displaced humans will experience real suffering—financial stress, loss of identity, and uncertainty about their futures. We cannot simply celebrate the eventual emergence of new economic ecosystems in the future while ignoring the immediate human cost now. Unlike ancient bacteria, displaced humans have mortgages, families, and decades of identity tied to their work. The eventually beneficial outcomes for the economy may take years emerge—cold comfort to someone losing their job this year.
We have an urgent responsibility to build robust support systems: retraining programs, social safety nets, and transition assistance that help people bridge from the old economy to the new one. The Great Oxygenation Event reminds us that transformative change, while ultimately beneficial, requires us to actively care for those caught in the disruption. Humanity will adapt and thrive in ways we can barely imagine today—but only if we ensure that the transition itself doesn't leave people behind.
Let's be thankful for the countless jobs that dominated our economy before they all perish in the Great Automation Event.
Jurgen
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Works Cited
The Future of Writing—Why AI Will Never Replace Human Creativity | The Unemployed Professors Blog
The Curious Case of Commonsense Intelligence | American Academy of Arts & Sciences
Why Artificial Intelligence Doesn't Need Consciousness | Medium
The Rise of Empathy-Driven Careers in the AI Era — Optim Careers
8 Job Ideas for People with High Emotional Intelligence - Defuse
Improve customer loyalty with a human touch - Sigma Connected
AI decision making & critical thinking: empowering human judgment
The Luxury of Authenticity: Top Strategies for Maintaining Brand Integrity
Generative AI use is skyrocketing, but consumers demand human touch
Finding Purpose: Meaningful Work in an Automated Age - AA Media Studios Blog
The Psychology of Automation and Artificial Intelligence at Work - ResearchGate
From tasks to transformation: the human-centric future of AI - Lewis Silkin LLP
How Will Artificial Intelligence Affect Jobs 2025-2030 | Nexford University
48 Jobs AI Will Replace by 2025: Check If Yours is at Risk - Winssolutions
This is one of the clearest, most grounded articulations of where we are right now.
It feels like you wrote my brain!
I felt that same fourth disillusionment land hard. For this I built what I call Reflective Prompting. It wasn’t a way to "prompt better." It was how I stayed coherent when everything was changing, how I used AI not to escape the discomfort, but to move through it with clarity.
I don’t think the next edge is about predicting collapse or celebrating the bloom, it’s about staying inside the uncertainty long enough to build from it. Not with forecasts, but with observation. What if we created small “canary” sub-groups inside companies, no roles, people gather around meaningful tasks in the way they love working? No fixed titles. No optimized teams. Just curiosity, mixed skills, and time. Some of what emerges might be noise. But some might be the next layer of signal.
This article is a gem 💎 I am contemplating for months now what I will do with my experiences in product management, agile coaching and a little bit of coding to make a living in the future; I think there are some thoughts in this article that will help me.