The Hidden Cost of AI: From FOMO to FOO: Fear of Obsolescence
In every technological revolution, the decisive force is not the tech itself but the human mind.
Adoption, investment, and competition are often less about careful planning and more about emotion, fueled by instinct, anxiety, and collective hope. Today, amid the generative AI boom projected to top $100 billion by 2026, we find ourselves reliving a familiar pattern, but with a sharper edge.
The Fear of Missing Out (FOMO) that once drove early technology waves has matured into something heavier: FOO, the Fear of Obsolescence.
This shift is not just a change in vocabulary. It is altering the rhythm of capital, the tempo of decision-making, and the fate of industries. If FOMO accelerated innovation, FOO could destabilize it. That emotion, more than AI’s actual capabilities, is being monetized with staggering precision.
The Feeling of Always Falling Behind
Many today describe a gnawing sensation: a sense of constantly trying to catch up as technology races ahead. You learn one tool, and then, almost overnight, something faster, bigger, and more complex like generative AI lands on your desk.
Initially, this anxiety felt familiar, a natural extension of FOMO. But increasingly, it seems deeper, more existential. This is not just fear of missing a market opportunity. It is fear of becoming irrelevant. It is fear of being forgotten.
Our sources confirm this shift. They highlight how today's AI-driven market is animated less by excitement and more by profound psychological tension. Not just hype, but a deep undercurrent shaping investment, strategy, and leadership behavior.
Following the Money: A Delicate Financial Reality
The excitement around generative AI is undeniable. OpenAI's ChatGPT and Anthropic’s Claude have reshaped expectations, unlocked new forms of creativity, and enthralled a global audience.
But beneath the headlines lies a more precarious financial foundation.
OpenAI, for all its cultural dominance, reportedly posted a $5 billion loss in 2024, with operating costs exceeding $700,000 per day (Business Insider, LessWrong).
Anthropic, buoyed by investments from Amazon and Google, is burning through $2.7 billion annually while aiming for $3.7 billion in revenue (The Information).
Neither is profitable. Their strategic value lies not in today’s margins but in future influence, a future no major tech player can afford to miss.
Enterprise adoption tells a similarly tangled story. Alphabet’s 2025 earnings cited AI-driven growth, yet the majority of gains stemmed from enhancements to existing ad products, not entirely new businesses. Microsoft, touting a $3.70 return for every $1 invested in AI, bases its claims largely on internally commissioned studies without independent validation.
Productivity gains, where they exist, are often measured in hours saved rather than in profit margin expansion. Meanwhile, across sectors, the clearest and most immediate outcome has been headcount reductions, not disruptive innovation.
In short, spending is accelerating not because of clear ROI, but because FOO demands it.
Fear as the New Business Model
While platform companies chase long-term dominance, a booming secondary economy has emerged, built not on technological capability but on psychological reassurance.
Accenture reported $900 million in generative AI revenues in 2024 and $3 billion in forward bookings (Reuters).
McKinsey and others flood executive inboxes with urgent whitepapers and strategic advisory services.
LinkedIn has been saturated with AI certifications, training programs, and online accelerators, all promising to future-proof careers.
What is being sold is not just technical expertise; it is strategic reassurance. The pitch is clear: without AI, your relevance, your brand, and your organization will fade.
Consultants, educators, and influencers have built entire businesses around selling relief from existential anxiety. Fear itself has become a commodity.
Psychological Shift: From FOMO to FOO
The emotional DNA of technological adoption is mutating. FOMO was about seizing opportunity. FOO is about avoiding annihilation.
This shift leads to patterns that should concern any thoughtful leader:
Overinvestment in tools without clear links to business value.
Strategic drift, with AI initiatives disconnected from customer needs.
Brand erosion, where hastily deployed AI like clunky chatbots damages customer experience and trust.
Talent dislocation, as AI-driven efficiency measures cut jobs without preparing organizations for future growth.
In the thick fog of urgency, clarity is the first casualty.
As our sources reveal, the FOO-driven economy creates circular logic: companies invest heavily in AI not because they are realizing measurable gains, but because they fear what inaction would signal. The fear itself is self-perpetuating.
Echoes of the Dot-Com Era
History offers a sobering parallel. During the dot-com bubble, billions were thrown at digital initiatives not because they made business sense, but because not acting was seen as an even greater risk.
The few winners, like Amazon and Google, emerged not by following hype but by solving real problems with durable strategies.
Today’s AI rush bears similar risks. Real transformations will happen, but many early adopters, especially those operating under FOO rather than grounded strategy, may not survive to benefit.
Moving Beyond FOO: Reclaiming Strategic Clarity
Recognizing FOO is not enough. Leaders must deliberately break its hold by asking sharper, more courageous questions:
Where does AI offer true competitive advantage for us?
Which customer problems genuinely require AI to solve?
How do we deploy AI to strengthen trust, not erode it?
Are we acting from vision, or merely from fear?
Above all, motion does not equal progress. In the race to remain relevant, it is possible to run headlong into irrelevance.
True innovation, in any era, demands clarity over urgency, deliberation over anxiety, and vision over fear.
In an age of accelerating algorithms, it is still human discernment that builds enduring futures. And it is human failure, not machine error, that risks squandering them.
The real challenge with technology is not speed, but ensuring we are carrying light forward, not racing blindly into darkness.