By Dr. Reza Olfati-Saber The Trump administration’s $100,000 H-1B visa fee ends three decades of tech labor arbitrage, triggering the largest geographic and educational rebalancing in American technology history. The Death of Silicon Valley’s Business Model On September 19, 2025, President Trump signed a proclamation that effectively ended the economic foundation of American technology’s coastal […]
Strategic Analysis of the Digital Therapeutics Revolution The Idea in Brief Digital therapeutics (DTx) are transforming healthcare from episodic interventions to continuous, AI-powered therapeutic relationships. FDA-cleared platforms like Pfizer’s migraine management application represent a paradigm shift where treatment becomes an ongoing, personalized experience. Companies understanding this platform transformation will capture disproportionate value in the emerging […]
The technology that promises to bridge the $240 billion treatment gap—but only if we get the implementation right By Dr. Reza Olfati-Saber The statistics are sobering: 970 million people worldwide suffer from mental health disorders, yet fewer than half receive adequate treatment (World Health Organization, 2022). In the United States alone, the economic burden of […]
The AI industry has created a fascinating economic paradox: incredible technological progress built on fundamentally broken business models. After three decades working with AI systems—from research labs to enterprise implementations—I’ve observed that we’re heading for a massive market correction that will separate the sustainable from the speculative.
The numbers reveal a stark economic reality. A consumer pays $200 for an AI coding assistant that costs the company $500 in API fees to OpenAI. OpenAI then pays $1,000 to Microsoft for cloud infrastructure, while Microsoft invests $10,000 in NVIDIA GPUs to power the operation. This mathematical impossibility only works because venture capital subsidizes every layer of the value chain.
Unlike previous AI winters driven by fundamental limitations, this correction stems from economic unsustainability while capabilities continue advancing. We are witnessing AI winter for some and AI summer for others simultaneously. Consumer AI applications and venture-funded horizontal platforms will experience devastating winter conditions, while AI infrastructure providers, specialized enterprise applications, and companies with proven regulatory compliance will experience unprecedented growth.
This Darwinian selection event will ultimately strengthen the AI ecosystem by eliminating subsidized business models and establishing sustainable economic foundations. The companies that survive will be those with quantifiable value propositions, regulatory expertise, and enterprise customer focus—transforming AI from a venture-subsidized experiment into economically viable infrastructure.
Continue reading for the complete analysis of winners, losers, and strategic implications…
How governance frameworks have transformed technologies from sources of harm to beneficial tools—and what this means for artificial intelligence By Reza Olfati-Saber: Founder, CEO, and Chief AI Architect of Wisdom Agent Inc. Understanding Technology Transformation In my three decades working with AI systems—from research labs to enterprise implementations—I’ve observed a consistent pattern. Technologies that initially […]
A practical guide for banking executives navigating the AI transformation in compliance By Dr. Reza Olfati-SaberFounder, CEO & Chief AI Architect, Wisdom Agent Inc.reza@wisdomagent.ai | wisdomagent.ai Your compliance team reviews 10,000 transaction alerts this month. Of those, 9,900 are false positives—legitimate customer activities flagged by rule-based systems. Meanwhile, money launderers continue to move funds through […]
Major technology companies have announced over $300 billion in combined AI infrastructure investments, yet McKinsey reports that 80% of organizations see limited material impact from their AI initiatives. Why this disconnect?
The answer lies not in the technology itself, but in where we are on the adoption curve. Like previous transformative technologies, AI is following a predictable S-curve pattern. Most organizations are still in the early stages, learning to navigate challenges around explainability, regulatory compliance, and organizational readiness.
The good news? The 20% seeing meaningful results—and the 4% creating substantial value—are showing us the path forward. Success requires understanding that AI explainability exists on a spectrum, with different approaches suited to different use cases. High-stakes decisions in healthcare or finance may require interpretable models, while content generation can leverage more complex systems.
As both technology and regulation continue to evolve, organizations that take a balanced approach—investing in people and processes alongside technology—are beginning to close the gap between AI investment and value creation.