SHENZHEN, the pulsing heart of China’s industrial machine, sitting across from one of the country’s legendary entrepreneurs—a man who has built billion-dollar supply chains and navigated every tectonic shift in global commerce for four decades. I expected our conversation to center on the Iran war, the Strait of Hormuz blockade, or the spiraling oil premiums strangling Asian manufacturers. Instead, he offered an observation that has haunted me ever since.

“For us, Trump’s attack on Iran is less consequential than his threat to attack Greenland,” he told me, swirling his tea. “When he did that, to America’s oldest allies—Denmark, the Netherlands, the Europeans—I knew immediately that Europe would not follow America’s approach to China. If he treats his friends this way, who needs enemies?”

That remark, delivered with the clinical detachment of a man reading a balance sheet, captures something profound about the tectonic shift underway in global geopolitics. The costs of President Donald Trump’s systematic contempt for allies are no longer theoretical. They are materializing in defense budgets, trade agreements, currency arrangements, and diplomatic realignments from Brussels to Tokyo. Governments that once anchored their entire foreign policies to the reliability of American power are now actively hedging against its absence.

The Greenland Shock: When Allies Became Targets

To understand the velocity of this realignment, one must revisit January 2026—the month Donald Trump threatened to annex Greenland, a sovereign territory of NATO ally Denmark, using military force if necessary, while simultaneously threatening escalating tariffs of 10% to 25% on eight European nations to coerce compliance. 

The European response was swift and unprecedented. European Commission President Ursula von der Leyen warned Washington to keep its hands off Greenland, declaring the island’s sovereignty “non-negotiable” and Europe’s response would be “unflinching.”  The European Union activated its trade “bazooka”—the Anti-Coercion Instrument—at an emergency leaders’ summit in Brussels. 

But the deeper damage was psychological. As the Council on Foreign Relations noted, “the president’s attempt to take control of Greenland could prove existential for the NATO alliance” and “Europeans have lost all illusions about the transatlantic relationship.”  The Economist described Trump’s Greenland gambit as having “created the biggest rift in the transatlantic alliance since the 1956 Suez crisis.” 

This was not a dispute over burden-sharing or defense spending targets—arguments that, however abrasive, operated within the guardrails of alliance management. This was the United States threatening to seize territory from a founding NATO member. For European capitals, the message was unambiguous: if Washington could treat Copenhagen this way, no ally was safe.

From Hedging to Hard Decoupling: Europe’s Strategic Awakening

The accumulation of abuse—tariff wars, insults hurled at allied leaders, open support for far-right parties seeking to fracture the European Union—has reached a tipping point. As Daniel DePetris recently wrote in the U.K. edition of the Spectator, a conservative and ardently pro-American magazine: “The war in Iran has forced Europe to grow a spine. European leaders are no longer interested in dropping to their knees and groveling to stay on Trump’s good side.” 

The shift from rhetoric to action is now unmistakable. The European Union’s ReArm Europe/Readiness 2030 plan commits approximately 800 billion euros (roughly $935 billion) to defense investment in the coming years.  Crucially, the objective is no longer simply to buy American weapons—the model that sustained the transatlantic security bargain for decades. Europeans now want their money to stay at home, building European firms and supply chains to gain strategic autonomy from Washington. 

The same logic is spreading beyond defense. The European Payments Initiative is actively building a European alternative to Visa and Mastercard, with its CEO explicitly citing “Trump fears” as a catalyst for adoption.  The era of “de-risking” was once discussed exclusively in relation to China. Now, European leaders are openly discussing de-risking from the United States. 

This is not merely about defense procurement or payment rails. It represents the embryonic architecture of a post-American Europe—one that is increasingly unwilling to subordinate its economic and strategic interests to the whims of an erratic White House.

The Iran War as the Final Straw

If Greenland shattered the illusion of American reliability, the Iran war has pulverized what remained. When U.S. and Israeli forces launched large-scale strikes across Iran in late February 2026, killing Ayatollah Ali Khamenei and other senior regime figures, Trump expected allied solidarity.  What he received was a collective shrug—and then active opposition.

As The Economist reported in early April 2026, European allies are “losing hope of keeping America in NATO,” with President Trump “fuming about their refusal to send ships to reopen the Strait of Hormuz and the reluctance of some to facilitate American operations.”  European NATO allies declared they would not get involved in Trump’s Strait of Hormuz blockade, further ratcheting up tensions within the increasingly fragile alliance. 

The Carnegie Endowment for International Peace captured the European mood precisely: “Donald Trump has certainly done irreversible damage to NATO, but the reasons why there is no way back are long-term and structural. U.S. strategic interests have shifted away from Europe. The transatlantic relationship may get more normal after Trump, based on narrower shared interests, respectful communication, and predictability, but Europeans will have to grow up.” 

The Iran war has done something no amount of diplomatic persuasion could achieve: it has forced Europe to contemplate a future in which American security guarantees can no longer be taken for granted. France and Germany have launched a nuclear steering group to discuss extending the French nuclear umbrella across the continent—a conversation that would have been unthinkable just two years ago.  French President Emmanuel Macron announced a major doctrine shift, opening deterrence exercises to European allies and dispatching French strategic nuclear forces to allied territory. 

Germany, historically the most reluctant European power to assume security leadership, is now actively discussing coming under the French nuclear shield. Poland’s president has openly mused about developing Warsaw’s own nuclear capability.  These are not fringe debates. They represent the most fundamental reimagining of European security architecture since the 1950s.

The View from Beijing: A Strategic Windfall

Perhaps the most damning indicator of how far American standing has fallen comes from the global survey data. The European Council on Foreign Relations found that a year after Trump’s return, a substantial portion of global respondents believe China is overtaking the United States as the world’s dominant power—and that Trump is “making China great again.” 

Only 16% of EU citizens now consider the United States an ally, while 20% see it as a rival or an enemy.  In Germany, trust in American leadership has dropped by a staggering 39 percentage points.  A POLITICO poll of major NATO allies found that majorities in Germany, Canada, and France describe the United States as an unreliable ally—including 57% of Canadians and half of German adults. 

Critically, this is not because Europeans have suddenly fallen in love with Beijing. They have not. Europe has deep conflicts with China over Ukraine, subsidies, electric vehicles, critical minerals, and market access.  But the strategic calculus has shifted. In a world where the United States threatens allies with annexation and economic warfare, maintaining a second channel to Beijing becomes not a preference but a necessity.

As the European Parliament’s own assessment concluded, transatlantic relations since early 2025 have been “marked by rising tension and uncertainty regarding the reliability of the United States as an ally” across multiple domains including NATO, Greenland, Ukraine, trade, technology, climate, and relations with China. 

The Asia-Pacific Fallout: When the Nuclear Umbrella Frays

The contagion is spreading far beyond Europe. Across the Asia-Pacific, American allies who have built their entire defense postures around U.S. security guarantees are now running the same calculus that Europeans have already completed: Can we still count on Washington?

A recent Taiwan poll found that 57% of respondents did not believe the United States would send troops to defend the island if war broke out in the Taiwan Strait.  In Japan and South Korea, the probability of independent nuclear arsenals—long considered a taboo—is now being openly discussed in policy circles, precisely because the American nuclear umbrella is increasingly viewed as an unreliable asset. 

The European Council on Foreign Relations report warned explicitly: “If Washington’s security guarantees are regarded as transactional, Asian partners may view the American nuclear umbrella as unreliable. An unforeseen consequence is that it increases the probability that Japan and South Korea will seek independent nuclear arsenals for strategic survival.” 

This is the ultimate cost of Trump’s contempt: a world in which American allies, rather than pooling their security under U.S. leadership, pursue their own nuclear capabilities—weakening nonproliferation norms, increasing the risk of miscalculation, and eroding the very architecture of American hegemony that has kept great-power peace for eight decades.

The Price America Will Pay

There is a paradox at the heart of Trump’s approach. His stated goal is to make America stronger, richer, and more respected. But the actual result is the systematic dismantling of the alliance system that amplifies American power at a fraction of the cost of unilateral action.

As CFR scholars have noted, “Washington’s network of alliances has granted the United States extraordinary influence in Europe and Asia, imposing constraints on Moscow and Beijing at a scale that neither power can replicate.”  Chatham House’s analysis of Trump’s national security strategy observed that “hedging remains the best way for other countries to respond” to U.S. volatility and unpredictability—not just to gain leverage but “to protect against volatility.” 

The irony is that allies are doing precisely what Trump claims to want—spending more on defense, building indigenous industrial capacity—but in ways that reduce American leverage rather than enhance it. The ReArm Europe plan will generate hundreds of billions in defense spending, but increasingly those euros will flow to European defense contractors rather than American ones. The French-German nuclear dialogue, once unimaginable, is now in active planning stages. The European Payments Initiative is building infrastructure that could one day challenge dollar dominance in trade settlement.

Trump’s defenders argue that this is all part of the plan—that burden-shifting is the objective, and if Europe finally takes responsibility for its own defense, that represents American strategic success. But this argument conflates European capability with American influence. A Europe that can defend itself without the United States is also a Europe that can act without the United States—including on China policy, trade policy, and technology standards.

A World After American Reliability

The Shenzhen businessman I spoke with understood something that Washington’s strategic community is only beginning to grasp: reliability is the fundamental currency of alliance leadership. Once squandered, it cannot be quickly restored—even by a future administration that reverts to traditional alliance management.

As Foreign Affairs noted in its assessment of the Trump administration’s approach, “By extorting old friends for short-term gain, threatening to annex allied territory, and applying tariffs indiscriminately, he has squandered decades of cooperation that has served U.S. interests.” 

The Brookings Institution’s analysis captured the structural nature of this shift: “As that confidence dissipates, investors and governments hedge. There is no true alternative to the dollar today, but Europe remains an incomplete financial and political union, and China’s renminbi lacks credibility as a freely trusted reserve asset. Still, the direction of travel is unmistakable.” 

The costs of Trump’s contempt are no longer prospective. They are being priced into defense budgets, trade agreements, currency reserves, and diplomatic alignments across the globe. The world is not waiting for America to become reliable again. It is building systems that do not depend on American reliability at all.

For a country whose post-1945 strategy has rested on being the indispensable nation, there is no greater strategic defeat than becoming dispensable.

In markets, narratives can matter as much as hard data. Investors make decisions based on the stories they tell one another. Over the past seven weeks the tales being swapped have been of war in Iran, its effect on global energy markets and presidential social-media activity. The S&P 500, America’s benchmark index of stocks, has moved up and down with Donald Trump’s estimates of the odds of an end to the conflict. It surged to an all-time high on April 17th as America and Iran agreed to let traffic resume in the Strait of Hormuz. It dipped on April 20th after the deal collapsed.

And yet, beneath all of that noise, US corporate earnings in 2026 are doing something remarkable. They are growing — fast, broadly, and with a consistency that embarrasses the pessimists.

The Numbers That Cut Through the Geopolitical Din

The earnings picture heading into this season was already extraordinary before a single company reported. According to FactSet’s April 17 Earnings Insight, the consensus estimate for Q1 2026 S&P 500 earnings growth stood at 13.2% year-on-year at the start of the quarter — the highest entry-level estimate for any earnings season since Q2 2022. That is not a soft bar. That is a high-jump pole set at altitude.

What happened next was better still. With 10% of S&P 500 companies reporting actual results as of April 17th, 88% beat EPS estimates — well above the five-year average of 78% and the ten-year average of 76%. The magnitude of those beats was equally striking: companies are reporting earnings 10.8% above estimates, against a five-year average surprise rate of just 7.3%.

This is the sixth consecutive quarter of double-digit year-on-year earnings growth for the index. Six consecutive quarters. The S&P 500 hit a record intraday high of 7,126.06 on April 17th. That is not a coincidence.

A War, a Waterway, and the Market’s Cold Arithmetic

The Strait of Hormuz has been effectively closed since early March, cutting off roughly 20% of global oil supply — what the International Energy Agency has called the largest energy supply disruption in the history of global markets. More than 500 million barrels of crude and condensate have been removed from the market, according to Kpler data. U.S. crude oil closed at $89.61 per barrel on April 20th after jumping 6.8% when the ceasefire unraveled. Brent settled at $95.48, up 5.6% on the day.

Iran declared the strait open on a Friday. Oil prices tumbled more than 10%. The S&P 500 surged. By the following Monday, Trump accused Iran of firing on a French ship, seized an Iranian vessel, and the deal was functionally dead. Stocks barely flinched, falling just 0.2%.

That asymmetric response is the most important data point of this earnings season — and nobody is talking about it enough. When peace breaks out, markets rally hard. When war resumes, markets shrug. That is not resilience born of confidence. It is resilience born of a very specific market bet: that American corporate profits have been insulated from the mayhem.

So far, that bet is paying off. But the reasons why demand closer inspection.

The Magnificent Few and the Hidden Concentration Risk

Goldman Sachs raised its year-end S&P 500 target to 7,600 in early April, citing 12% earnings growth and a broad recovery — but its own analysts immediately flagged a problem with that framing. As Goldman’s equity strategy team noted, consensus estimates for 2026 and 2027 are about 4% above January levels, but the improvement is not evenly distributed. Exxon Mobil and Micron Technology account for a disproportionate share of upward revisions, while the median S&P 500 company has seen little or no change to its 2026 earnings outlook.

This is a market that looks healthier at the index level than it does underneath. FactSet’s breakdown makes the concentration explicit: the Magnificent 7 are projected to deliver 22.8% earnings growth in Q1 2026. The remaining 493 companies are projected to deliver 10.1%. Strip out NVIDIA alone, and the Magnificent 7 growth rate collapses to 6.4% — lower than the broader market.

That is a meaningful distinction for any portfolio manager choosing between chasing the benchmark and staying selective. The headline number flatters the underlying reality.

Q1 2026 Sector Earnings Growth: Who Is Carrying the Load

The sector-level breakdown, per FactSet and IG’s Q1 earnings preview, tells a more nuanced story than the aggregate suggests.

The Financials sector has been the early season standout. JPMorgan Chase reported $5.94 EPS against a $5.47 estimate. Citigroup delivered $3.06 versus $2.65. Bank of America and Morgan Stanley both beat. The blended Financials growth rate jumped from 15.0% to 19.7% in a single week of reporting.

Energy, meanwhile, is the cautionary tale embedded in this table. The sector’s estimated earnings growth swung from +12.9% in early April to -0.1% by mid-month, driven almost entirely by downward revisions to ExxonMobil’s guidance. The average Q1 oil price of $72.67 per barrel was only 1.8% above Q1 2025’s $71.38 average — the Q1 price spike only materialized late in the quarter, too late to flow through to most upstream earnings.

The Contrarian Case: Strength Built on Sand

Here is the uncomfortable truth that the bull narrative glosses over: US corporate profits are not resilient because American companies are exceptionally strong. They are resilient because they have exceptional pricing power — and because AI capital expenditure is creating an accounting illusion of demand.

Consider the mechanics. Technology companies are reporting earnings that are overwhelmingly driven by AI infrastructure spending. The firms writing the checks — hyperscalers, cloud providers, semiconductor companies — are booking revenues that appear as organic demand growth but are substantially circular: one tech giant’s AI capex becomes another’s top line. NVIDIA’s extraordinary contribution to S&P 500 growth (it is the single largest contributor for both Q1 2026 and full-year 2026 per FactSet) reflects an investment supercycle, not end-market demand expansion.

Meanwhile, the companies not in the AI supply chain — the median S&P 500 firm, the one Goldman says has seen no earnings revision — are passing higher energy and input costs onto consumers. That is pricing power. It is real. It has kept margins intact. But it is not growth in the classical sense. It is inflation in corporate clothing.

The IMF warned this week that global growth will take a hit even if the ceasefire holds, citing persistent energy disruption as a drag on output and a source of renewed inflation. “It’s clear we’re not going back to the Goldilocks scenario,” said Brian Arcese of Foord Asset Management. Investors who mistake pricing-power resilience for genuine economic strength will discover the difference when consumers, finally stretched too thin by elevated energy costs, stop absorbing the increases.

What the Forward Guidance Will Reveal

The real test of this earnings season is not Q1 — it is what companies say about Q2, Q3, and Q4. Most of Q1’s business activity predates the Hormuz closure, which only became a severe supply disruption in March. The damage in transportation costs, energy inputs, and supply-chain friction will show up in Q2 guidance calls, not Q1 actuals.

Analysts are currently forecasting earnings growth of 20.1%, 22.2%, and 19.9% for Q2 through Q4 2026 respectively. The full-year 2026 consensus sits at 18.0% growth. Those are staggering expectations for an economy operating under the largest energy supply disruption in modern history. A single round of conservative guidance from the major industrials — logistics companies, airlines, manufacturers — could puncture them quickly.

The market is already signaling some unease. According to FactSet’s April 17 update, companies reporting positive Q1 earnings surprises have actually seen an average price decrease of 0.2% in the two days following their reports. The market is saying: we already priced this in. Show us what comes next.

The Narrative Premium and Its Limits

There is a concept worth naming here: the “narrative premium.” It is the excess valuation that accrues to markets when the dominant story — in this case, AI-driven earnings supercycle plus geopolitical resolution — outpaces the underlying data. The forward 12-month P/E ratio for the S&P 500 stands at 20.9, above both the five-year average of 19.9 and the ten-year average of 18.9. Since March 31st, the price of the index has risen 7.6% while forward EPS estimates have risen just 1.5%. That gap is narrative premium, not fundamental re-rating.

Narrative premiums can persist for a long time. They can also collapse with remarkable speed when a single data point — an unexpected miss on forward guidance, an oil price shock that does not reverse — forces a reassessment of the story.

The S&P 500 hit an all-time record on April 17th. American profits are, genuinely, impressive. The earnings season is, genuinely, strong. But investors who are treating current valuations as justified by fundamentals — rather than supported by narrative — are carrying a risk they may not have fully priced.

The Strait of Hormuz is still closed. Thirteen million barrels a day are still locked out of global markets. And Q2 guidance calls start this week.

Frequently Asked Questions

What is driving US corporate earnings growth in 2026?

US corporate earnings growth in 2026 is being driven primarily by the Information Technology sector, which is projected to report 45% year-on-year EPS growth in Q1, largely due to AI infrastructure investment and semiconductor demand led by NVIDIA. Financial sector earnings have also significantly outperformed, with major banks including JPMorgan Chase, Citigroup, and Bank of America all beating Q1 estimates. The broader S&P 500 is on track for its sixth consecutive quarter of double-digit earnings growth, with analysts forecasting 18% full-year 2026 growth according to FactSet data.

How has the Iran war and Strait of Hormuz closure affected S&P 500 stocks?

The S&P 500 has shown surprising resilience despite the Strait of Hormuz being effectively closed since early March 2026, representing the largest energy supply disruption in modern history per the IEA. The index hit a record intraday high of 7,126.06 on April 17th when a brief ceasefire opened the waterway, then fell only 0.2% on April 20th when the deal collapsed. Energy sector earnings have been volatile — projected growth swung from +12.9% to -0.1% in two weeks — but the tech and financials sectors have more than offset the disruption at the index level.

Are S&P 500 earnings expectations too high for 2026?

Analysts are currently forecasting 18% full-year earnings growth for the S&P 500 in 2026, with Q2 through Q4 estimates ranging from 20.1% to 22.2%. These figures are historically elevated and carry substantial downside risk from Q2 forward guidance, given that most Q1 business activity predated the Hormuz supply disruption. The forward P/E ratio of 20.9 — above both the five- and ten-year averages — reflects a significant narrative premium tied to AI investment and geopolitical resolution expectations. A single round of conservative guidance from industrial or energy companies could materially revise these expectations lower.

Northern Trust’s $1.4 trillion asset management arm says the AI boom is “massively disinflationary.” The evidence is building — but so are the near-term headwinds. Here is what the bulls are getting right, what they are glossing over, and what every central banker should be thinking about this week.

Analysis · 2,150 words · Cites: Northern Trust, IMF WEO April 2026, BIS Working Papers, OECD

There is a sentence making the rounds in macro circles this morning that deserves more than a tweet. Northern Trust Asset Management — custodian of $1.4 trillion in client assets — told the Financial Times that the AI boom is poised to be “massively disinflationary.” Two words, twelve letters, and an argument that, if it proves correct, will reshape monetary policy for the rest of this decade. If it proves wrong, it will look like the most expensive case of group-think in asset management history.

The claim is bold, but it is not baseless. Across its 2026 Capital Market Assumptions, Northern Trust has laid the groundwork: nearly 40 percent of jobs worldwide — and 60 percent in advanced economies — are now exposed to AI, signalling what the firm calls “a major shift” in productivity and labor market dynamics. Add to that the IMF’s own January 2026 estimate that rapid AI adoption could lift global growth by as much as 0.3 percentage points this year alone, and up to 0.8 percentage points annually in the medium term, and suddenly “massively disinflationary” sounds less like a marketing line and more like a macroeconomic thesis worth taking seriously.

But serious theses deserve serious scrutiny. And when you peel back the optimism, you find a story with a considerably more complicated second act.

“AI today is still in its early innings. It is reshaping how we operate. It is reshaping how we work. Yet at the same time, we know there are going to be a number of missteps.” — Northern Trust Asset Management, February 2026

The disinflationary logic — and why it is compelling

The core argument runs as follows. AI raises the productive capacity of every worker, firm, and economy that adopts it. More output from the same inputs means falling unit costs. Falling unit costs mean downward pressure on prices. In a world still wrestling with inflation — the IMF’s April 2026 World Economic Outlook projects global headline inflation at 4.4 percent this year, elevated partly by a new Middle East conflict — that kind of structural supply-side boost could not arrive at a better moment.

The historical analogy is not perfect, but it is instructive. The internet and personal computing drove a productivity renaissance through the 1990s that helped the US run a decade of growth with unusually low inflation. The difference this time, optimists argue, is both speed and scope. Generative AI is being deployed across sectors — finance, law, medicine, logistics, software — simultaneously, rather than trickling through the economy over fifteen years. The IMF’s own research noted that investment in information-processing equipment and software grew 16.5 percent year-on-year in the third quarter of 2025 in the United States alone. That is not a technology cycle. That is a structural reorientation.

At the firm level, the mechanism is equally legible. AI-assisted coding reduces software development costs. AI-powered customer service reduces headcount requirements per unit of output. AI-accelerated drug discovery compresses R&D timelines. Each of these reduces costs for producers, and in competitive markets, cost reductions eventually become price reductions for consumers. The BIS, in its 2026 working paper on AI adoption among European firms, found measurable productivity gains at companies with higher AI adoption rates — gains that, if broad-based, translate directly into disinflationary pressure.

The uncomfortable counterarguments

Now for the cold water. The hyperscalers — Alphabet, Microsoft, Amazon, Meta — are expected to spend upwards of $600 billion on data center capital expenditure in 2026 alone, according to Northern Trust’s own analysis. That is $600 billion of demand competing for semiconductors, specialised labor, land, electricity infrastructure, and cooling systems. In the near term, this is not disinflationary. It is, by any honest accounting, inflationary. It bids up the price of every input that AI infrastructure requires.

Energy is the most acute example. Northern Trust’s own economists have noted that data centers are expected to account for 20 percent of the increase in global electricity usage through 2030. The IMF’s recent research put it plainly: energy bottlenecks “could delay AI diffusion, anchor a higher level of core inflation, and generate local pricing pressures” in grid-constrained regions. This is not a theoretical risk. It is a live constraint in the US, the UK, Ireland, Singapore, and across northern Europe, where grid capacity has become a hard ceiling on data center expansion.

There is also the measurement problem — and it is a serious one. As the IMF’s own Finance & Development noted in its March 2026 issue, GDP accounting simultaneously overstates AI’s immediate contribution (by counting massive capital outlays as output) while understating its broader economic impact (by missing productivity spillovers that do not show up in standard national accounts). This is precisely the statistical paradox that masked the early productivity gains of the 1990s IT revolution — and it cuts in both directions for policymakers. If AI is quietly raising potential output, the economy may be running cooler than headline data implies. If the infrastructure surge is instead stoking a new floor for energy and construction costs, central banks may be tightening into a real supply shock.

The IMF’s chief economist Pierre-Olivier Gourinchas put the dilemma with characteristic precision: the AI boom could lift global growth, but it also “poses risks for heightened inflation if it continues at its breakneck pace.” That is the paradox in miniature — the same technology that promises to lower prices over time is currently consuming enormous resources to build itself.

The geopolitical dimension: who wins, who lags, and who is locked out

The disinflationary thesis is not uniformly distributed across the global economy, and this is where the Northern Trust framing risks glossing over structural inequality. Advanced economies — the US, Japan, Australia, South Korea — are positioned to capture the productivity upside first. Their firms are adopting, their labor markets are adapting, and their capital markets are pricing in the gains. Northern Trust’s own forecasts identify the US, Japan, and Australia as likely leaders in equity returns over the next decade, precisely because of AI-driven productivity.

Europe sits in a more ambiguous position. The continent is not at the forefront of AI model development, and Northern Trust acknowledges it explicitly in its CMA 2026. The region offers a healthy dividend yield and attractive valuations — but if AI productivity is the driver of the next decade’s returns, Europe’s relative lag in AI infrastructure and frontier model development is a structural disadvantage, not a cyclical one. The ECB faces its own version of the monetary policy puzzle: if AI-driven disinflation arrives later and slower in Europe than in the US, it changes the rate path, the currency dynamics, and the comparative fiscal math.

Emerging markets face the starkest challenge. The IMF’s analysis of AI in developing economies is clear: AI preparedness — digital infrastructure, human capital, institutional capacity — is the binding constraint on whether productivity gains materialize or get captured entirely by technology importers. Many emerging economies are primarily consumers of AI built elsewhere. The disinflationary benefits they receive are mediated through imports; the inflationary effects of AI-driven energy demand and semiconductor scarcity are borne locally. The net result, without deliberate policy intervention, is a widening productivity gap rather than a convergence story.

China deserves a separate paragraph. Its AI investment is substantial and accelerating, even under the constraints of US semiconductor export controls. The China-US AI race is not merely a geopolitical contest — it is a race to determine which economy gets to define and monetize the next general-purpose technology. Beijing’s capacity to deploy AI at scale across manufacturing, logistics, and services could generate its own disinflationary dynamic, although its ability to export that technology — and the disinflation it carries — is constrained by the very geopolitical tensions that are simultaneously driving energy and defence inflation.

What central banks should actually do

The honest answer is: proceed carefully, communicate transparently, and resist the temptation to read AI’s structural effect through the noise of its near-term capex cycle. The IMF’s April 2026 World Economic Outlook makes the right call when it urges central banks to guard against “prolonged supply shocks destabilising inflation expectations” while reserving the right to “look through negative supply shocks” where inflation expectations remain anchored.

That is the narrow path. If AI is genuinely raising potential output, then central banks that tighten aggressively in response to near-term energy and infrastructure inflation are making a classic policy error: fighting tomorrow’s economy with yesterday’s models. The 1990s analogy is instructive again — the Federal Reserve’s willingness to allow growth to run above conventional estimates of potential, on the grounds that productivity was accelerating, helped produce the longest peacetime expansion in American history.

But the reverse error is equally dangerous. If the AI productivity jackpot takes longer to arrive than Northern Trust and its peers anticipate — and Daron Acemoglu’s careful 2025 work in Economic Policy gives serious reason for that caution — then central banks that ease prematurely, trusting in a disinflationary future that is still several years away, risk entrenching the very inflation they spent the early 2020s battling back.

The IMF is right to treat AI as what it called in its April 2026 research note “a macro-critical transition rather than a standard technology shock.” Human decisions — by managers, workers, regulators, and investors — will shape the pace of adoption, the distribution of gains, and the political sustainability of the disruption. Those decisions are not made yet. Which means the data, for now, is genuinely ambiguous.

The verdict: right thesis, wrong timeline

Northern Trust is probably correct that AI will be massively disinflationary. The logic is sound, the historical analogies are supportive, and the scale of investment being made is simply too large to yield no productivity dividend. The question is not whether, but when — and the “when” matters enormously for portfolio construction, monetary policy, and fiscal planning.

The near-term picture, stripped of AI optimism, is one of elevated global inflation shaped by geopolitical conflict, persistent services price stickiness, and a capex boom that is consuming rather than producing cheap goods. The medium-term picture, contingent on adoption rates and diffusion across the global economy, is one where AI-driven productivity could deliver a genuine and sustained disinflationary impulse — the kind that would allow central banks to run looser for longer, equity multiples to expand sustainably, and real wages to recover.

The investor who misidentifies the timeline — and treats the medium-term story as immediate reality — will find themselves long duration in a world where rates stay higher than expected, and long AI infrastructure capex in a world where the ROI question remains, as Northern Trust itself acknowledged in February, one of “many more questions than answers.”

The honest macro position, as of April 2026, is this: Northern Trust is pointing in the right direction. But they may be holding the map upside down with respect to the calendar. For investors, policymakers, and strategists, the discipline required is not deciding whether AI will be disinflationary — it will — but calibrating, with intellectual humility, exactly how long the world will have to wait before the price deflator actually arrives.