‘I might not have a job’: SEBI-registered analyst says AI may soon replace finance roles too
What changed his outlook was the rollout of finance-focused capabilities within Anthropic’s Claude model. Udupa refers to these as “Claude Plugins” tailored for investment banking and research workflows.
- Feb 26, 2026,
- Updated Feb 26, 2026 11:19 PM IST
The fear that artificial intelligence could upend white-collar careers is no longer confined to software developers. Over the past year, as generative AI tools such as ChatGPT and Claude have grown sharper and faster, anxiety has quietly seeped into corporate offices, business schools and even professions once considered stable and insulated from automation.
Now, a finance professional has publicly acknowledged that his own field may not be immune.
Shashank Udupa, a SEBI-registered research analyst and founder of Vayu Capital, sparked debate after posting an Instagram reel reflecting on how quickly the AI disruption narrative is shifting. In the video, he candidly admits that the threat he once associated primarily with IT roles may now be knocking at his own door.
“So last week I kept saying that IT jobs are in trouble, but this week I might not have a job,” he says.
What changed his outlook was the rollout of finance-focused capabilities within Anthropic’s Claude model. Udupa refers to these as “Claude Plugins” tailored for investment banking and research workflows. According to him, the tool can perform tasks that form the backbone of financial research in a fraction of the usual time.
He claims the system can read company financial statements, build a discounted cash flow (DCF) model and generate a complete equity research report in just five to seven minutes. By comparison, Udupa estimates it takes him 30 to 40 minutes to complete similar work, while junior analysts may need close to an hour.
“This is still day zero in finance,” he says, suggesting that what appears impressive today could represent only the starting point of a larger transformation.
Beyond speed and efficiency, Udupa’s deeper concern lies in what AI adoption could mean for young professionals entering the industry. India produces thousands of chartered accountants (CAs), chartered financial analysts (CFAs) and research aspirants each year, many of whom aim for roles in investment banking and equity research.
“If everyone becomes a very good research analyst through Claude then all the RAs in India, all the CFAs, all the CAs who are now coming in, trying to get into investment banking will have a problem,” he warns.
He adds that large financial institutions could customise such AI systems to fit internal workflows, potentially reducing the need for expansive junior analyst teams. Accounting and audit roles, he suggests, may also face mounting pressure as automation improves.
His comments quickly triggered a wave of anxious — and philosophical — responses online, reflecting broader unease about an AI-driven economy.
One user questioned the sustainability of mass automation: “If everyone will be out of job, who will be paying for these models, who will pay taxes to the government, who will buy stuff if they don't have money, how the economy will thrive? Are these robots going to start paying taxes? Nothing makes sense to me.”
Another raised concerns about reliability, referencing past controversies over AI-led auditing errors and warning that blind reliance on automated systems could carry legal and financial risks.
A third commenter offered a more adaptive view: “From here on, everyone becomes an orchestrator. More abstract from here onwards. Maybe a reshuffle is bound to happen, but we’ll find an equilibrium.” The suggestion reflects a growing belief that while entry-level roles may shrink, new supervisory and strategic positions could emerge around managing AI systems.
Yet skepticism persists. “If everyone would be out of jobs slowly, then who would buy stocks or mutual funds?” another user asked. “If no one buys that, what would these financial models and plugins be used for?”
The debate underscores a broader inflection point for the finance industry. For decades, automation in banking focused on trading algorithms and back-office efficiency. Generative AI, however, targets cognitive tasks once thought uniquely human — analysis, modelling and report writing.
Whether AI ultimately replaces junior analysts or simply reshapes their responsibilities remains uncertain. But as tools like Claude move deeper into specialised domains, professionals across sectors are confronting a new reality: disruption is no longer theoretical — it is arriving at their desks.
The fear that artificial intelligence could upend white-collar careers is no longer confined to software developers. Over the past year, as generative AI tools such as ChatGPT and Claude have grown sharper and faster, anxiety has quietly seeped into corporate offices, business schools and even professions once considered stable and insulated from automation.
Now, a finance professional has publicly acknowledged that his own field may not be immune.
Shashank Udupa, a SEBI-registered research analyst and founder of Vayu Capital, sparked debate after posting an Instagram reel reflecting on how quickly the AI disruption narrative is shifting. In the video, he candidly admits that the threat he once associated primarily with IT roles may now be knocking at his own door.
“So last week I kept saying that IT jobs are in trouble, but this week I might not have a job,” he says.
What changed his outlook was the rollout of finance-focused capabilities within Anthropic’s Claude model. Udupa refers to these as “Claude Plugins” tailored for investment banking and research workflows. According to him, the tool can perform tasks that form the backbone of financial research in a fraction of the usual time.
He claims the system can read company financial statements, build a discounted cash flow (DCF) model and generate a complete equity research report in just five to seven minutes. By comparison, Udupa estimates it takes him 30 to 40 minutes to complete similar work, while junior analysts may need close to an hour.
“This is still day zero in finance,” he says, suggesting that what appears impressive today could represent only the starting point of a larger transformation.
Beyond speed and efficiency, Udupa’s deeper concern lies in what AI adoption could mean for young professionals entering the industry. India produces thousands of chartered accountants (CAs), chartered financial analysts (CFAs) and research aspirants each year, many of whom aim for roles in investment banking and equity research.
“If everyone becomes a very good research analyst through Claude then all the RAs in India, all the CFAs, all the CAs who are now coming in, trying to get into investment banking will have a problem,” he warns.
He adds that large financial institutions could customise such AI systems to fit internal workflows, potentially reducing the need for expansive junior analyst teams. Accounting and audit roles, he suggests, may also face mounting pressure as automation improves.
His comments quickly triggered a wave of anxious — and philosophical — responses online, reflecting broader unease about an AI-driven economy.
One user questioned the sustainability of mass automation: “If everyone will be out of job, who will be paying for these models, who will pay taxes to the government, who will buy stuff if they don't have money, how the economy will thrive? Are these robots going to start paying taxes? Nothing makes sense to me.”
Another raised concerns about reliability, referencing past controversies over AI-led auditing errors and warning that blind reliance on automated systems could carry legal and financial risks.
A third commenter offered a more adaptive view: “From here on, everyone becomes an orchestrator. More abstract from here onwards. Maybe a reshuffle is bound to happen, but we’ll find an equilibrium.” The suggestion reflects a growing belief that while entry-level roles may shrink, new supervisory and strategic positions could emerge around managing AI systems.
Yet skepticism persists. “If everyone would be out of jobs slowly, then who would buy stocks or mutual funds?” another user asked. “If no one buys that, what would these financial models and plugins be used for?”
The debate underscores a broader inflection point for the finance industry. For decades, automation in banking focused on trading algorithms and back-office efficiency. Generative AI, however, targets cognitive tasks once thought uniquely human — analysis, modelling and report writing.
Whether AI ultimately replaces junior analysts or simply reshapes their responsibilities remains uncertain. But as tools like Claude move deeper into specialised domains, professionals across sectors are confronting a new reality: disruption is no longer theoretical — it is arriving at their desks.