Citrini Research last month released an article framed as a report written from the future, dated June 30, 2028. It envisioned a world in which artificial intelligence takes over jobs and disrupts the global economy, eventually triggering a sharp market crash in November 2027 that sends stock markets tumbling.
Damodaran, Professor of Finance at the Stern School of Business at New York University, examined several scenarios from the report using his “3P test”, a framework he uses to assess the probability and plausibility of narratives in valuation.
He began with two scenarios that he described as possible but not very plausible. “The first is a speedy, massive AI disruption, where AI displaces workers across most businesses, and does so quickly, as visualised by Citrini. It can happen, but given the history of disruption, the limits of AI technology and inertia in the process, it is implausible,” he wrote.
At the other extreme, Damodaran said it is also possible that AI simply provides tools that marginally improve productivity, with many ending up as distractions rather than transformational technologies. However, he believes this scenario is equally unlikely given the rapidly improving capabilities of AI tools.
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Instead, he views the most plausible outcome as one where AI disrupts certain industries — such as software and parts of financial services — while acting as a productivity tool in others.
“As for probable, I think that disruption will reduce workforces in a subset of businesses, that its tools will include some game changers and that it will take longer to unfold, at least when it comes to monetisation, than its advocates think,” he added.
Why will AI disruption take time?
Justifying why he feels AI disruption will take time, Damodaran listed out a mix of factors. AI products sometimes work magically well and quickly, but have some drawbacks. They are unable to “separate good data from bad, and partly from their imperfect attempt to imitate humans”.
History was the second factor cited by the valuation expert – no disruption has ever unfolded without delays and drawbacks, he noted. “The third is human nature, where much as employees and managers claim to want to move on to new and better options, they remain attached to old technology and products; typewriters and mimeographs took a while to disappear after PCs stormed the workplace, and flip phones persisted well into the smartphone era,” he added.
AI disruption to be significant in the long term
However, Damodaran still thinks AI disruption is going to be significant in the long term, citing two reasons for it. Those arguing that AI will not displace jobs in the long term are assuming that AI in its more advanced form will look like “ChatGPT on steroids” or be primarily mechanical in its applications, he said, adding that AI’s advanced tools suggest that they have far greater capabilities, and their capacity to mimic human intuition and thought processes is unsettling.
“The second is the blanket assumption that workers in most white-collar jobs will not be easily replaced because they bring training, brainpower and experience into those jobs that will be difficult to replicate. Many white-collar workers are bright people with specialised knowledge, but the businesses that hire them put them in straitjackets, pushing mechanics over intuition and rule-driven thinking over principle-driven assessments. In short, it is the nature of the jobs that we have created in many white-collar settings that makes them vulnerable to disruption, not the intelligence or training of the people holding those jobs,” he said.
Damodaran highlighted that in his probable scenario, AI will unfold at different rates in different businesses. According to him, the most and soonest targeted businesses will include young companies with younger employees with high gross margins and profitability and no or weak system protections from regulators. The least exposed businesses will include older companies with aging workforces, lower gross margins and profitability buffers and strong system dependence and protection from rule-writers and regulators.
Why has software become one of the first targets of AI disruption?
Software is a relatively young industry. It is a profitable business, and its products and services are logical and rule-based, and much of it has no regulatory or system protection. These factors made it one of the first victims of AI disruption, according to Damodaran.
“Within software, though, I would expect software that requires more user interface to be more resilient to AI disruption than software that operates in the background. This table, though, can help determine which white-collar jobs will be most exposed to AI disruption, and which least, and perhaps also explain why blanket statements about job displacement in banking, consulting and law are overwrought. With banking and law, a substantial portion of the work done is to meet legal or regulatory requirements, not fill operating needs,” he added.
Citrini’s research report had sent shockwaves across markets, which were already questioning AI’s possible impact after Anthropic’s launch of new AI tools. In the report’s hypothetical situation in 2028, the rupee fell 18% against the dollar in four months as the services surplus that had anchored India’s external accounts “evaporated”.
“The country’s IT services sector exported over $200 billion annually, the single largest contributor to India’s current account surplus and the offset that financed its persistent goods trade deficit. The entire model was built on one value proposition: Indian developers cost a fraction of their American counterparts. But the marginal cost of an AI coding agent had collapsed to, essentially, the cost of electricity. TCS, Infosys and Wipro saw contract cancellations accelerate through 2027,” it said.
(Disclaimer: Recommendations, suggestions, views and opinions given by the experts are their own. These do not represent the views of The Economic Times)