A comprehensive new research by Morgan Stanley suggests that Artificial Intelligence adoption may unleash savings of about $1 trillion annually, putting Corporate America on the verge of a fundamental shift. According to the bank, AI will automate or enhance 90% of occupations in some form, and cost reductions will come directly from lower headcount, natural attrition, and the automation of mundane yet knowledge-intensive operations.
According to the Wall Street Bank, the S&P 500 corporations might gain by $920 billion annually from the widespread use of embodied AI humanoid robotics and so-called agentic AI software. According to economists, the majority of those savings will come from reducing payroll costs and the need for human labor in jobs that need a lot of repetition or processing.
Roughly 28% of the index’s 2026 pretax earnings would be saved, which is a startling efficiency increase that analysts predict would have an impact on many businesses. More concerns are necessary since Morgan Stanley’s Thematic Investing team warns that these cost savings would “probably take many years to achieve” and that there is “significant risk” that certain businesses won’t reach full adoption levels. They note that the $920 billion amount is 41% of the whole compensation expenditure for the S&P 500, and they only have enough data to do analysis for around 90% of the S&P 500.
According to them, the “economic value creation” will be achieved through cost reduction (for example, reducing the number of employees and the expenses of using AI to perform a wide range of tasks) as well as the creation of new revenue and margins because employees will have more time to engage in higher-value activities that have the potential to boost profits and revenue. Depending on industry and occupation, they see a wide range of the balance between these two influences. According to the analysis, depending on valuation multiples, the $920 billion yearly economic gain may result in a $13 trillion to $16 trillion increase in the S&P 500’s market value. That sum would represent around 25% of the market capitalization as of right now.
Most vulnerable sectors
Not every industry will be affected in the same way. Distribution and retail of consumer staples, real estate management, and transportation are among of the industries most at risk. The potential productivity gains from AI might surpass 100% of projected 2026 earnings. There are significant opportunities and disruptions for professional services, automobiles, and health care equipment and services.
However, the potential value of AI is relatively smaller in areas like semiconductors and electronics that already have a labor-to-earnings ratio.
Jobs at risk, upcoming new jobs
Morgan Stanley emphasized the difference between complete automation and task-level augmentation, even if payroll reductions will result in the best financial results. In contrast to embodied AI, which takes the shape of humanoid robots, which presents greater direct replacement threats in sectors like logistics and physical retail, agentic AI, which includes generative AI and software applications, prefers to reassign duties rather than completely kill employment.
Alongside the displacement trend, the paper predicts the emergence of whole new job categories, such as chief AI officers and AI governance specialists. This is similar to previous waves of technological disruption that increased demand for programmers, IT specialists, and digital marketers.
A long ramp-up
The researchers warn that complete acceptance is likely to take years, if not decades, to occur, despite the headline number. Businesses will rely more on attrition and process optimization than on sudden mass layoffs, especially in industries where income is generated by customer-facing positions.
The key message for investors, however, is evident: AI is no longer a topic for speculation. In the second half of this decade, the potential cost reductions might be one of the most significant factors driving the increase of corporate profitability in the United States.
