As a result, investors are acquiring more duration exposure through benchmark ownership at a time when long-term interest-rate uncertainty is increasing.

Changing risk characteristics: Historically, IG indices derived a meaningful portion of their risk exposure from financial institutions, utilities and telecommunications companies. Today, investors are increasingly financing capital expenditures tied to:

• AI adoption
• Data-centre utilization
• Cloud-computing demand
• Future monetization assumptions
• Competitive positioning within the AI ecosystem

In other words, credit risk is increasingly connected to companies investing heavily in AI infrastructure, cloud capacity and emerging technologies.

The issue is not that hyperscalers are weak credits. They have some of the strongest balance sheets in the market. Rather, investors must evaluate whether future AI-related investments will generate returns sufficient to justify the scale of capital being deployed. If those returns fail to materialize, the impact is likely to be felt first by data-centre and AI-infrastructure issuers such as Beignet and Sopaipilla, whose credit profiles are more directly tied to the success of the AI buildout.

This changes the opportunity set for credit investors. As AI becomes an increasingly important driver of credit issuance, fundamentals and performance, some traditional assumptions around diversification may need to be revisited. Exposure to different sectors or asset classes does not necessarily mean exposure to different underlying risks if those investments are increasingly linked to the same AI capital spending cycle.

This evolution matters because it changes the nature of diversification.

Unlike hyperscalers, however, many of these issuers lack the scale, profitability and operating history of the hyperscalers themselves. They also are primarily reliant on project financing structures, leasing arrangements and contractual guarantees from the hyperscalers to support funding.

For investors, this creates both opportunity and risk. The opportunity lies in earning higher income from companies that will benefit from greater AI adoption, which is expected to remain the economy's primary growth engine. The risk is that with higher competition and less scale, these companies are even more reliant on AI adoption, the related revenues and long-term utilization rates meeting the market's lofty assumptions than the IG-rated issuers.

This is particularly important because many of these issuers have already become material components of HY benchmark indices and passive investment vehicles, with their exposures likely to continue to grow.

For HY, refinancing may be where AI-related risk becomes more visible. Borrowers with weaker interest coverage, declining enterprise values or unproven monetization may struggle to extend their debt maturities should risk appetite become choppier, particularly if the current interest rate paradigm persists.

At the same time, AI is creating a growing dispersion across credit markets. This dispersion comes at a time when broad credit fundamentals remain supportive. Economic growth, corporate earnings and default trends continue to provide a solid backdrop for credit markets. However, spreads remain near historically tight levels and interest rates are normalizing in the post-zero-rate world, limiting the potential for further spread compression. In this environment, returns are increasingly likely to be driven by issuer selection rather than broad market beta.

Moreover, financing the AI buildout may become a market-capacity issue. While IG markets have thus far absorbed record levels of issuance, the growing amount of debt coming to market may affect valuations and create relative value opportunities as some issuers are required to offer more attractive pricing to investors.  This dynamic is particularly relevant for large institutional investors, many of whom operate under issuer concentration limits designed to manage portfolio risk.

This environment increasingly highlights the importance of credit research and active fixed income management.

As AI-related issuance continues to reshape the market, the opportunity for active management is therefore not simply to avoid technology exposure. It is to distinguish between issuers, valuations and structures within a rapidly changing credit landscape and to manage the concentration and duration risks that passive benchmark ownership can increasingly embed.

The second major shift is occurring in monetary policy.

Following the Global Financial Crisis (GFC), the Fed increasingly relied on communication as a policy tool. Initiated by Chair Greenspan, and under Chairs Bernanke, Yellen and Powell, forward guidance became a central pillar of monetary policy. Investors were provided with extensive information regarding the likely path of interest rates, the economic outlook and the Fed's reaction function. Over time, markets became highly conditioned to interpreting central bank communication, and understanding what the Fed was likely to do often became almost as important as understanding the underlying economic data itself.

Chair Kevin Warsh has signaled a different approach. Rather than emphasizing extensive forward guidance, the Fed is providing investors with current information while placing greater responsibility on market participants to interpret incoming data and determine what policy actions may follow. This does not mean the Fed has become less transparent. It means investors can no longer rely on the same degree of policy pre-commitment that characterized much of the post-GFC era. The market therefore must place greater weight on incoming economic data, inflation, employment and financial conditions when assessing the future path of monetary policy.

This shift is important because it comes at a time when monetary policy is no longer the only major force influencing bond markets.

For much of the post-GFC era, monetary policy was the dominant force influencing financial markets. Today, rising government borrowing requirements, industrial policy initiatives, defense spending, energy investment and AI-related spending are increasing the influence of fiscal policy and playing a larger role in determining long-term interest rates and term premia.

At the same time, markets are reassessing the level of the neutral policy rate. Investors increasingly question whether the post-GFC environment of structurally low interest rates remains applicable given stronger fiscal spending, rising investment requirements and a more resilient economy. As a result, a portion of the increase in long-term yields reflects not only a higher term premium, but also a repricing of where markets believe policy rates may settle over the longer term. 

The combination of uncertainty around the neutral rate, growing fiscal deficits and substantial government borrowing requirements is contributing to higher long-term yields and increased volatility across fixed income markets.

Government bond yields have climbed to their highest levels in decades across most developed countries, driving bond prices lower as a result. This recent selloff has been concentrated almost entirely in longer-term maturities, i.e., 10-, 20- and 30-year bonds. That distinction matters: this is not a reaction to next month’s Fed decision. Rather, it reflects a deeper shift in how investors view long-term deficits, inflation, and future demand for government debt.

The recent rise in global bond yields reflects both a repricing of the expected path for monetary policy and a higher term premium across advanced economies. While expectations for further rate hikes may diminish as inflation moves closer to target, the rise in term premia could prove more persistent.

Investors are demanding greater compensation for holding long-dated bonds amid increased uncertainty around fiscal sustainability, the geopolitical environment and the policy framework that has anchored markets for much of the past several decades.

Importantly, this is not just a U.S. phenomenon. Term premia have risen across most advanced economies, including Canada. Similar dynamics have been evident in Europe, where long-term yields have risen alongside changing fiscal, growth and policy expectations. The result has been a broad-based increase in long-term borrowing costs across developed markets.

At the same time, traditional sources of demand for government bonds are becoming less reliable. Foreign central banks continue to diversify reserves, while Japanese institutions are increasingly repatriating capital as domestic yields become more attractive. 

Meanwhile, the corporate sector is becoming a significant competitor for investor capital. Companies are issuing substantial amounts of debt to finance AI-related infrastructure, including data centres, semiconductor facilities and digital networks. This wave of issuance is competing directly with sovereign debt for the same pool of investor capital.

These forces are occurring at the same time and are contributing to upward pressure on long-term yields.

The rise in long-term yields has direct implications across fixed income markets.

Bond prices have declined, and the longest maturity bonds have experienced the largest losses. Corporate borrowing costs remain elevated. Credit spreads have remained relatively stable so far, but the unprecedented volume of new corporate debt absorbing investor demand can create pricing pressure for new issuers.

At the fiscal level, higher yields increase interest costs, which widen deficits and put further upward pressure on yields.

One of the most important implications for bond investors is that the forces affecting interest rates are not the same across the yield curve.

The front end is primarily influenced by inflation pressures and expectations for central bank policy. The belly of the curve is increasingly affected by the large amount of corporate issuance, particularly from hyperscalers and companies financing AI-related investment.

At the long end, fiscal concerns, government borrowing requirements, changing demand from traditional buyers and a higher term premium are becoming more important.

This creates a more complex interest-rate environment than simply asking whether rates will go up or down.

While some of these pressures could be resolved relatively quickly, the deeper structural forces—including fiscal deficits, increased government borrowing, changing sources of demand for government bonds and growing competition for capital from corporate borrowers—are likely to be a multi-year trend.

Higher starting yields therefore create opportunities for long-term investors and income-focused investors. High-quality bonds now offer some of the most attractive income potential in nearly two decades. At the same time, investors need to consider how much duration they want to own and where along the yield curve they are being compensated for the risks they are taking.

This environment rewards investors who can interpret economic data, assess the different forces driving the yield curve and form differentiated views on rates.

The opportunity is not simply to add duration because yields are higher. Different parts of the curve are being driven by different factors, and those factors can evolve at different speeds.

Active management can therefore play an important role in positioning portfolios across the curve, managing overall duration exposure and adjusting allocations as the economic and fiscal outlook changes. 

The key is that the opportunity set is not static. As the forces driving rates change, the most attractive part of the yield curve can change with them.

Viewed independently, each development is important. Viewed together, they become even more significant.

Hyperscaler issuance is increasing duration, concentration and technology exposure within credit benchmarks. At the same time, a changing Fed communication framework, rising fiscal influence and growing competition for capital are contributing to greater uncertainty around the future path of interest rates.

The result is a market where investors face more issuer-specific risk, more duration risk and a wider range of potential outcomes than in the past.

Importantly, these two structural changes are also becoming increasingly connected. AI-related issuance is concentrated in longer-maturity debt, meaning that credit risk and interest-rate risk are becoming more closely connected. Investors therefore need to evaluate both the economics of AI investment and the future path of rates at the same time.

That combination can increase dispersion across issuers, sectors and maturities, creating an environment where active management can play a more meaningful role.

The opportunity today is not simply that bond yields are attractive. The opportunity is that fixed income markets are undergoing structural change.

Benchmarks are changing. Risk concentrations are changing. Monetary policy communication is changing. Fiscal policy is becoming more important. And the interaction between credit markets and interest-rate markets is changing.

These are precisely the types of environments where active management can add value.

For years, fixed income investing was often dominated by broad market exposure and duration management. Today, investors increasingly need to evaluate:

• Which issuers deserve financing.
• Which AI-related risks are adequately compensated.
• Which maturities offer the most attractive risk-adjusted returns.
• Whether benchmark indices continue to provide meaningful diversification relative to equity portfolios.
• Whether rising fiscal borrowing will change the behavior of long-term interest rates.
• How much duration risk investors want to own given the changing drivers of the yield curve.

In other words, investors increasingly need to make active decisions about the risks they want to own.

The role of the active manager is no longer simply to outperform a benchmark. It is also to determine whether the benchmark itself remains the best representation of the risks investors actually want to own.

That is why the return of active fixed income may be one of the defining investment themes of the next decade.