Morgan Stanley has identified a critical inflection point in AI adoption, with businesses beginning to translate artificial intelligence investments into tangible bottom-line improvements. Katy Huberty, the firm’s Global Head of Research, revealed in a recent interview that companies with strong pricing power—the ability to maintain or increase prices due to high demand—will capture the most significant profit gains from AI implementation.
In a January 6 client note, Morgan Stanley’s research team compiled a list of 139 AI-adopting companies with robust pricing power, narrowing it down to 20 stocks with market capitalizations exceeding $20 billion. Huberty emphasized that this represents “the next step in a yearslong secular bull trend for the broadening AI trade” and identified pricing power as a key area for alpha generation in 2025.
The investment thesis centers on a crucial economic principle: companies with pricing power can retain the productivity gains from AI investments rather than passing savings to customers through lower prices. “What we’ve recommended to our clients is they should start thinking about pricing power,” Huberty explained. “Pricing power will allow the companies to retain the productivity that they experience on the back of these investments and not have to pass that on to the customer.”
The 20-stock list spans diverse sectors, demonstrating AI’s broad applicability across industries. The roster includes Home Depot (HD) leading with a $414.3 billion market cap, followed by healthcare giants Thermo Fisher Scientific (TMO) at $210.5 billion and Intuitive Surgical (ISRG) at $192 billion. Industrial powerhouse Deere & Co. (DE) commands a $120.5 billion valuation, while technology and e-commerce players like Spotify (SPOT) and MercadoLibre (MELI) represent the communication services and consumer discretionary sectors.
The hospitality sector features prominently with Marriott International (MAR) and Hilton Worldwide (HLT), while industrial companies including PACCAR (PCAR), Johnson Controls (JCI), and Axon Enterprise (AXON) demonstrate manufacturing and technology applications. Energy sector representatives include Schlumberger (SLB), Baker Hughes (BKR), and Halliburton (HAL). Airlines Delta (DAL) and United (UAL) round out the transportation sector, alongside e-commerce platform Coupang (CPNG), financial services firm Experian (EXPGF), healthcare diagnostics company IDEXX Laboratories (IDXX), and Chinese industrial automation specialist Shenzhen Inovance Technology.
This strategic framework suggests that 2025 marks a transition from AI infrastructure investment to operational deployment and profit realization, with pricing power serving as the critical differentiator for investor returns.
Key Quotes
What we’ve recommended to our clients is they should start thinking about pricing power. Pricing power will allow the companies to retain the productivity that they experience on the back of these investments and not have to pass that on to the customer.
Katy Huberty, Morgan Stanley’s Global Head of Research, articulated the firm’s core investment thesis connecting AI adoption to profit realization. This statement highlights why not all AI adopters will see equal benefits—only those with strong market positions can capture the full value of productivity improvements.
That’s one of the areas where alpha generation will come this year.
Huberty identified pricing power among AI adopters as a key source of outperformance for 2025, signaling a shift in where investors should look for returns as AI moves from hype to operational reality.
We’re at a ’tipping point’ when it comes to AI adoption. Businesses are starting to use the technology to boost their bottom lines — and they’re about to start reaping the benefits.
This statement from Huberty frames the current moment as an inflection point where AI transitions from experimental technology to profit-generating tool, suggesting imminent financial impacts for well-positioned companies.
Our Take
Morgan Stanley’s framework represents a maturation of AI investment thinking, moving from “picks and shovels” infrastructure plays to identifying second-order beneficiaries. The pricing power criterion is particularly astute—it recognizes that technology adoption alone doesn’t guarantee shareholder value if competitive dynamics force companies to share productivity gains with customers.
What’s striking is the sector composition: traditional economy stalwarts like Home Depot, Marriott, and Deere alongside tech-forward companies. This suggests AI’s impact will reshape competitive dynamics across industries, not just within technology. The inclusion of airlines and energy services companies—historically cyclical, capital-intensive businesses—indicates AI’s potential to transform operational efficiency in unexpected places.
The timing matters too. With 139 companies meeting Morgan Stanley’s criteria, we’re past early adoption and entering mainstream deployment. Investors should watch whether these companies actually demonstrate margin expansion in coming quarters—that will validate or challenge this thesis. The real test is whether AI productivity gains prove durable or get competed away faster than Morgan Stanley anticipates.
Why This Matters
This analysis represents a significant evolution in AI investment strategy, moving beyond pure-play technology companies to identify beneficiaries across traditional industries. Morgan Stanley’s framework acknowledges that we’ve entered a new phase where AI adoption translates into measurable business outcomes rather than speculative potential.
The emphasis on pricing power reveals a sophisticated understanding of how AI value accrues to shareholders. Companies that can retain productivity gains rather than competing them away through price reductions will see AI investments flow directly to profit margins. This creates a clear investment thesis distinct from earlier AI plays focused on infrastructure providers like chipmakers and cloud platforms.
The sector diversity in Morgan Stanley’s list—spanning retail, healthcare, hospitality, energy, and manufacturing—demonstrates AI’s maturation from a niche technology to an economy-wide productivity driver. This broadening suggests we’re witnessing the democratization of AI benefits beyond Big Tech, with implications for market leadership and sector rotation.
For businesses, this signals that competitive advantage will increasingly depend on both AI adoption speed and market positioning that enables value capture. Companies without pricing power may find themselves forced to pass AI-driven cost savings to customers, limiting shareholder returns despite successful technology implementation. This dynamic will likely accelerate industry consolidation and widen performance gaps between market leaders and followers.
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