Recently, Wall Street has been permeated with a sense of &#34;AI anxiety.&#34;
The market is concerned that with the rise of Generative AI (GenAI) and Agentic AI, many traditional &#34;service + cycle&#34; companies—especially in software, information services, and financial intermediation—will be completely disrupted. This panic has led to indiscriminate selling in related sectors.
However, this may represent a significant pricing error.
On February 25, Morgan Stanley's U.S. Equity Strategy and Thematic Team released a research report indicating that the recent U.S. stock market has overreacted to the &#34;AI disruption theory.&#34;
First, after the sharp decline, the group viewed as &#34;disruptive targets&#34; currently accounts for only 13% of the total market capitalization of the S&amp;P 500. This proportion explains why the overall pullback of the major indices has been limited recently, while there has been turmoil within the sectors.
Second, the valuations and crowding of this group are at extremely low levels. According to Morgan Stanley's data, the relative valuation of the &#34;service + cycle&#34; sector is at the 9th percentile since 2010, nearly in the historically cheapest range. Meanwhile, institutional net exposure has also dropped to the 20th percentile historically, indicating a state of extreme underweight.
Morgan Stanley bluntly stated: &#34;The bearish view on GenAI seems to underestimate the ability of established software vendors to participate in this round of innovation.&#34;
In fact, the groups that have been sold off have not only not been disrupted, but are also, according to Morgan Stanley's thematic team's AI mapping analysis, the groups with the highest AI adoption rates and strongest pricing power (ranking in the top third).
The &#34;victims&#34; in the market are actually the biggest &#34;beneficiaries.&#34; These groups, which have seen significant declines, actually have a very high concentration of AI adopters.
<img src="https://imageproxy.pbkrs.com/https://wpimg-wscn.awtmt.com/46ad1d71-29ec-44aa-9af7-a99a98cf0c28.png?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg" alt="" original-src="https://imageproxy.pbkrs.com/https://wpimg-wscn.awtmt.com/46ad1d71-29ec-44aa-9af7-a99a98cf0c28.png"/>
<h2>Quantifiable benefits are already evident; it's not just a pie in the sky, but real money</h2>
Investors generally doubt: Can AI really save money or generate profits for companies at this stage? The data provides a positive answer.
The Morgan Stanley team analyzed over 10,000 earnings reports and conference calls using AI models. The results show that companies are realizing substantial AI dividends, and the momentum is continuing to strengthen.
In the recently concluded fourth quarter of 2025, 30% of companies identified by analysts as &#34;AI adopters&#34; mentioned at least one &#34;quantifiable financial impact&#34; from AI during their conference calls.
This proportion was 24% in Q3 2025 and only 16% in Q4 2024. For the broader S&amp;P 500 constituents, this proportion has also risen to 21%.
Morgan Stanley stated: &#34;The most frequently mentioned quantifiable benefits are primarily concentrated in 'financial impacts' (including revenue growth and cost savings), and this mention volume has doubled compared to the previous quarter.&#34;
Reflecting on the fundamentals, AI adopters with strong pricing power are not only seeing their forward net profit margin expectations unscathed but are actually accelerating expansion
Morgan Stanley expects that the adoption of AI will contribute 40 basis points to the overall profit margin growth of the S&amp;P 500 index by 2026.
<img src="https://imageproxy.pbkrs.com/https://wpimg-wscn.awtmt.com/be402a75-cec1-472b-a309-5204f247eef2.png?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg" alt="" original-src="https://imageproxy.pbkrs.com/https://wpimg-wscn.awtmt.com/be402a75-cec1-472b-a309-5204f247eef2.png"/>
<h2>Data Confirms the Profit Expansion of &#34;AI Adopters&#34;</h2>
The report shows that between 2024 and 2025, the EBIT profit margin of AI adopters expanded by 310 basis points, at a rate twice that of the MSCI Global Index during the same period. Morgan Stanley analysts estimate that about 80% of the benefits brought by AI adoption will be reflected in improved cost efficiency.
For example, Citibank stated: &#34;So far this year, AI-driven automated code reviews have exceeded 1 million, greatly enhancing developer productivity, with this single innovation saving approximately 100,000 hours per week.&#34;
European companies are the most aggressive in their actions. Surveys show that as much as a net 35% of European companies plan to reduce their workforce using AI, far exceeding the slightly above 10% level in other regions. This directly points to a stronger profit margin performance in the future.
<img src="https://imageproxy.pbkrs.com/https://wpimg-wscn.awtmt.com/cd20172f-edeb-49f6-a78d-b7e59936c27e.png?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg" alt="" original-src="https://imageproxy.pbkrs.com/https://wpimg-wscn.awtmt.com/cd20172f-edeb-49f6-a78d-b7e59936c27e.png"/>
<h2>Historical Reflection: Insights from the 2007 Smartphone Era</h2>
To clarify the current market logic, Morgan Stanley rewinds time to 2007.
At that time, the iPhone had just been released, and the market was similarly caught in a &#34;disruption panic.&#34; Industries such as gaming, PCs, printers, GPS, and desktop software were considered to be facing existential threats.
Data tells us that in the years following the iPhone's release, the performance of these &#34;disrupted concept stocks&#34; was extremely polarized.
Facing similar shocks, Google rose by 28% due to successfully seizing advertising opportunities in the mobile era, while Nokia plummeted by 73%.
After testing multiple fundamental variables, Morgan Stanley found that the most critical indicator determining stock price performance in the face of epoch-making technological shocks is the change in &#34;forward earnings.&#34;
In other words, those who can leverage AI for profit growth will ultimately prevail in the capital markets. Since the end of 2023, the upward revision of earnings for AI adopters has reached about twice that of AI disruptors, and this gap is widening as investment returns accumulate.
For instance, after the iPhone's release, the Spearman rank correlation coefficient between forward earnings and stock price performance reached as high as 0.9 (very strong correlation).
Morgan Stanley concluded: &#34;What we are currently experiencing is a typical characteristic of a significant investment cycle. Capital will flow not only to structural leaders but also to cyclical leaders. A bottom-up stock selection strategy is particularly important at this time.&#34;
<img src="https://imageproxy.pbkrs.com/https://wpimg-wscn.awtmt.com/c7c0ac5c-0869-4bd7-b196-af86ca301eeb.png?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg" alt="" original-src="https://imageproxy.pbkrs.com/https://wpimg-wscn.awtmt.com/c7c0ac5c-0869-4bd7-b196-af86ca301eeb.png"/>
<h2>Moats Are Deeper Than Expected: Compliance, Trust, and Proprietary Data</h2>
In response to the AI impact faced by specific industries, analysts at Morgan Stanley provided extremely detailed logical breakdowns, revealing what constitutes true disruption and what is mere panic:
Software Industry: Panic Peaks, AI is Not a &#34;New Category&#34; but a &#34;New Capability&#34;
The software sector has recently experienced a dramatic valuation decline. The current average valuation multiple (EV/Sales around 4.4 times) has fallen back to the low levels seen during the extreme panic over cloud computing from 2014 to 2016.
The market has &#34;three major concerns&#34;: AI startups stealing market share, the collapse of the seat-based charging business model, and GPUs driving up costs and suppressing profit margins.
However, Morgan Stanley bluntly stated that these concerns are misplaced: &#34;Generative AI fundamentally expands the capabilities of enterprise software. The issue is not whether software can ultimately monetize during this innovation cycle, but who will participate in building these additional capabilities.&#34;
Morgan Stanley believes that AI essentially enhances the capabilities of enterprise software, addressing the pain point of &#34;unstructured data&#34; that traditional software cannot handle. Existing giants with distribution channels, proprietary data, and workflow control are, in fact, the biggest beneficiaries.
Consumer Finance and Payments: AI Cannot Replace Trust and Compliance
Recent market concerns suggest that &#34;Agentic AI&#34; could autonomously shop, thereby bypassing traditional credit card payment networks.
Morgan Stanley refuted this viewpoint: &#34;We are skeptical that Agentic AI can significantly disrupt the credit card exchange network. This overlooks the importance of trust systems, fraud protection, credit extension, and customer rewards.&#34;
In these highly data-intensive and rule-defined industries, regulatory licenses and balance sheets serve as natural barriers. AI will only accelerate the optimization of underwriting, fraud prevention, and customer service efficiency.
Morgan Stanley expects that banks and consumer finance companies will significantly enhance operational leverage through AI. By 2026 and 2027, large banks' profit margins are expected to improve further.
Internet and E-commerce: The Next Generation of &#34;Agentic Commerce&#34; Will Expand the Pie
Morgan Stanley predicts that &#34;Agentic commerce,&#34; which can autonomously help users compare prices and place orders, will be the next major unlocking point for generative AI.
This will make the consumer funnel more conversational, personalized, and interactive. Morgan Stanley estimates that by 2030, agentic commerce will bring an additional $50 billion to $115 billion in spending to the U.S. e-commerce market.
Platforms with large logistics infrastructure, unique inventory, and strong fulfillment capabilities will not only not be replaced but will also leverage AI to expand their online wallet share.
Transportation: Heavy Assets Reap Benefits, Light Assets Face Risks
Transportation is one of the industries most susceptible to AI impact. However, Morgan Stanley pointed out significant internal differentiation.
&#34;Heavy asset operators&#34; with fleets, railways, and warehouses will be pure beneficiaries of AI. Physical AI (autonomous trucks, humanoid robots) will structurally reduce the labor costs that dominate and enhance asset utilization
On the contrary, &#34;light asset freight brokers (3PL)&#34; that rely on information asymmetry to make money face real disruption risks. Generative AI is commodifying freight matching capabilities, which will continue to squeeze brokers' profit margins.
Real Estate and Commercial Insurance: Highly Complex Non-Standard Businesses Are Hard to Replace
For commercial real estate services and large commercial insurance brokerage firms, the market underestimates the complexity of their business.
Large commercial policies require complex contract disaggregation, risk tower construction, and compliance review. Morgan Stanley points out: &#34;AI cannot replace this expertise that requires market access and regulatory oversight.&#34;
In the commercial real estate sector, the application of AI is more about &#34;augmentation&#34; rather than &#34;replacement.&#34; These labor-intensive businesses will reduce back-office costs through AI. Morgan Stanley estimates that AI automation in the public REITs and CRE services sectors could bring a financial impact of up to $34 billion, equivalent to 16% of their operating cash flow.
<img src="https://imageproxy.pbkrs.com/https://wpimg-wscn.awtmt.com/4da6882f-1dd0-4222-872f-10d06827083b.png?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg" alt="" original-src="https://imageproxy.pbkrs.com/https://wpimg-wscn.awtmt.com/4da6882f-1dd0-4222-872f-10d06827083b.png"/>
<h2>The Truth About the Job Market: Will AI Trigger Mass Unemployment?</h2>
The ultimate concern running through all &#34;AI disruption theories&#34; is that AI will lead to mass unemployment among white-collar workers, thereby triggering economic recession and consumption downgrade.
Morgan Stanley, by reviewing the technological changes over the past 150 years (electrification, tractors, computers, the internet), points out that history shows every major technological innovation profoundly changes the labor structure but &#34;does not replace labor.&#34;
On the contrary, technology creates entirely new job positions. Morgan Stanley expects that with the deepening application of AI, companies will not only need &#34;Chief AI Officers,&#34; but will also give rise to entirely new professions such as &#34;Product Manager-Engineer hybrids,&#34; &#34;AI Supply Chain Forecasters,&#34; and &#34;Computational Geneticists.&#34;
In summary, the sweep of new technology indeed brings about the growing pains of the old order. However, when the market blindly panics and mistakenly kills off many quality assets, returning to the essence of business—focusing on proprietary data, physical asset barriers, and long-term profitability—is the optimal solution to navigate through the technological cycle.
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"Wall Street" AI disruption panic triggered indiscriminate selling, but Morgan Stanley believes this is a significant pricing error. Sectors such as software and financial intermediaries, viewed by the market as "victims," have seen valuations drop to the 9th percentile since 2010, yet they are precisely the group with the highest AI adoption rates. Currently, over 30% of companies have realized AI dividends, and the compliance and heavy asset moats are difficult to breach, demonstrating resilience for long-term profitability

- Recent market sentiment reflects "AI anxiety" on Wall Street, leading to significant sell-offs in traditional service-oriented sectors, particularly software and finance.  
- Morgan Stanley's report suggests that the market's reaction to potential AI disruption is overblown, as affected companies now represent only 13% of the S&P 500's total market value and are undervalued historically.  
- The firm anticipates that AI adoption will boost profitability for these companies in the near future, countering fears of obsolescence as data shows a substantial financial impact from AI integration.

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After analyzing over ten thousand financial reports, Morgan Stanley found that the "services + cyclical" sector, which has been sold off, actually has the highest AI adoption rate and the strongest bargaining power