Paytm layoffs: What the AI-led job cuts mean for the company, startups and the economy

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One97 Communications, the parent firm of Paytm, fired over 1,000 employees due to the “more than expected” impact of artificial intelligence on its operations.

"We are transforming our operations with AI-powered automation to drive efficiency, eliminating repetitive tasks and roles to drive efficiency across growth and costs, resulting in a slight reduction in our workforce in operations and marketing,” a company spokesperson said, adding that Paytm expects to save 10-15% in employee costs.

The move has ramifications at three levels: for Paytm itself, for the startup ecosystem in particular and for the economy in general. Let’s look at all three.

Paytm and the way forward

Paytm listed on November 18, 2021, after completing a ₹18,300-crore IPO, the second-biggest IPO in India so far after the LIC IPO.

However, from an issue price of ₹2,150, its shared tanked more than 27% on the first day of listing, before eventually cratering out below ₹500 a year later. The development wrecked plans by a number of so-called “new age” companies that were planning to list.

As Paytm became the poster boy of the struggles of the startups, a handful of which have lasted over the past couple of years, analysts in particular started scrutinising the payments firm over lack of clarity on what it wants to become.

The firm, which started as a mobile recharge-cum-wallet company has lost ground in the UPI-led payment market (it has 13% share), where PhonePe (46%) and GPay (36%) are bigger players.

It has since ventured into other areas, such as loans, insurance broking as well as launched Paytm Money, an end-to-end mutual fund, stock broking and wealth management platforms.

It has really been loans where Paytm has seen most growth: its loan book grew from ₹1,400 crore in FY21 to ₹35,000 crore in FY23, and was slated to hit ₹70,000 crore in FY24.

Things appeared to be going good but suddenly, the RBI recently slammed the brakes on small-ticket loan lending after it asked firms to keep aside more money while issuing these loans. More than 70% of loans Paytm had disbursed was through its small-ticket, buy-now-pay-later product: Paytm Postpaid.

The Paytm share, which had more than doubled from its ₹465 low to a recent high of nearly ₹1,000, crashed to around ₹650 levels.

What the market wants from startups: quicker path to profitability

That the market has been fairly circumspect on the stock means Paytm increasingly finds itself under increased pressure to deliver: as loan growth will invariably slow down, Paytm now says it will ramp up focus on merchant solutions and its wealth management business.

CEO Vijay Shekhar Sharma has exuded confidence that a result of its renewed focus and because of its automation efforts, the company will be profitable sooner than expected, perhaps in as early as a year.

Its decision to cut workforce will likely help it get there quicker.

Several other startups, both listed and those that want to list, have made it clear that their key focus is to now become profitable.

For many, AI will be a godsend.

AI, startups and economy

Paytm is one of the first companies to openly say that its layoffs are a result of an increased adoption of AI, which saw an explosion in 2023 following the launch of ChatGPT.

But it’s no secret that nearly every modern company is implementing AI in various ways in an effort to improve productivity, reduce cost or both.

The jury is still out on whether AI will generate enough jobs to offset job losses. But should it fail to do so, there will be ramifications for startups, large companies, job seekers and the economy in general. These are:

  • By virtue of being nimbler, startups can implement AI solutions quicker, which may help them to grow faster or become profitable sooner. Large companies will have to increase their speed of adoption.
  • The job market will become more two-layered: low-skilled workers may struggle for opportunities while demand for higher-skilled workers will grow. This could lead to jobless growth and create a headache for policymakers.
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