But a new, cross-asset research report from Morgan Stanley<\/a> offers a remarkably grounding message for anxious employees and jittery markets: most of you won\u2019t be permanently unemployed; you are just going to find new jobs, many or most of which don\u2019t exist yet.<\/p>\n Addressing the widespread concern that AI will \u201creplace millions of jobs and increase unemployment by an equivalent amount,\u201d a large team of Morgan Stanley analysts pointed directly to history. Over the past 150 years, sweeping technological shifts\u2014from electrification and the tractor to the computer and the internet\u2014have fundamentally altered the labor force, but they \u201cdid not replace labor\u201d.<\/p>\n When the spreadsheet was popularized in the 1980s, for example, it automated tedious financial modeling and reduced the need for certain bookkeeping clerks. However, it simultaneously freed up analysts\u2019 time to do more complex work and birthed entirely new financial professions. Similarly, the firm argues, AI will merely change \u201cjob types, occupations, and needed skills\u201d.<\/p>\n \u201cWhile some roles may be automated, others will see enhancement through AI augmentation and other, entirely new roles will be created,\u201d the report said. Rather than a mass extinction event for the white-collar worker, in short, the bank sees the corporate landscape is simply preparing for an evolution.<\/p>\n So, what will these new jobs look like? Morgan Stanley outlines several emerging professions that it predicts will soon become corporate staples. As AI becomes central to business strategy, companies are expected to hire executive-level \u201cChief AI Officers\u201d to guide technology adoption across departments. There will also be a massive surge in AI governance roles focused on data compliance, policy oversight, and information security, particularly in sensitive sectors like healthcare.<\/p>\n Story Continues <\/p>\n The tech sector could see the rise of blended roles, such as the product manager-engineer hybrid. Empowered by natural language coding tools, product managers will increasingly engage in \u201cvibe coding\u201d\u2014prototyping and iterating concepts themselves before handing them off to engineers for deployment.<\/p>\n Highly specialized roles could also emerge across various industries. In the consumer sector, \u201cAI personalization strategists\u201d and \u201cAI supply chain analysts\u201d will blend data science with customer experience. In industrials, we will see \u201cpredictive maintenance engineers\u201d and \u201csmart grid analysts,\u201d while healthcare will demand \u201ccomputational geneticists\u201d and specialists dedicated to AI diagnostic oversight.<\/p>\n For financial markets, the current panic over AI disruption appears premature, if not entirely misplaced, in the bank\u2019s view. Morgan Stanley notes that the services and cyclical industries that have recently seen outsized underperformance due to disruption fears make up only about 13% of the S&P 500\u2019s market cap.<\/p>\n Fortune previously reported<\/a> on a similar finding from other Wall Street economists: the market appears to be talking itself into a panic that the fundamentals don\u2019t justify, a trend likely exacerbated by the increasing number of retail investors in the equities market. Apollo Global Management Chief Economist Torsten Slok warned<\/a> on Wednesday that the \u201centire market [is] exposed to a big move,\u201d reasoning that the share of S&P 500 names moving more than 10% in a single day has increased, while options activity remains \u201cextremely elevated, consistent with heavy retail speculation and leverage-like exposure.\u201d This leaves the market structure \u201cmore fragile and more vulnerable to an abrupt, outsized move.\u201d<\/p>\n The Morgan Stanley report offers welcome reassurance \u2014 but it may be telling a comforting story that doesn\u2019t fit the technological and economic realities of 2026. While it\u2019s true that past waves of automation created as many jobs as they destroyed, AI may represent a qualitatively different shift, targeting cognitive, creative, and decision-making tasks once thought immune to automation.<\/p>\n In a new paper released the same day, two Nobel-winning economists (Daron Acemoglu and Simon Johnson) and another, massively influential one (David Autor, known for his work on \u201cthe China Shock\u201d) argued that this time really could be different. In \u201cBuilding pro-worker artificial intelligence,\u201d published by The Hamilton Project, they warned that \u201cpure automation technologies\u201d do the opposite of collaborating with workers: \u201cthey commodify human expertise, rendering it less valuable and potentially superfluous.\u201d The specific stock of specialized, human expertise could become \u201cobsolete\u201d with wide deployment of such technology.<\/p>\n While the Morgan Stanley thesis reflects historical optimism, history\u2019s lessons may not apply cleanly in a situation with a shift from tools that amplify labor to systems that replace cognition. As warned in the speculative essay by Citrini Research<\/a>, AI could produce productivity gains that decouple corporate profits from employment even more than in the computing era. If firms can scale output with largely automated workforces, they would have little incentive to rehire at historic rates.<\/p>\n Morgan Stanley cites evidence that corporate America is already reaping tangible rewards from AI adoption. By the fourth quarter of 2025, 30% of companies identified as AI \u201cadopters\u201d reported quantifiable financial or productivity benefits from the technology, up from just 16% a year prior. As a result, forward profit margin expectations are actively accelerating for companies successfully utilizing AI. How those margins continue to increase, and how many new jobs those companies create as a result, will bear out whether Morgan Stanley\u2019s prediction is right.<\/p>\n For this story,\u00a0Fortune\u00a0journalists used generative AI as a research tool. An editor verified the accuracy of the information before publishing.<\/p>\n <\/p>\n