Iran, Oil, Artificial Intelligence, and the New Global Power Economy

Author: Zion Zhao Real Estate | 88844623 | 狮家社小赵 | wa.me/6588844623

Author’s note and disclaimer: For general education and market literacy only. Not financial, investment, legal, accounting, or tax advice, and not an offer, solicitation, or recommendation. Information is general and may be inaccurate or change. No liability accepted. Investing involves risk, including loss of principal; past performance is not indicative of future results. 

From Oil Shock to Artificial Intelligence Boom: The New Politics of Power, Growth, and Global Risk 

The most important takeaway is that this is not really a story about Iran, artificial intelligence, or taxation in isolation. It is a story about how all three now intersect inside one fragile political economy. The Iran war reminds us that the old world of hard power, energy chokepoints, and supply shock still governs inflation and growth. The artificial intelligence boom reminds us that the new world of software, compute, and tokenized intelligence is monetizing at extraordinary speed. The tax debate in wealthy American states shows how political systems react when volatility, inequality, and fiscal pressure collide. Read together, these trends point to a single conclusion: the next decade will be shaped by the interaction between physical scarcity, digital acceleration, and public legitimacy.

Start with Iran. Markets do not fear headlines alone. They fear duration. The Strait of Hormuz remains one of the most strategically important energy chokepoints in the world, carrying roughly one-fifth of global petroleum liquids consumption and a substantial share of liquefied natural gas trade. That is why any disruption there immediately becomes a global macroeconomic issue rather than a local military story (U.S. Energy Information Administration, 2025). When oil prices spike, the damage is not limited to fuel costs. Higher energy prices weaken consumer confidence, raise business input costs, complicate central-bank policy, and risk re-embedding inflation into the wider economy. The International Energy Agency’s coordinated release of emergency reserves in March 2026 was not symbolic. It was a recognition that the shock was serious enough to require a system-level response (International Energy Agency, 2026).

The more difficult question is whether an off-ramp exists. Markets clearly want a short conflict, and risk assets have behaved as though investors still expect eventual de-escalation. But wanting an off-ramp is not the same as possessing one. Shipping routes, insurance markets, commercial confidence, and regional deterrence all have to normalize together. In that sense, the transcript is right to stress de-escalation, but too casual about how easy it would be to restore normal trade once a major maritime corridor has been militarized. This is especially important for Asia. China, India, and other major importers are structurally more exposed to prolonged disruption, which means the conflict is not only a Middle East problem or an American problem. It is also a broader Asian energy-security problem with obvious geopolitical consequences.

That brings us to artificial intelligence, where the discussion captures something undeniably real. OpenAI and Anthropic are scaling revenue at a pace that would have seemed implausible even a short time ago. Anthropic reported a run-rate revenue figure of $14 billion in February 2026 and later reached an even higher run-rate, while OpenAI disclosed annual recurring revenue of $20 billion at the end of 2025 and was later associated with an annualized figure above that level (Anthropic, 2026; Reuters Breakingviews, 2026). These numbers matter because they answer a question that skeptics kept asking: is there actual demand, or only hype? The answer is now clear. There is real demand.

But real demand is not the same as mature economics. This is where the debate becomes more interesting and more intellectually honest. Some artificial intelligence revenue is clearly sticky, mission-relevant, and tied to real workflow gains, especially in coding, research, and enterprise assistance. At the same time, much of the corporate world is still in pilot mode. McKinsey’s 2025 survey found that although artificial intelligence adoption was widespread, only a minority of organizations had truly begun scaling across the enterprise (McKinsey & Company, 2025). In other words, frontier labs are monetizing aggressively, but the quality of that revenue still varies. Some of it is embedded. Some of it is exploratory. Some of it is driven by fear of being left behind. Investors should celebrate the scale but stay disciplined about the durability.

The empirical evidence supports both optimism and caution. Field studies show that generative artificial intelligence can lift productivity in real settings, including customer support and software development (Brynjolfsson et al., 2025; Cui et al., 2025). Yet newer research also shows that gains are not universal and that, in some complex environments, frontier tools can slow experienced workers rather than speed them up (Baker et al., 2025). That is the right frame for 2026. This is not fake. It is not solved either. The market is funding a technology that is commercially real, strategically important, and still uneven in operational maturity.

The biggest underappreciated issue, however, is not revenue. It is trust. Artificial intelligence in the United States has a legitimacy problem. Public optimism remains far weaker than in China and much of Asia, and American workers are more worried than hopeful about its impact on jobs (Stanford Institute for Human-Centered Artificial Intelligence, 2025; Pew Research Center, 2025). That matters because artificial intelligence is no longer just a software product. It is now a labor-market story, a legal-liability story, a healthcare-regulation story, and an infrastructure story. If the public distrusts the technology, resistance spreads from chatbots to data centers, from abstract ethics to zoning fights and professional restrictions. Pew’s 2026 survey on data centers shows that many Americans now view these facilities negatively on environmental and quality-of-life grounds, even while acknowledging their economic benefits (Pew Research Center, 2026).

This is where the industry has badly mishandled its own narrative. When leaders alternate between apocalyptic claims, utopian claims, and casual utility analogies, they do not project seriousness. They create confusion. That confusion invites regulation, fuels backlash, and makes local opposition easier to organize. The result is a paradox: the same industry posting historic revenue growth is also eroding the social consent it needs to scale. That is not a communications footnote. It is a strategic risk.

The tax debate fits the same pattern. Washington state’s proposed millionaire tax and the broader discussion of wealth mobility, fiscal pressure, and capital flight reflect a political system struggling to fund its commitments without undermining competitiveness. Here too the conversation is directionally important but needs nuance. High earners do respond to tax differentials, especially when mobility is high, yet the economics are not as simple as either side suggests. The bigger point is that redistribution battles intensify when growth feels uneven and when the public suspects that technological abundance is enriching some groups faster than it is improving broad living standards.

That is why this moment matters. The winners of the next decade will not be chosen by energy markets alone or by model quality alone. They will be chosen by who can align economics, infrastructure, and public legitimacy. Oil shocks still move the world. Artificial intelligence can still reshape it. But neither can be scaled sustainably without political trust. That is the real lesson.

References

Anthropic. (2026, February 12). Anthropic raises $30 billion in Series G funding at $380 billion post-money valuation.

Baker, M., Dell’Acqua, F., De Cremer, D., Kapoor, K., Kupor, D., & Patel, R. (2025). AI tools in software development: Evidence from a randomized controlled trial.

Brynjolfsson, E., Li, D., & Raymond, L. R. (2025). Generative AI at work. The Quarterly Journal of Economics, 140(2), 889-942.

Cui, K. Z., Demirer, M., Jaffe, S., Musolff, L., Peng, S., & Salz, T. (2025). The effects of generative AI on high-skilled work: Evidence from three field experiments with software developers.

International Energy Agency. (2026, March 11). IEA member countries to carry out largest ever oil stock release amid market disruptions from Middle East conflict.

McKinsey & Company. (2025). The state of AI in 2025: Agents, innovation, and transformation.

Pew Research Center. (2025). On future AI use in workplace, U.S. workers more worried than hopeful.

Pew Research Center. (2026). How Americans view data centers’ impact in key areas, from the environment to jobs.

Reuters Breakingviews. (2026, March 10). Anthropic gives lesson in AI revenue hallucination.

Stanford Institute for Human-Centered Artificial Intelligence. (2025). AI Index Report 2025.

U.S. Energy Information Administration. (2025, June 16). Amid regional conflict, the Strait of Hormuz remains critical oil chokepoint.

War, Energy, Artificial Intelligence, and Tax Revolt: Decoding the Forces Reshaping the Modern Economy

Energy shocks, artificial intelligence monetization, and tax politics are no longer separate debates. Iran exposes the fragility of global growth, frontier artificial intelligence proves demand is real but still maturing, and public backlash shows legitimacy matters. The next winners will align economics, infrastructure, trust, and execution at scale.

This matters to Singapore property clients because real estate does not move in isolation. Wars, oil shocks, inflation, artificial intelligence growth, and tax policy all shape interest rates, business confidence, wealth flows, tenant demand, and investor sentiment. In a market like Singapore, these global forces can influence everything from purchasing power and mortgage decisions to rental resilience, capital preservation, and long term asset appreciation.

For buyers, this means timing, affordability, and property selection must be assessed against a shifting macroeconomic backdrop, not just headlines or emotion. For sellers, it means understanding how market sentiment, liquidity, and buyer psychology can affect pricing strategy and exit outcomes. For landlords and tenants, it means reading rental demand through the lens of employment trends, expatriate flows, and business expansion. For investors, it means choosing assets that are not only attractive today, but also resilient through volatility, policy change, and evolving global capital trends.

That is where informed representation makes a real difference. I do not merely market properties. I help clients interpret the wider economic environment and translate it into practical property decisions with clarity, discipline, and conviction. Whether you are buying your first home, upgrading, selling for maximum value, securing a quality tenant, or building a Singapore property portfolio, I provide strategic advice grounded in market knowledge, macroeconomic awareness, and execution experience.

If you are looking for a real estate professional who understands both Singapore property and the global forces shaping it, engage my services today. Let us discuss your objectives and build a strategy that protects your interests and positions you ahead of the market.