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The Advancement of Artificial Intelligence Is Already Pressuring Elite Professions, Accelerating Cuts in Technology Firms and Redesigning Careers Linked to Analysis, Accounting, Law, and Finance, in a Movement That Market Managers Treat as Structural, Rapid, and Hard to Reverse in the Short Term.
Artificial intelligence has already begun to change typical office functions and, in the assessment of managers interviewed by the Stock Pickers Aftermarket program, the first deeper impact is likely to hit higher-paying occupations, such as legal, accounting, analytical, and financial fields.
This diagnosis was presented by Paulo Passoni from Valor Capital Group, in a conversation with Andrew Reider from WHG Long Biased, and Christian Keleti from Alpha Key, aired in March 2026.
Passoni summarized the change in two central ideas: the speed of tool evolution and the growing capacity to automate repetitive intellectual tasks.
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According to him, the inflection point is not only in what technology already executes but in the volume of activities it can absorb in a short time, while part of the market still treats the advancement as something experimental.
“No one has realized that the tools are improving at an absurdly fast speed,” said the investor.
Along the same lines, he stated that “every type of intellectual work will change,” especially functions focused on data retrieval, information consolidation, report generation, and reconstruction of past events.
AI in the Labor Market Is Already Targeting Intellectual Functions
In the analysis presented in the debate, vulnerability is not evenly distributed among professions.
Activities based on sector research, document screening, drafting standardized opinions, organizing databases, and initial analytical writing appear as the most immediate candidates for partial or broad replacement by available AI systems.
The logic presented by Passoni is straightforward: the more a job depends on processing existing information and returning it in a structured format, the lower the barrier for automation tends to be.
In this formulation, steps that require interpretation, foresight, strategic judgment, and genuine creativity retain relative value, even if they also come under pressure from productivity gains.
Instead of initially targeting lower-income occupations, as happened in other waves of mechanization, this new technological push may advance over careers that historically concentrated prestige, higher salaries, and extensive academic training.
It was in this context that the manager provocatively stated that areas once seen as “dream jobs” might now become some of the most exposed.
Automation in the Financial System Has Become a Sign of Structural Change
One of the examples cited in the conversation involves Jamie Dimon, CEO of JPMorgan Chase.
The executive reiterated that artificial intelligence should transform corporate routines and has stated, at various times, that technology could contribute to shorter workweeks in the future, as it increases productivity and reduces the burden of repetitive tasks.
In the debate, the reference to JPMorgan emerged as a symbol of a broader change: when a global financial institution begins to incorporate automation as a structural vector of efficiency, the effect is no longer merely experimental but takes on the contours of a permanent reorganization of qualified work.
The discussion thus extended beyond a new tool, but to the redesign of teams.
Although the direct reduction of work hours was not presented as an immediate policy for the entire bank, Dimon’s remarks were interpreted by participants as evidence that productivity calculations have already entered the center of business decisions.
In information-intensive sectors, this calculation usually comes with fewer hours, fewer people, or new function cuts.
Block and Job Cuts with Artificial Intelligence
The most concrete case cited in the program was that of Block, a payment company founded by Jack Dorsey and owner of brands like Square and Cash App.
In February 2026, the company announced it would cut more than 4,000 jobs, as part of a restructuring explicitly associated with a deeper incorporation of artificial intelligence.
The company described the measure as part of a structural review to embed AI in its operations, while Dorsey stated that “intelligent tools” have changed the meaning of building and managing a company.
That information caught attention because the move was not presented as a response to an immediate financial collapse.
Instead, coverage highlighted the combination of restructuring, commitment to efficiency, and positive market reaction, with a rise in shares in after-hours trading following the announcement.
This association reinforced the understanding that AI-related cuts have already left the abstract realm.
Why Lawyers, Accountants, and Analysts Are on the Radar
When Passoni mentions lawyers, accountants, and analysts, the focus is less on the complete extinction of these careers and more on the erosion of entire blocks of tasks that sustained these occupations.
This includes document review, compiling case law, accounting verification, sector research, producing preliminary materials, and other time-intensive and standardized routines.
In this framework, professionals remain relevant when they need to arbitrate ambiguities, negotiate, assume technical responsibility, make sensitive decisions, or formulate an original interpretation.
Nonetheless, the operational base that traditionally occupied junior analysts, support teams, and intermediate functions tends to shrink, pressuring the entry and progression in these careers.
The practical consequence is not only the risk of layoffs but a revision of what companies come to consider as scarce skills.
Instead of rewarding the volume of hours spent on information gathering and formatting, demand tends to shift towards oversight, validation, context, critical thinking, and the ability to use AI as a production tool.
Comparisons with Other Recent Economic Disruptions
Andrew Reider resorted to a historical parallel to frame the transformation.
According to him, while globalization shifted industrial jobs from wealthy countries to cheaper hubs starting in the 1990s, artificial intelligence now operates something similar with office workers by offering a “worker” that is cheap, continuous, and scalable.
“AI has a bunch of very cheap workers that work 24/7, do not complain, do not want a four-day week, and will replace accountants, lawyers, and bankers,” said the manager.
For him, the dimension of uncertainty opened by this turning point finds parallel only, in terms of potential impact, with shocks like the 2008 crisis and the pandemic.
The debate, thus, did not treat artificial intelligence as a peripheral technology topic but as a force capable of reordering costs, margins, careers, and hiring criteria in sectors traditionally associated with specialized knowledge.
The central point of the alert was precisely this: automation no longer threatens only low-income operational functions and has begun to compete in areas where there was previously a sense of institutional protection.
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