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Morgan Stanley's deep dive on AI's rate of change By
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IntroductionIn a recent report, Morgan Stanley delved into the rapidly evolving landscape of AI's integration an ...
In a recent report,What does dealer mean? Morgan Stanley delved into the rapidly evolving landscape of AI's integration and its impact on various sectors. This comprehensive study, an update from their fourth-quarter 2023 survey, points to the shifts in AI exposure and materiality across a wide array of stocks, offering a detailed map of AI's rate of change.
According to its findings, 337 stocks, representing over $11 trillion in market value, have changed their AI exposure categories.

This includes shifts in exposure from categories like "Adopter" to "Enabler." For instance, Morgan Stanley notes that AI “is now more material to 97% of Utilities coverage," signaling a substantial integration of AI technologies in this sector. This represents a dramatic increase from previous levels, reflecting the growing role of AI in enhancing operational efficiency and addressing power bottlenecks.
The study also notes that AI's materiality to investment theses has increased significantly, with 446 stocks, worth $15 trillion, seeing changes in this regard. The increased importance is driven by AI's potential to deliver operational efficiencies, productivity gains, and innovative solutions across industries.
“AI is becoming more material for the investment case,” the firm wrote.
Morgan Stanley emphasizes that measuring AI’s rate of change is crucial for identifying incremental alpha opportunities. Their global mapping effort, even at this early stage of AI diffusion, aims to provide a clearer understanding of these opportunities.
The report identifies two primary strategies for generating AI alpha:
1) 'Enablers with Rising AI Materiality': Stocks re-categorized as having "Core to Thesis" exposure to AI have seen a rally of over 25% year-to-date. Morgan Stanley suggests that investors should continue focusing on these enablers, as they now show a 20% upside to Morgan Stanley's base case target prices, compared to a 14% upside for those merely "Core-to-Thesis."
On a sector basis, Utilities, which have already delivered 15% alpha YTD, are highlighted for their further upside potential.
2) 'Adopters with Strong Pricing Power': Companies classified as AI adopters with robust pricing power have outperformed those with lower pricing power by 24% since the release of ChatGPT. Morgan Stanley expects this trend to persist, with 135 stocks identified as meeting this criterion.
The report also details significant shifts in AI exposure and materiality by sector. Utilities, materials, and industrials have seen major changes, with a considerable number of companies reclassified as enablers or enabler/adopters. For example, the number of utilities tagged as enablers has increased from about 3% to over 30% in the past six months.
Morgan Stanley projects that AI-driven productivity gains will add approximately 30 basis points to the net margin by 2025.
“Our proprietary industry group framework focused on AI-driven efficiency gains corroborates this view as Software/Internet-related groups screen as top beneficiaries,” the report states.
“In terms of industry drivers of productivity gains, our framework highlights that services-oriented pockets of the market possess a more significant opportunity with respect to AI-driven efficiency gains,” it adds.
“These groups include Software Services, Consumer Services, Health Care Equipment & Services, Financial Services, and Media & Entertainment. Just these groups alone represent over 30% of expected 2025 net income for the S&P 500, which speaks to the potential margin opportunity.”
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