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Reading: Morgan Stanley predicts AI will not allow you to retire early: As a substitute, you may have to coach for jobs that do not exist but | Fortune
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Asolica > Blog > Business > Morgan Stanley predicts AI will not allow you to retire early: As a substitute, you may have to coach for jobs that do not exist but | Fortune
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Morgan Stanley predicts AI will not allow you to retire early: As a substitute, you may have to coach for jobs that do not exist but | Fortune

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Last updated: February 26, 2026 9:26 am
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14 hours ago
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Morgan Stanley predicts AI will not allow you to retire early: As a substitute, you may have to coach for jobs that do not exist but | Fortune
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Tech titans and inventory market buyers are more and more unified of their forecast that synthetic intelligence will completely get rid of thousands and thousands of white-collar jobs and render conventional employment out of date.

Contents
  • The roles to come back?
  • However what if this time is completely different?

Software program and companies shares have taken a beating, with software program multiples pulling again by roughly 33% since late 2025 as buyers fret over AI’s potential to automate huge swaths of data work. Earlier this yr, Elon Musk predicted that AI and humanoid robots will make work utterly “optional” inside the subsequent 10 to twenty years, ushering in a post-scarcity financial system the place cash itself turns into irrelevant. He joins a rising refrain of tech executives issuing stark warnings about human obsolescence; OpenAI CEO Sam Altman just lately cautioned that superintelligence might quickly outperform even high company executives, whereas Microsoft AI chief Mustafa Suleyman and Anthropic CEO Dario Amodei have projected that sweeping white-collar automation might arrive in a single to 5 years. Economists stay skeptical of the timeline, noting that the apocalyptic narrative could also be as a lot a instrument to justify astronomical tech valuations as it’s an impending financial actuality.

However a brand new, cross-asset analysis report from Morgan Stanley gives a remarkably grounding message for anxious staff and jittery markets: most of you received’t be completely unemployed; you might be simply going to search out new jobs, many or most of which don’t exist but.

Addressing the widespread concern that AI will “replace millions of jobs and increase unemployment by an equivalent amount,” a big staff of Morgan Stanley analysts pointed on to historical past. Over the previous 150 years, sweeping technological shifts—from electrification and the tractor to the pc and the web—have essentially altered the labor pressure, however they “did not replace labor”.

When the spreadsheet was popularized within the Nineteen Eighties, for instance, it automated tedious monetary modeling and lowered the necessity for sure bookkeeping clerks. Nonetheless, it concurrently freed up analysts’ time to do extra advanced work and birthed completely new monetary professions. Equally, the agency argues, AI will merely change “job types, occupations, and needed skills”.

“While some roles may be automated, others will see enhancement through AI augmentation and other, entirely new roles will be created,” the report stated. Somewhat than a mass extinction occasion for the white-collar employee, in brief, the financial institution sees the company panorama is solely making ready for an evolution.

The roles to come back?

So, what is going to these new jobs appear to be? Morgan Stanley outlines a number of rising professions that it predicts will quickly turn into company staples. As AI turns into central to enterprise technique, firms are anticipated to rent executive-level “Chief AI Officers” to information expertise adoption throughout departments. There may even be a large surge in AI governance roles targeted on information compliance, coverage oversight, and data safety, notably in delicate sectors like healthcare.

The tech sector might see the rise of blended roles, such because the product manager-engineer hybrid. Empowered by pure language coding instruments, product managers will more and more interact in “vibe coding”—prototyping and iterating ideas themselves earlier than handing them off to engineers for deployment.

Extremely specialised roles might additionally emerge throughout varied industries. Within the client sector, “AI personalization strategists” and “AI supply chain analysts” will mix information science with buyer expertise. In industrials, we’ll see “predictive maintenance engineers” and “smart grid analysts,” whereas healthcare will demand “computational geneticists” and specialists devoted to AI diagnostic oversight.

For monetary markets, the present panic over AI disruption seems untimely, if not completely misplaced, within the financial institution’s view. Morgan Stanley notes that the companies and cyclical industries which have just lately seen outsized underperformance as a result of disruption fears make up solely about 13% of the S&P 500’s market cap.

Fortune beforehand reported on an analogous discovering from different Wall Road economists: the market seems to be speaking itself right into a panic that the basics don’t justify, a pattern probably exacerbated by the growing variety of retail buyers within the equities market. Apollo International Administration Chief Economist Torsten Slok warned on Wednesday that the “entire market [is] exposed to a big move,” reasoning that the share of S&P 500 names transferring greater than 10% in a single day has elevated, whereas choices exercise stays “extremely elevated, consistent with heavy retail speculation and leverage-like exposure.” This leaves the market construction “more fragile and more vulnerable to an abrupt, outsized move.”

However what if this time is completely different?

The Morgan Stanley report gives welcome reassurance — however it might be telling a comforting story that doesn’t match the technological and financial realities of 2026. Whereas it’s true that previous waves of automation created as many roles as they destroyed, AI might characterize a qualitatively completely different shift, concentrating on cognitive, inventive, and decision-making duties as soon as thought proof against automation.

In a brand new paper launched the identical day, two Nobel-winning economists (Daron Acemoglu and Simon Johnson) and one other, massively influential one (David Autor, recognized for his work on “the China Shock”) argued that this time actually could possibly be completely different. In “Building pro-worker artificial intelligence,” printed by The Hamilton Challenge, they warned that “pure automation technologies” do the alternative of collaborating with staff: “they commodify human expertise, rendering it less valuable and potentially superfluous.” The particular inventory of specialised, human experience might turn into “obsolete” with large deployment of such expertise.

Whereas the Morgan Stanley thesis displays historic optimism, historical past’s classes might not apply cleanly in a state of affairs with a shift from instruments that amplify labor to methods that change cognition. As warned within the speculative essay by Citrini Analysis, AI might produce productiveness positive aspects that decouple company earnings from employment much more than within the computing period. If corporations can scale output with largely automated workforces, they might have little incentive to rehire at historic charges.

Morgan Stanley cites proof that company America is already reaping tangible rewards from AI adoption. By the fourth quarter of 2025, 30% of firms recognized as AI “adopters” reported quantifiable monetary or productiveness advantages from the expertise, up from simply 16% a yr prior. Because of this, ahead revenue margin expectations are actively accelerating for firms efficiently using AI. How these margins proceed to extend, and what number of new jobs these firms create consequently, will bear out whether or not Morgan Stanley’s prediction is true.

For this story, Fortune journalists used generative AI as a analysis instrument. An editor verified the accuracy of the knowledge earlier than publishing.

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