Cloud software stocks are navigating a precarious moment, one where technological optimism collides with market skepticism. The early months of 2026 have seen the sector slide further into a downturn, continuing a trend from 2025.

The WisdomTree Cloud Computing Fund has fallen more than 8% this year, while marquee software names like Salesforce, Adobe, and ServiceNow are each down more than 14%. Yet beneath the surface of declining share prices lies a broader narrative: the cloud software industry is facing a structural challenge as generative AI and enterprise AI agents begin to reshape the rules of business.

The crux of the market’s unease is a shift in the value proposition of software itself. For years, enterprise tools thrived on automating repetitive tasks, centralizing data, and providing subscription-based access to specialized workflows. Now, AI agents are emerging with the capability to perform many of these functions without requiring a suite of individual software licenses. Anthropic’s recent launch of Cowork, an AI agent designed to execute complex enterprise tasks, crystallized investor fears that traditional software may soon be bypassed entirely.

“Companies that have spent decades building workflow and collaboration solutions are now facing a fundamental question: can they integrate AI at a pace that keeps them relevant?” said a senior private equity investor who requested anonymity. “Those that can’t may need capital, partnerships, or strategic exits, which is why we’re expecting a wave of consolidation.”

Private equity firms, already long-term buyers of cloud software, see opportunity in the selloff. Orlando Bravo of Thoma Bravo, whose firm has a storied record in enterprise acquisitions, described the current market as a “rare buying window,” particularly for companies that are developing AI agents to complement existing software infrastructure rather than compete solely on their own.

“We’re actively looking at companies that have a platform advantage and are embedding AI in ways that customers actually use,” he said in Davos.

However, the reality is uneven. Analysts such as Jackson Ader of KeyBanc have flagged specific vulnerabilities in the sector. Companies with single-purpose, seat-based applications—Monday.com, Asana, Sprout Social—are particularly exposed. Unlike established ERP or CRM platforms, these firms lack a core system of record and do not operate a multi-product ecosystem, leaving them open to displacement by AI-driven alternatives. Their steep share declines reflect investor doubts over long-term survivability.

Even established, diversified software giants are feeling pressure. Salesforce CEO Marc Benioff told CNBC that the company’s latest quarter was “the best we’ve ever had,” highlighting strong cash flow and broad adoption. Yet market enthusiasm has not followed, underscoring a new investor mindset: financial performance alone is no longer sufficient. In the current environment, companies must demonstrate AI leadership.

Benioff summarized it succinctly, saying: “If you don’t produce a large language model, you’re out of fashion.”

ServiceNow’s response illustrates the dual path available to incumbents: embrace AI aggressively or risk irrelevance. The company announced a partnership with OpenAI to deploy enterprise AI agents, signaling a proactive approach to automation. Yet the market initially punished ServiceNow’s stock, reflecting the deep skepticism about the pace and effectiveness of AI integration.

Smaller companies and niche players face an even sharper reckoning. HubSpot, Atlassian, and Braze have all lost more than 20% of their market value in January alone. Analysts warn that, absent a clear AI strategy, these firms may face investor pressure to explore mergers, sales, or recapitalization. RBC Capital Markets’ Rishi Jaluria suggested that deals without a compelling AI component are unlikely to excite investors, highlighting the way AI is now central to valuation narratives.

Underlying the turmoil is a broader industry tension: the speed of AI adoption versus customer readiness. Companies must not only develop AI-enhanced products but also convince customers to trust and pay for these tools. As Jaluria notes, the pivotal question is how quickly AI agents can move from narrow automation—such as summarizing tasks or generating code—to orchestrating complex enterprise workflows that currently underpin the business models of software vendors.

The coming months will be critical. Earnings season will provide a clearer window into which companies are effectively integrating AI and which are lagging. Investors will be scrutinizing product roadmaps, customer adoption, and real-world agent performance. Firms that demonstrate tangible AI-driven efficiency or productivity gains are likely to emerge stronger, while others may find themselves on the auction block.

In essence, cloud software is at an inflection point. Generative AI and enterprise agents are no longer theoretical threats—they are immediate, market-shaping forces. The sector’s next chapter is expected to reward bold innovation, deep integration, and an ability to convert AI capabilities into real business outcomes. Those who fail to adapt risk being sidelined.

Nvidia CEO Jensen Huang has offered a counter-narrative to the growing anxiety around artificial intelligence and job losses, arguing that the AI boom is set to create a wave of high-paying jobs far from traditional office settings.

Speaking at the World Economic Forum in Davos on Wednesday, Huang said the global rush to build AI infrastructure is already driving demand — and wages — for skilled trades, with salaries reaching into six figures for those helping to construct and maintain what he described as “AI factories.”

At the heart of Huang’s argument is scale. The global race to deploy artificial intelligence is no longer only about algorithms and software models. It is about factories, power systems, cooling plants, fiber networks, and specialized facilities that can house and operate vast amounts of computing equipment. Huang described this moment as the largest infrastructure buildout ever undertaken, measured not only in dollars but in geographic reach and industrial complexity.

That buildout, he said, is already changing who benefits from the AI economy. Chip fabrication plants, data centers, and so-called AI factories require armies of electricians, plumbers, steelworkers, construction crews, and network technicians. These are roles that cannot be easily automated and cannot be filled overnight. As demand surges faster than supply, wages are rising sharply.

Huang told the Davos audience that salaries in some of these trades are nearly doubling, pushing total compensation into six-figure territory for workers involved in building and maintaining AI infrastructure. The implication is that while AI threatens to compress pay and reduce headcount in parts of the white-collar economy, it is creating scarcity — and pricing power — for skilled manual labor.

That view adds an important layer to a week dominated by warnings. Consulting firm Challenger, Gray & Christmas has linked nearly 55,000 U.S. layoffs in 2025 to AI adoption, with companies such as Amazon, Salesforce, Accenture, and Lufthansa pointing to automation and efficiency drives. IMF managing director Kristalina Georgieva captured the prevailing mood when she said AI is hitting the labor market “like a tsunami,” leaving governments and companies unprepared.

Huang does not deny the disruption. Instead, he is arguing that the focus has been too narrow. The AI economy, in his telling, is not a purely digital phenomenon. It is an industrial one, tied to energy systems, land use, supply chains, and construction capacity. Every new model trained and deployed increases demand for physical assets that must be built, installed, and serviced by people.

That argument finds support in Microsoft research released in 2025, which examined how often workers rely on AI tools to complete their tasks. Analyzing about 200,000 Bing Copilot conversations, Microsoft found that roles involving physical work with people or machines showed the lowest reliance on AI assistance. Jobs ranging from painters and plasterers to ship engineers and healthcare support workers were among the least exposed to automation pressure.

In practical terms, that means AI is not flattening the labor market evenly. It is accelerating a long-running divergence. Office roles built around routine information processing are becoming easier to automate or augment, while hands-on technical work tied to complex physical systems is becoming more valuable.

European policymakers at Davos acknowledged the implications. Roxana Mînzatu, the European Commission’s executive vice president for social rights and skills, said the semiconductor industry alone is searching for tens of thousands of vocationally trained workers. Her comments underline a growing concern across Europe and North America: the bottleneck in the AI era may not be software talent, but electricians, technicians, and engineers who can physically deliver projects.

The energy dimension adds another layer of pressure. AI infrastructure is energy-hungry, and regions with high power costs or limited grid capacity face constraints on how quickly they can build. That reality links Huang’s labor optimism to a broader policy challenge. Training workers is only part of the equation. Governments must also expand energy supply, streamline permitting, and modernize grids if they want to capture the industrial upside of AI.

There are social implications as well. For years, political leaders have encouraged university education as the primary path to economic security, even as tuition costs rose and returns became less certain. In the United States, the annual cost of attending a four-year public college increased by about 30% between 2011 and 2023, according to CNBC Make It calculations. Over that period, enrollment fell by roughly 2 million students.

At the same time, skilled trades have gained appeal, particularly among younger workers. Data from the Department of Labor and payroll firm Gusto show that Gen Z now accounts for a growing share of new hires in trade roles, outpacing their representation in the overall workforce. For many, the appeal is straightforward: lower training costs, faster entry into paid work, and wages that now rival or exceed many graduate-level office jobs.

Huang’s message taps directly into that shift. “You don’t need to have a PhD in computer science to make a great living,” he said, framing AI as a force that could rebalance opportunity rather than concentrate it further.

Still, the transition is not frictionless. Scaling vocational training fast enough to meet demand will test education systems that have spent decades prioritizing academic pathways. Labor shortages could delay projects, inflate costs, and slow the rollout of AI infrastructure. And while trade jobs may be safer from automation, they are not immune to economic cycles or policy shocks.

Even so, Huang’s intervention in Davos reframed the AI debate in a way that many executives and policymakers have avoided. The question is no longer only how many jobs AI will eliminate, but which kinds of work it will elevate. If the AI race continues at its current pace, the winners may include not just chip designers and software engineers, but the people wiring, cooling, and powering the factories that make the technology possible.

U.S. Treasury yields held in a narrow range on Thursday, as investors parsed a steady flow of economic data while keeping one eye on an increasingly complex mix of trade signals, geopolitics, and political developments in Washington.

The benchmark 10-year Treasury yield edged higher by just over one basis point to 4.265%, a move that signaled caution rather than conviction. The 30-year yield was largely unchanged at 4.873%, while the policy-sensitive 2-year note climbed by more than a basis point to 3.61%. The muted shifts pointed to a market struggling to reconcile strong domestic fundamentals with rising uncertainty around policy direction.

Early trading leaned slightly bearish for bonds after new labor market data reinforced the view that the U.S. economy remains on a firm footing. Initial jobless claims for the week ended January 17 fell to 200,000, below the 208,000 forecast by economists surveyed by Dow Jones. Claims were marginally higher than the prior week after an upward revision, but the broader trend continues to show limited stress in the labor market.

For bond investors, the implication was straightforward: an economy still generating jobs at a solid pace reduces the urgency for aggressive interest-rate cuts. Chris Rupkey, chief economist at FWDBONDS, said the data fit a pattern of economic growth running well above 3%, with labor indicators pointing to a potentially strong January employment report.

In his view, the resilience of growth and hiring suggests that the economy is performing well without additional intervention. That assessment matters for Treasuries, as expectations around Federal Reserve policy remain one of the dominant drivers of yields, particularly at the front end of the curve.

Later in the session, attention shifted to inflation, where the Commerce Department reported that both headline and core personal consumption expenditures price index readings for November matched expectations. The PCE index is closely followed by Federal Reserve officials, and the absence of any upside surprise helped calm fears that inflation pressures were re-emerging after months of gradual easing.

Still, the data did little to move yields decisively. Investors appear increasingly sensitive not just to economic releases, but to how those figures interact with political signals coming from the White House and the Federal Reserve.

One such signal came from President Donald Trump, who said in an interview with CNBC at the World Economic Forum in Davos that he may have already selected his nominee to replace Jerome Powell as Fed chair. Trump said the shortlist had narrowed sharply, suggesting that a final decision was effectively settled in his mind, though he declined to identify the candidate.

The comment injected an additional layer of uncertainty into markets. Even though Powell’s term still has time remaining, early speculation about the next Fed chair raises questions about the future policy stance of the central bank, particularly at a moment when investors are debating how long rates will remain elevated.

That uncertainty is compounded by scrutiny surrounding Powell himself. The Fed chair recently said he was under investigation by the Department of Justice in connection with the $2.5 billion renovation of the Federal Reserve’s headquarters in Washington. While the issue has not altered policy operations, it has added political noise at a time when markets are highly sensitive to any hint of instability at the central bank.

Geopolitical developments also played a role in shaping sentiment. Trump said he had reached what he described as a “concept of a deal” on Greenland, following earlier remarks that he would not pursue control of the Danish territory through military means. In a subsequent post on Truth Social, he said tariffs announced last week on eight European countries opposing a U.S. takeover would not take effect.

The decision eased immediate trade-related anxiety that had weighed on markets earlier in the week. Tariff threats had contributed to sharp swings across equities, currencies, and bonds, with Treasuries initially benefiting from a flight to safety. Thursday’s pause in escalation removed one source of pressure, leaving yields to drift rather than trend.

The combination of firm economic data, steady inflation readings, and shifting political signals left the Treasury market in a holding pattern. Shorter-dated yields continued to show sensitivity to labor strength and Fed policy expectations, while longer-dated yields suggested investors remain uncertain about the long-term path of growth, inflation, and fiscal policy.

Currently, the bond market appears to be waiting for a clearer catalyst. A stronger-than-expected jobs report could push yields higher by reinforcing the case for rates to stay elevated. On the other hand, renewed trade tensions or sharper political uncertainty could revive demand for safe-haven assets. Until one of those forces asserts itself, Treasury yields look set to remain range-bound, even as the list of risks facing investors continues to grow.