AI Is Creating Winners and Losers

A majority of investors still believe the rally has room to run.

• 65% of respondents expect the “Magnificent Seven” to move higher after earnings
• But confidence is split on how strong that upside will be

The reason is simple: AI is no longer a uniform growth story. Instead, it’s creating a gap between:

• Hardware companies building the infrastructure
• Software firms struggling to defend their value

Chip Stocks Are Dominating the Market

The biggest winners so far are semiconductor companies.

• The VanEck Semiconductor ETF (SMH) has surged, including a massive 28% jump this month alone
• Meanwhile, the iShares Expanded Tech Software ETF (IGV) just posted its worst quarter since the 2008 financial crisis

This marks the widest outperformance of chips over software on record. Companies like Nvidia continue to benefit from massive demand for AI infrastructure, including data centers and advanced chips.

Software Faces a New Threat

While hardware thrives, software is entering a more uncertain phase. According to market participants, AI is turning some software into a commodity.

Lower barriers to entry and low switching costs mean:

• Some products can be easily replicated or replaced
• Competitive advantages are eroding faster
• Profitability could come under pressure

In short, not all tech companies are equally protected in the AI era.

Massive Spending, But Growing Doubts

The AI boom is being fueled by an enormous wave of investment.

• Up to $1 trillion in capital expenditure is expected over the next year
• Spending is spreading beyond tech into energy and infrastructure

But investors are starting to question whether it’s justified.

• More than half of survey participants said AI spending may not deliver expected returns
• Still, optimism is rising slightly, with 41% now supporting the investment case

Rising Costs Add Another Layer of Risk

At the same time, costs are increasing across the board.

• Energy prices are rising, especially with oil above $100
• Chip production requires huge amounts of power
• Higher input costs could limit output or reduce margins

Despite this, the strength of AI-related stocks has helped support the broader market, even in a challenging macro environment.

The AI boom is not ending. It’s evolving.

• Chips and infrastructure are leading the rally
• Software is becoming more vulnerable
• Spending is massive, but not fully trusted

The result: a tech market that looks strong from the outside… but is increasingly divided inside. AI is still driving growth. But now, it’s deciding who wins and who falls behind.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

Related: ETFs vs Mutual Funds: What Investors Need to Know in 2026

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Google is reportedly in talks with the US Department of Defense to allow the Pentagon to use its Gemini AI models in classified environments, according to recent reports.

The potential agreement would enable the military to deploy Google’s AI across “all lawful uses”, significantly expanding the company’s role in government and defense technology.

Safeguards under discussion

As part of negotiations, Google is proposing limits on how its AI can be used, including:

• No domestic mass surveillance
• No fully autonomous weapons without human oversight

These conditions highlight growing concerns around AI ethics in military applications. The deal would mark a major step for Google as it:

• strengthens ties with the US government
• competes more directly in the military AI space
• positions Gemini as a key tool in national security infrastructure

AI is becoming central to defense strategy. As the US accelerates adoption of advanced AI to improve efficiency and decision-making, Big Tech companies like Google are moving closer to the core of military operations.

The post Google in Talks With Pentagon to Deploy AI in Classified Systems first appeared on Finblog.

For months, the market narrative has been simple: war in the Middle East pushes oil higher, which feeds into inflation. But beneath that, a more structural risk is emerging. The same conflict that is disrupting energy flows is now beginning to affect semiconductors, data centers, and the cost of building AI itself.

At the center of the issue is the Strait of Hormuz, one of the world’s most important shipping routes. When flows through the strait are threatened, oil prices rise. That alone matters for AI, because modern data centers consume enormous amounts of electricity. Higher energy prices mean higher costs to train and run AI models.

But energy is only one side of the story.

A less obvious but more critical disruption is forming in the semiconductor supply chain. South Korea, home to chip giants like Samsung and SK Hynix, relies heavily on the Middle East not just for energy, but also for helium, a key material used in chip manufacturing. Around one-third of global helium supply comes from Qatar, and current disruptions are making that supply harder to access.

That creates a chain reaction. If helium and energy become constrained, chip production slows. When chip production slows, memory prices rise. And when memory prices rise, the cost of building and scaling AI systems increases.

This is where the impact becomes more serious.

The AI boom has been built on the assumption that compute will continue to scale efficiently. Companies like OpenAI and Anthropic are already spending billions on infrastructure, often without turning profits. If both energy and hardware costs move higher at the same time, the economics of AI become more challenging.

So the key question becomes: can AI continue to scale if its core inputs become more expensive?

There is also a timing issue. Unlike short-term market shocks, this situation may not resolve quickly. Iran does not need to directly confront larger military forces to disrupt global trade. By targeting shipping routes and increasing risk in the region, it can create sustained pressure on supply chains at a relatively low cost.

That means the current environment could last longer than markets expect.

At the same time, this pressure is forcing the industry to rethink how AI infrastructure is built. One idea gaining traction is the use of on-site energy solutions, including nuclear microgrids, to power data centers independently. If energy becomes a constraint, companies may need to generate their own power rather than rely on unstable global markets.

This shift would mark a major change in how the tech industry operates.

For now, the AI story has not broken. Demand remains strong, and investment continues. But the foundation supporting that growth, cheap energy, stable supply chains, and falling compute costs, is starting to show cracks.

And that leaves markets with a new reality to consider:

The AI boom is still intact, but it is becoming increasingly exposed to global geopolitical risks.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

Related: Trump Warns Iran: Deal or Energy Sites Will Be Hit

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Technology companies delivered solid results in the latest earnings season, driven largely by rising demand for AI chips, data centers, and cloud infrastructure. However, market reactions have been mixed, with many tech stocks falling despite strong financial performance.

AI Demand Drives Strong Earnings

Major companies reported strong revenue growth fueled by AI related spending.

• Nvidia’s revenue rose 73% year over year
• Semiconductor firms like Monolithic Power Systems and Broadcom exceeded expectations
• AI infrastructure companies including Applied Materials, Lam Research, and KLA projected strong growth

Demand for data centers and AI computing infrastructure is expected to remain strong as companies continue building large scale AI systems.

Stocks Not Following Earnings

Despite the positive earnings picture, many tech stocks have struggled in the market this year.

Several major software companies have seen sharp declines:

• ServiceNow and Salesforce down about 26%
• Oracle down over 23%
• Adobe down more than 22%
• Microsoft down over 16%

This disconnect suggests investors are increasingly focused on long term risks and AI investment costs, rather than short term earnings growth.

Key Takeaways

• Morningstar analysts say that positive fourth-quarter earnings show there’s plenty of room for the AI trade to run, even as tech stocks lag.
• Strong demand for AI products and infrastructure helped tech revenue surge, but questions remain around how long that can last.
• Software companies continue to see a mismatch in earnings growth and share price losses, with analysts tracking whether hefty AI-related investment will yield long-term returns.

Big Spending Raises Questions

Tech companies are investing heavily to stay competitive in AI.

For example, Microsoft recently announced $37.5 billion in capital spending, a sharp increase from $22.6 billion a year earlier, largely aimed at expanding data center capacity. Analysts say the key question now is whether these massive investments will eventually translate into sustainable profits.

Software Sector Faces Biggest Uncertainty

Software companies appear to face the most skepticism from investors.

Although many firms reported strong earnings and rising demand for AI powered services, markets remain unsure whether the new AI tools will generate enough revenue to justify the massive spending.

Long-Term Outlook Still Positive

Despite the uncertainty, analysts say AI adoption continues to expand rapidly across industries.

Demand for AI computing power, cloud services, and data infrastructure remains strong, suggesting the technology boom could continue for years.

For investors, the challenge is identifying which companies will turn AI investment into long term growth and which may struggle to justify the massive costs.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

The post What Q4 Earnings Did and Didn’t Tell Us About AI Boom and for Tech Stocks first appeared on Finblog.

The bank argues that excessive declines across sectors reflect investor anxiety rather than fundamental weakness, creating attractive entry points for selective investors.

AI Fear vs. AI Opportunity

Morgan Stanley strategist Andrew Pauker and his team say investors should focus on what they call “AI incumbents”, strong growth companies, and high-quality firms positioned to benefit from AI adoption.

“Nearer-term AI adoption tailwinds help to offset longer-term disruption fears,” Pauker wrote.

The strategists believe the current volatility is typical of major investment cycles, where markets question both the pace of capital spending and which industries could face disruption.

Software Selloff May Be Overdone

Software stocks have been among the hardest hit as investors worry that AI tools could replace traditional enterprise software.

However, Morgan Stanley disagrees with the assumption that incumbents cannot adapt. Instead, they argue AI could expand the addressable market for enterprise software companies.

The bank sees “attractive entry points” in names such as: Microsoft, Intuit, Atlassian

These companies are viewed as capable of integrating AI while maintaining pricing power.

Banks and Finance Seen as Net Beneficiaries

Morgan Stanley also expects financial institutions to benefit over time as AI improves productivity and operational efficiency.

Among the “most defensible” banking names highlighted by analysts: Citigroup, Bank of America, State Street, Truist Financial

In payments and fintech, Morgan Stanley sees AI and agent-driven commerce supporting long-term growth for: Mastercard, Visa

Volatility Is Part of the Cycle

The strategists emphasize that widening volatility bands are normal during transformative investment phases.

“What’s going on now is typical of a major investment cycle,” the team wrote.

While markets remain divided over whether AI spending is excessive or transformative, Morgan Stanley’s view is clear: short-term panic may offer long-term opportunity for disciplined stock pickers.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

Related: The AI Bust is Here. The AI Boom Is Still Going.

AI Boom Could Trigger 38% S&P 500 Crash, Research Scenario Warns

The post AI Panic Is Opportunity for Stock Pickers, Morgan Stanley Says first appeared on Finblog.

Markets had already been shaken on Monday by a widely shared “AI doomsday” research note that imagined a severe economic downturn tied to rapid AI adoption. Bitcoin continued to slide, underscoring broader pressure on risk assets.

AI Boom — and Bust — at the Same Time

AI is creating a rare market dynamic: a boom in infrastructure spending alongside a bust in certain tech stocks.

Companies are pouring billions into AI data centres, chips, and research. Yet shares of firms that could be disrupted by AI, particularly software and services companies, have dropped sharply. The S&P 500 software and services sector has been under heavy pressure this year.

At the same time, even major AI leaders are struggling:

• Microsoft is down 21% this year
• Amazon has fallen 11%
• Alphabet and Meta Platforms have largely stalled

Investors are increasingly concerned about overinvestment in AI infrastructure. According to a Bank of America fund manager survey, managers are now more worried about excessive capital expenditure than insufficient spending, the first time that concern has flipped.

Heavy AI investment requires strong profit growth to justify it. But as more tech giants compete in the space, pricing power may weaken, potentially squeezing margins.

Oracle, which has taken on significant debt to fund AI expansion, has fallen 28% this year.

Infrastructure Winners Stand Out

While software shares struggle, companies tied to building and powering data centers have surged:

• Caterpillar is up 32%
• GE Vernova has gained 27%
• Sandisk is up 181%
• Western Digital has risen 63%
• Seagate Technology has gained 48%

Semiconductor names have been mixed. Nvidia, Broadcom, and AMD are flat to slightly lower this year, while ASML has helped push the broader semiconductor sector up 18%.

The shift reflects a market trying to determine who ultimately benefits from AI’s expansion, and who loses.

Related: AI Boom Could Trigger 38% S&P 500 Crash, Research Scenario Warns

Trade Uncertainty Adds Pressure

Adding to volatility, Trump’s new tariffs have introduced fresh uncertainty. The administration has indicated it may pursue additional trade tools if needed, keeping markets cautious.

Meanwhile: ( Author is watching)

FedEx: The parcel-delivery company filed a lawsuit seeking a full refund plus interest for what it paid in levies stemming from Trump’s tariffs enacted last year.

Novo Nordisk: The Wegovy maker said an obesity drug it is developing with China’s United Laboratories International helped patients lose weight in a clinical trial. Shares fell, however, extending Monday’s losses that followed disappointing results from another trial.

Hims & Hers Health: The telehealth platform’s fourth-quarter sales disappointed, as did its guidance for this quarter. The stock declined around 7% in premarket trading.

Home Depot: The home-improvement retailer is among the companies due to post earnings this morning.

Apple: The iPhone maker will move some production of its Mac Mini desktop computer to the US from Asia, its latest initiative to reshore parts of its vast supply chain.

Whirlpool: The appliance maker said it would issue $800 million in new shares to help pay off its debt and investment in automation. Shares dropped 7.5% in off-hours trading.

Luxury Brands Face a Different Disruption

While AI dominates headlines, another structural shift is happening in luxury goods.

The global luxury resale market reached €50 billion (about $59 billion) last year, according to Bain & Company. That makes resale roughly the same size as the off-price channel used by luxury brands.

Resale is growing faster than traditional luxury retail. Thousands of small resellers now operate through livestreams, Shopify stores, and platforms like Vestiaire Collective. Brands have little control over how their products are displayed or priced in these channels.

Luxury companies face a dilemma:

• Ignore resale and lose control
• Or participate and risk weakening brand exclusivity

The resale market is approaching a tipping point, and brands are still deciding how to respond.

Broader Market Unease

The rapid rotation between AI winners and losers has left investors uneasy. The scale and speed of the boom-and-bust dynamic raise questions about whether markets are correctly pricing long-term outcomes.

For now, capital continues flowing into physical infrastructure tied to AI, while software valuations reset lower. The ultimate economic impact of AI, whether a productivity boom or profit squeeze, remains uncertain.

Source: The Wall Street Journal, Markets A.M. Newsletter, James Mackintosh, February 2026.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

The post The AI Bust is Here. The AI Boom Is Still Going. first appeared on Finblog.

The commentary, published by Citrini Research and guest co-author Alap Shah of Lotus Technology Management, presents a hypothetical look back from mid-2028. In that scenario, unemployment rises to 10.2%, and the S&P 500 falls 38% from its October 2026 peak near 8,000.

The authors stress that the piece is not a prediction, but a stress-test of a risk that markets may be underestimating.

Related: Could these 6 non-AI chip stocks be the next leg of the AI boom?

The Core Argument: AI Success Could Hurt Jobs

The thesis begins with “agentic AI”, systems that automate complex white-collar tasks. In the scenario, software-as-a-service companies see declining demand as clients adopt more advanced AI tools that replace traditional workflow systems.

Companies respond by cutting headcount and using cost savings to invest further in AI, accelerating job losses.

By early 2027, AI agents are assumed to be embedded into smartphones and business systems. These systems automatically optimise consumer choices, cancelling subscriptions, finding cheaper alternatives, and reducing brand loyalty.

The result: lower corporate margins and shrinking profits.

The disruption spreads to payments, with stablecoins replacing traditional processors such as Mastercard, adding further sector pressure.

From Sector Risk to Systemic Risk

Citrini argues the dynamic becomes systemic because AI may differ from previous technological revolutions.

Unlike past innovations, displaced white-collar workers cannot easily move into “AI management” roles, since AI can already perform those tasks.

White-collar employment represents roughly 50% of US jobs and 75% of discretionary consumer spending, according to the scenario. A hiring collapse in that segment weakens consumption across the economy.

Bond markets notice first. Treasury yields fall as investors price in economic slowdown. By February 2027, initial jobless claims spike to 487,000, triggering a 6% drop in the S&P 500 in a single move. A recession follows in the second quarter.

Related: Two Stock Market Trends Investors Should Know

Financial Contagion Scenario

The research outlines a chain reaction in financial markets:

• Private credit firms mark down software investments
• Moody’s downgrades billions in debt
• Software-backed loans default
• Insurers linked to private credit are forced to raise capital or sell assets

San Francisco home prices fall 11% in the scenario. Policymakers struggle to respond, reluctant to tax high-growth AI sectors to support displaced workers.

Meanwhile, the AI sector continues expanding, even as the broader economy weakens.

Market Reaction and Debate

The note generated strong online reactions. Some analysts argue the disruption risk is overstated, suggesting governments could respond with re-industrialisation or fiscal stimulus.

For now, markets remain relatively stable near record highs.

As of the latest data:

Yet volatility beneath the surface is rising. Individual stock volatility is widening sharply compared to the broader index, according to Bianco Research.

The scenario raises a central question: What if AI works too well?

If productivity gains come alongside widespread white-collar job losses and shrinking consumer demand, the stock market could face pressures few models currently account for.

Citrini emphasizes the exercise is about modeling an underexplored risk, not forecasting doom. But as AI adoption accelerates in 2026, investors are increasingly debating whether the next phase of technological growth could carry unexpected economic consequences.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

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After a bruising start to the week, US stock futures now suggest some stabilization. But the bigger question remains unresolved: is this just a painful reset, or the start of something much larger?

The question investors always ask too late

Interest in the phrase “AI bubble” has surged recently, especially after market volatility shook investor confidence. Historically, this question is rarely asked at market tops. It usually appears after prices wobble, not before.

And despite the noise, the AI boom has been massive and persistent. Valuations are stretched, capital spending is enormous, and expectations are sky-high. That combination has prompted some of the most respected voices in finance to weigh in, with sharply different conclusions.

The case for a bubble, according to history’s skeptics

Veteran investor Jeremy Grantham and financial historian Edward Chancellor argue that markets are once again displaying classic bubble characteristics. In a recent essay, they compared today’s AI enthusiasm to more than 300 historical market manias.

Their conclusion is blunt: this looks like one of the great bubbles. However, even they concede that the final signs of a major top may not yet be in place.

Grantham, who openly calls himself a “permabear,” has a long track record of spotting excesses early, sometimes painfully early. That nuance matters, because calling a bubble too soon can be just as costly as missing one entirely.

A calmer view: why this may not be a bubble yet

A very different framework comes from economist and fund manager Owen Lamont, who argues that despite frothy conditions, the AI boom does not yet qualify as a true bubble.

Lamont uses what he calls the four horsemen of bubbles:

1. Overvaluation
2. Bubble beliefs and hype
3. Large inflows from investors
4. Equity issuance by insiders

According to him, only three out of four are present today.

Valuations are undeniably high. Investor excitement is everywhere. Retail participation is strong.
But one crucial signal is missing: massive equity issuance.

In past bubbles, corporate insiders rushed to sell shares through IPOs, SPACs, and secondary offerings, effectively handing risk to the public. Today, the opposite is happening. US companies have been buying back nearly $1 trillion in stock, thereby shrinking the public float rather than expanding it.

That behaviour suggests the so-called “smart money” is not yet acting as if prices are unsustainably high.

Big spending does not automatically mean irrationality

Another concern haunting markets is whether the enormous spending on AI infrastructure will ever pay off. Professor Aswath Damodaran takes a pragmatic view.

He argues that many transformative technologies require heavy, uncertain investment upfront. Railroads, oil drilling, and the internet all experienced periods of overbuilding. Some investments failed, but the overall innovation reshaped the economy.

His message is simple: negative returns on some AI projects do not automatically mean the entire sector is a bubble. They may simply reflect the cost of discovering which models and platforms will ultimately win.

Why today still looks different from past crashes

Goldman Sachs strategist Peter Oppenheimer adds another layer of context. Unlike the dotcom era, today’s AI leaders are profitable, cash-rich, and deeply embedded in the global economy. That financial strength gives them far more staying power than many tech firms had in 2000.

That does not guarantee safety. Even cash-rich companies can waste capital. But it reduces the risk of a sudden, system-wide collapse driven by weak balance sheets.

The real warning sign investors should watch

If history is any guide, the moment to worry is not when markets argue about bubbles, but when insiders rush for the exits.

Lamont points to a simple signal: a flood of IPOs from companies eager to sell shares at inflated prices. That phase often brings fraud, speculative listings, and aggressive storytelling aimed at retail investors.

So far, that wave has not fully arrived. But the calendar matters. Reports suggest that 2026 could mark the start of an IPO megacycle, with major private firms preparing to go public. If that happens, the market narrative could shift quickly.

Boom first, bubble later?

For now, the evidence points to an uncomfortable but important conclusion. The AI trade may be overextended in places, volatile, and emotionally charged, but it does not yet display the full anatomy of a historic bubble peak.

That does not mean investors are safe. It means the easy phase of the rally may be over, while the dangerous phase has not yet begun.

In past cycles, the biggest gains often came before the final excess. The biggest losses followed only after everyone agreed there was no risk left at all.

For investors trying to navigate this moment, the real task is not predicting the end, but recognizing the signal when it finally appears.

Resources: WSJ, Fortune

Related: ‘Get Me Out’: AI Fears Trigger a Software Stock Selloff

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

The post Are We in an AI Bubble or Just the Early Innings? first appeared on Finblog.

President Donald Trump used his Davos speech to stress that the US must rapidly expand domestic power generation to support AI growth.

“We needed more than double the energy currently in the country just to take care of the AI plants,” Trump said, adding that the US is now opening energy facilities instead of shutting them down.

Energy demand surging fast

According to Goldman Sachs, global data-center power use is set to jump from 55 gigawatts to 84 gigawatts in just two years. But the supply side is struggling to keep up.

Heavy machinery makers face multi-year backlogs for gas turbines. Connecting new plants to the US power grid can take more than a decade. Nearly half of US transmission equipment is near the end of its useful life, Bank of America estimates.

Schneider Electric CEO Olivier Blum summed up the challenge:

“AI is the digital engine of growth, but it is also a massive consumer of energy.”

Industrials surge on infrastructure boom

Investors are already positioning for what Nvidia CEO Jensen Huang called “the largest infrastructure build-out in history.”

• The Industrials sector is up 17.5% over the past year
• Caterpillar has jumped 58%
• Jensen Huang says AI will require trillions of dollars in new spending

BlackRock added that power availability and grid reliability are now “the key constraint” for AI growth.

Nuclear makes a comeback

One of the biggest themes at Davos was what many called a “nuclear renaissance.”

Trump said the US plans to add 300 gigawatts of new nuclear capacity by 2030, calling modern nuclear technology safe and affordable.

“We’re going heavy into nuclear… the progress they’ve made is unbelievable,” Trump said.

Bank of America now expects nuclear to become a $10 trillion industry, with 18 gigawatts of new capacity added annually through 2040.

Who wins the AI race

Microsoft CEO Satya Nadella framed the competition bluntly:

“Are you a cheap producer of energy? Can you build data centers? That will decide who wins.”

Big Tech firms including Amazon, Microsoft, Google, and Meta are preparing to lift AI spending again in upcoming earnings. But HSBC warns that capacity constraints will persist through 2026 due to long construction timelines.

AI demand is not slowing. But power shortages, aging grids, and slow infrastructure rollouts now threaten to cap growth.

As Davos made clear, the next AI winners may not be the best chip designers, but the countries and companies that can build power plants and grids the fastest.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

Related: Davos Turns Into an AI Summit: What to expect?

The post AI Power Boom Dominates Davos as Leaders Warn Energy Will Decide the 2026 Tech Race first appeared on Finblog.

Corporate Bond Trading Hits Record Levels

Last year saw an average of $50 billion worth of corporate bonds traded each day, a new high that beat the $46 billion daily average in 2024, according to data from Crisil Coalition Greenwich. That figure covers both investment-grade and high-yield debt, reflecting a surge in market activity driven by heavy borrowing and active secondary trading.

Traders say two main forces are behind the record volumes:

1. AI-related borrowing: Many companies are issuing bonds to finance large AI infrastructure investments, such as data centers, which creates new debt that investors then trade in the secondary market.
2. Private credit expansion: Growth in private credit markets, where institutions provide direct loans or private bonds, has expanded the pool of corporate debt and encouraged more trading activity as investors look for liquidity.

Morgan Stanley and JPMorgan Chase expect high-grade US corporate bond issuance to hit record levels in 2026, as firms continue to tap debt markets for AI-related projects and other strategic spending.

Convertible Bonds Surge to 24-Year High

Strong demand for financing tied to AI has also pushed sales of convertible bonds — debt that can be converted into equity, to their most active level in over two decades. Bloomberg reports that companies raised around $166.5 billion in convertible bond deals in 2025, the most since 2001, as issuers seek cheaper ways to fund growth and innovation.

Major technology firms, including names such as Alibaba, Lumentum, and Super Micro Computer, have tapped these convertible markets to support AI expansion, helping to fuel this spike in issuance.

What’s Driving the Trend

Market participants point to several key drivers behind the corporate debt boom and elevated trading volumes:

• Capital-intensive AI deployment: Building and scaling AI infrastructure, especially data centres and advanced computing facilities, requires large amounts of upfront capital. This leads companies to issue long-term debt to cover these costs, which then fuels secondary trading as investors adjust portfolios.
• Private credit growth: As private credit becomes a larger share of corporate financing, more debt is being created outside traditional bank lending, expanding the supply of bonds and creating new trading opportunities.
• Active trading strategies: New trading methods, including electronic execution, portfolio trading, and high-speed strategies, have made bond markets more dynamic and accessible, helping narrow price spreads and encourage participation.

Market Outlook

With AI spending expected to remain high and private credit markets continuing to grow, analysts see corporate bond trading staying elevated in 2026. Some Wall Street firms even project record levels of investment-grade debt issuance this year as companies refinance old obligations and fund next-generation technology projects.

The result is a corporate debt market that not only supports technological expansion but is increasingly central to overall credit market activity, shaping investor strategies in both public and private fixed-income arenas.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

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The post AI Boom and Private Credit Surge Push Corporate Bond Markets to New Records first appeared on Finblog.