A Market in Transition: 2026 Q2 Outlook on Geopolitics, AI, and Credit Markets

April 1, 2026

Most major asset classes have posted disappointing returns to start the year, but the year-to-date figures understate how abruptly markets deteriorated in the final month of the first quarter. Much of the damage in both stocks and bonds came after the war with Iran began, as investors were forced to reprice oil, inflation, and the path of central bank policy. While large cap US equities have been among the weaker performers this year, they have held up well over the past month, relative to international equity markets. That likely reflects the US’s greater resilience to oil shocks as well as the US dollar strengthening since the conflict began. If we compare equity market returns by country since the war with Iran began, returns appear to align broadly with each country’s dependence on imported energy as a share of total consumption.

Exhibit A: Total Returns by Asset Class

Exhibit B: Total Returns by Country vs. Energy Imports 

While Iran is dominating headlines today, the quarter was also defined by a major shift in how investors are thinking about artificial intelligence and growing concerns about private credit.

The AI Fear Trade

At the start of the year, the central debate around AI was whether the enormous spending on AI would ultimately generate an adequate return. By quarter-end, the fear had flipped to the opposite extreme: what if AI works too well? What if rapid adoption leads to widespread job displacement, weaker consumer spending, and a world in which AI agents compete away the profits of large parts of the economy?

Investor concerns first hit software companies after Anthropic released Claude Cowork, a model capable of generating substantial amounts of code and notable in part because Anthropic said much of the tool itself had been built by AI. The fears were twofold. First, that increasingly capable models could make it easier to replicate pieces of existing software products. Second, that AI agents could reduce demand for human seats across a wide range of industries, undermining the per-seat pricing models on which many software companies depend.

As the quarter progressed, that fear spread well beyond software. Anthropic rolled out more customized versions of Claude aimed at specific industries, and investors responded by selling not just software stocks, but also companies in real estate services, insurance, legal services, financial brokerage, logistics, and data-related businesses.

Exhibit C: February 2026 Total Returns by Sub-Industry Groups

AI Impact and a Perspective on the Future

One of the strangest episodes came in logistics. Algorhythm Holdings, a micro-cap company that had previously sold karaoke machines before rebranding around AI-enabled freight, said its platform was helping customers increase freight volumes by 300% to 400% without a corresponding increase in headcount. That was enough to trigger a sharp selloff in logistics stocks, including CH Robinson. The episode was remarkable not just because of the tiny size and unusual pedigree of the company delivering the headline, but because CH Robinson itself had been widely highlighted as an AI beneficiary just two quarters ago.

The episode serves as a good illustration of AI’s deflationary potential. If one company adopts AI and improves margins by lowering labor intensity, its competitors will likely do the same. Over time, the initial benefit is competed away and passed through to the customer in the form of lower prices. This is why we continue to believe AI is more likely to be structurally disinflationary over the intermediate term.

AI models will only continue to improve, and it can be difficult to imagine what they may be capable of in the future. In late February, investors were given one particularly vivid vision of how that future could unfold. Citrini Research published a widely circulated paper imagining a 2028 scenario in which AI adoption had led to widespread unemployment, weaker consumer spending, and significant profit compression across a range of industries. In many ways, the piece marked the peak of the AI fear trade. While the analysis relied on a number of simplifying assumptions and several of its conclusions were challenged by economists, it was a valuable thought piece that meaningfully shifted investor psychology around AI, equities, and the labor market. We have written for several quarters that while we do not expect AI to cause widespread labor displacement in the near term, it is likely already having an impact on job creation, particularly for entry-level workers.

Ultimately, we believe that the AI selloff became too indiscriminate in the first quarter, particularly amongst larger software companies. Incumbents’ moats are not built on code alone. The best companies have advantages rooted in workflow integration, proprietary data, regulatory complexity, distribution, customer relationships, support infrastructure, and brand trust. In many cases, the longer that incumbents can hold off pure AI-native challengers, the more time they buy themselves to embed comparable features directly into products customers already know how to use. AI may not erode the strongest incumbents’ moats. It may actually deepen them.

Private Credit

The AI fear trade also spilled directly into private credit. By way of background, private credit is non-bank lending, provided by private institutional investors generally to middle-market companies to fund acquisition or growth initiatives. It is similar to the broadly syndicated loan market, which many investors know as bank loans or leveraged loans. The key differences are that private credit loans are typically less liquid, more customized, and not broadly traded. Investors have been drawn to the asset class because it offers floating-rate exposure, relatively high spreads, and an illiquidity premium that can range from roughly 100 to 500 basis points over comparable broadly syndicated loans.

Software companies have been a popular target for direct lenders because they have historically exhibited recurring revenue and strong free cash flow conversion. Some estimates suggest software companies could represent 15-20% of total private credit loans. As the market has begun questioning the durability of software margins and revenue models in an AI world, it is only natural for credit investors to ask whether those borrowers deserve the same underwriting assumptions they received a year ago.

Private Credit Investment Vehicles

For many individual investors, access to the asset class has come through business development companies, or BDCs. Some are publicly traded and can be bought and sold on an exchange, though the share price can trade at significant discounts or premiums to reported NAV. Others are non-traded vehicles, many of them evergreen, that offer periodic liquidity, usually quarterly, subject to limits called “gates.” Those gates have become a major focus of the selloff as several large private credit managers have capped withdrawals at the standard 5% quarterly level in response to rising redemption requests.

We do not necessarily view the imposition of gates as a sign of imminent crisis. In many cases, they are working as designed. These vehicles own illiquid loans, not securities that can be sold quickly in deep public markets. If managers were forced to sell assets to meet redemptions well above what the structure anticipated, remaining investors could be permanently harmed. Gates are established to prevent exactly that outcome. Their existence is not, by itself, evidence that a fund is headed for significant defaults. It is evidence that investors are worried and, perhaps, that the underlying assets are less liquid than some investors believed.

The public market does not need to wait for private marks to change in order to express a view. Publicly traded BDCs and alternative asset managers have provided a real-time referendum on where investors think fair value may lie if software credit risk proves materially worse than currently marked. Many publicly traded BDCs’ share prices are down 10% and trading 20% or more below their latest NAVs. Alternative asset managers that collect fees from these vehicles are down more than 30%.

Why Private Credit is Unlikely to Pose Systemic Market Risk

As the selloff in private credit has intensified, some market commentators have begun to ask whether the asset class could pose a systemic risk akin to the 2008 financial crisis. The comparison could benefit from context. Starting with total size: the US private credit market is now roughly a $2 trillion industry, representing 5% of credit to the private non-financial sector. In contrast, mortgages represented 45% of such credit in the lead-up to the global financial crisis.

The funding structures are also very different. Private credit is funded with either capital locked up for five to ten years or through vehicles with strict quarterly redemption gates, providing managers time to work through stressed assets rather than having to sell into a panic. In 2008, highly illiquid, long-duration mortgage assets were financed with overnight borrowing in repo and commercial paper markets. Once confidence in the underlying collateral cracked, that short-term funding evaporated, forcing rapid deleveraging and fire sales.

Leverage provides another key distinction. Large financial institutions ahead of the crisis were often levered more than 30-to-1, meaning small losses could wipe out equity entirely. BDC leverage is capped at roughly 2-to-1 and most funds operate with materially less leverage than that.

That does not mean private-credit investors are safe from losses. They are not. Poor underwriting, stale marks, and technological disruption can all hurt returns. But there is a major difference between an asset class producing disappointing returns and an asset class sitting at the center of a system-wide crisis. At least for now, the evidence points much more strongly toward the former than the latter.

US banks do have exposure to private credit, but it does not represent a significant portion of their asset base. Moody’s estimates that as of June 2025, US banks had nearly $300 billion in loans outstanding to private credit providers, plus another $285 billion lent to private equity funds. Together, that is a little more than 2% of total US bank assets.

Lost somewhat in the market’s fixation on private credit was a development that pointed in the opposite direction for banks. In March, regulators moved ahead with a major proposal to lower bank capital requirements. The revised framework would reduce required capital by roughly 4.8%, potentially freeing additional balance-sheet capacity for lending, securities purchases, dividends, or buybacks. That does not make private-credit risk disappear, but it does suggest a more supportive regulatory backdrop is beginning to materialize.

The Iran War

The Iran war remains the hardest variable to forecast with confidence because the situation is evolving quickly and the information flow has been unusually noisy. The result is a market that is reacting, often sharply, to headlines before the underlying facts have clearly changed.

The most volatile market reactions have been in oil prices. Oil has been the only reliable hedge during the conflict, as Treasuries and gold have both sold off. That has likely made oil an increasingly crowded trade and more vulnerable to sharp selloffs on any hint of progress toward a ceasefire.

For investors, the natural instinct in an environment like this is to reduce risk and wait for an “all-clear” signal. History suggests that can be a costly strategy. Last year’s “Liberation Day” trade war was a reminder that by the time a final resolution is obvious, a meaningful portion of the rebound may already be over. The tail risks that continue today are clearly more severe, because this is a real war and a humanitarian crisis, not a trade dispute. But the market’s sharp reactions to even the suggestion of a ceasefire are a reminder that waiting for certainty can mean missing a large part of the recovery.

Our instinct is that the conflict’s current form is unlikely to persist for many more weeks, not because the end state is obvious, but because the present path is unsustainable. Either Iran’s missile capacity will become degraded enough to eliminate its ability to threaten traffic through the Strait of Hormuz, or the global economic pain caused by energy disruption and constrained transit through the Strait will generate enough political pressure from US allies and trading partners to force a change in course. The likely outcome is not necessarily a tidy negotiated settlement, but some form of transition away from the current phase of open-ended escalation.

Interest Rates, the Fed, and Positioning

The war with Iran is now the dominant near-term driver of financial markets. Higher energy prices have forced investors to reassess the path of central bank policy rates around the world, with direct implications for both fixed income and equities. Before the war, markets were pricing rate cuts or a prolonged pause from the Federal Reserve, European Central Bank, and Bank of England. Markets are now having to contemplate the possibility of renewed tightening.

Exhibit D: Expected Central Bank Policy Actions by December 2026

Source: Bloomberg, Fiduciary Trust Company. Data as of  March 31, 2026.

The US appears better positioned than many other developed markets because it is less exposed to an oil shock than major energy importers. That relative resilience helps explain why markets are pricing a less dramatic shift in the expected path of US policy rates than for the ECB or Bank of England.

For the Fed, however, the challenge extends beyond the immediate inflationary effects of higher oil prices. Assuming Kevin Warsh is confirmed and takes over as Chair of the Federal Reserve this quarter, he may have to navigate an inflation spike at the same time as the economy is sending more mixed signals beneath the surface. One of the more striking features of the recent environment has been the extent to which economic activity has held up better than job creation. Historically, stronger growth would be expected to tighten labor markets, lift wages, and reinforce inflationary pressure. But if AI is beginning to weaken that transmission mechanism, then the policy framework becomes much more complicated.

Exhibit E: US Real GDP Growth vs Nonfarm Payroll Growth

Over the longer term, the fiscal deficit remains the binding constraint for US policymakers. In theory, persistent deficits and rising Treasury supply should place upward pressure on long term yields. In practice, however, the government’s growing interest burden gives policymakers a powerful incentive to resist any sustained rise in borrowing costs. That does not mean they can control the long end of the curve, but as yields move higher, the pressure on the Fed and Treasury to lean against that move is likely to grow. It was notable that President Trump announced he was postponing certain strikes on Iran just as the 10-year Treasury yield reached 4.3%, the same level it hit last year when he paused the implementation of reciprocal tariffs.

That leaves the Fed with a difficult balancing act. Near-term energy inflation argues for caution. Medium-term AI-driven productivity gains may prove disinflationary. And over the long term, fiscal realities suggest policymakers cannot tolerate a sustained rise in yields.

Conclusion

Coming into 2026, the bullish case rested on several pillars: meaningful fiscal support from the One Big Beautiful Bill, higher tax refunds, easier monetary policy, improving productivity, bank deregulation, and continued heavy investment by large technology companies. Many of those supports remain in place. The problem is that markets now must weigh them against a very different set of near-term risks.

Volatile markets like these are exactly when investment discipline matters most. It can be difficult to resist the urge to react to every headline, but a long-term investment plan only works if it can withstand short-term noise. The goal is to stay anchored in long-term objectives while using volatility to revisit assumptions, re-underwrite key holdings, and add selectively when dislocations create opportunity.

That is especially important in periods like this, when correlations can temporarily rise and traditional diversifiers may not provide much relief in the moment. Diversification does not always work on a day-to-day basis, especially during periods when markets are reacting to the same macro shock. Its purpose is to improve resilience over longer periods and across full market cycles, when different assets and risk exposures tend to respond differently as conditions change.

We will continue to look for opportunities to add to high conviction positions when volatility creates better entry points. In equities, that means distinguishing between genuine AI losers and businesses whose moats are stronger than the market currently assumes. In fixed income, it means using increases in yields to add to higher quality duration.

As always, please reach out to your Fiduciary Trust investment officer with any questions.

Exhibit F: Fiduciary Trust Asset Class Perspectives