SKN | Morgan Stanley Identifies Five Companies Positioned to Benefit From AI-Driven Productivity Gains

Key Takeaways:

• Morgan Stanley’s September 2026 research shifts attention beyond AI infrastructure providers toward businesses capable of translating artificial intelligence into measurable productivity improvements.
• The bank’s AI Productivity Spread measures revenue-per-technical-employee growth against increases in average technical employee compensation, helping identify companies potentially extracting greater value from AI adoption.
• Five companies highlighted through the strategy are Waste Connections, Symbotic, Axon Enterprise, ASML and Aurora Innovation, representing different ways AI and automation could influence business efficiency and profitability.

Morgan Stanley is expanding its investment research into a less obvious segment of the artificial intelligence opportunity: companies that use AI to transform their operations rather than simply supply the technology. In its September 2026 report, AI Beneficiaries: Investing in Second-Order Effects – Update: 100x AI Cultures, the bank argued that businesses integrating AI more effectively into their workflows could capture substantial economic benefits as automation spreads across industries.

Morgan Stanley Develops a Framework to Identify AI Productivity Leaders

The bank’s research challenges the assumption that the largest beneficiaries of technological revolutions are necessarily the companies manufacturing the underlying technology. Drawing on historical examples involving automobiles and Wi-Fi, Morgan Stanley argues that the broader economic transformation created by new technologies can generate opportunities beyond their original suppliers.

To identify potential beneficiaries, Morgan Stanley developed its AI Productivity Spread indicator. It measures the difference between growth in revenue per technical employee and growth in average technical employee compensation. A positive and widening spread suggests that a company is generating greater business output relative to its employee compensation costs.

The research analyzed approximately 750 publicly traded technology companies and 40 million employee records. Morgan Stanley found that companies with higher AI Productivity Spreads subsequently delivered stronger stock returns relative to peers. The framework provides an analytical approach to evaluating how effectively organizations translate technological adoption into measurable productivity.

Five Companies Illustrate the Bank’s Second-Order AI Strategy

Insider Monkey identified five companies included in Morgan Stanley’s Tailwinds Strategy as of June 30, 2026. Their selection illustrates the breadth of the bank’s approach:

Waste Connections (NYSE: WCN) represents the potential for automation to improve waste sorting, recycling efficiency and operating economics. Morgan Stanley’s thesis centers on using technology to strengthen productivity within an established, infrastructure-intensive business.

Symbotic (NASDAQ: SYM) develops AI-powered warehouse robotics. Its automation systems could improve inventory movement, distribution efficiency and labor productivity, including through deployments across Walmart’s distribution network.

Axon Enterprise (NASDAQ: AXON) combines public safety hardware, cloud software and AI-enabled workflows. Its established relationships with law enforcement agencies and integrated technology ecosystem could support wider adoption of automated administrative and analytical processes.

ASML (NASDAQ: ASML) occupies a different position in the AI ecosystem through its advanced semiconductor lithography equipment. Its inclusion connects the productivity theme with the specialized infrastructure required to manufacture increasingly sophisticated chips.

Aurora Innovation (NASDAQ: AUR) focuses on autonomous trucking. Its technology could improve fleet utilization by allowing commercial vehicles to operate for longer periods, potentially reducing transportation costs and increasing the productivity of existing assets.

Automation Could Create a Broader Corporate Profitability Shift

Morgan Stanley’s analysis extends beyond technology companies. The bank estimates that automating half of the positions classified as having a high probability of automation across the 1,000 largest publicly traded companies could eliminate approximately 1.7 million jobs and reduce labor costs by $207 billion.

After accounting for how these savings may be distributed among shareholders, employees, customers and suppliers, the companies could retain approximately $87 billion in additional profits. This distinction is important: automation does not automatically translate into shareholder gains, since the economic benefits may be shared across multiple stakeholders.

Execution Determines Who Captures the AI Dividend

Morgan Stanley’s research provides a framework for assessing AI adoption through operational performance rather than technology exposure alone. The five companies illustrate different applications, but each faces distinct execution, financing, competitive and regulatory considerations. For global investors, the central question is whether productivity improvements can become durable earnings growth. As AI adoption broadens, the ability to convert efficiency gains into sustainable profitability may become an increasingly important measure of corporate competitiveness.

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