On Friday, September 12, 2025, Infosys remained in focus after the company secured exemptive relief from the U.S. Securities and Exchange Commission (SEC) for its proposed share buyback worth up to ₹18,000 crore. The programme, subject to shareholder approval via postal ballot, will be executed through the tender offer route at a price of ₹1,800 per share, representing a 19% premium over the current market price. The buyback will cover approximately 2.41% of the company’s equity.
The move marks Infosys’ fifth share buyback in eight years, continuing a consistent capital return strategy to shareholders.
Infosys buyback history
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2017: Infosys launched a ₹13,000 crore buyback at ₹1,150 per share, a 23% premium over the prevailing market price. This was carried out through the tender offer route.
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2019: The company executed an ₹8,260 crore buyback at ₹747.38 per share, offering an 18% premium. This was conducted via the open market route.
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2021: Infosys announced a ₹9,200 crore buyback at ₹1,648.53 per share, a 25% premium over CMP, again via the open market route.
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2022: A ₹9,300 crore buyback followed at ₹1,850 per share, offering a 30.3% premium, covering about 1.19% of capital. This too was via the open market route.
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2025: The current buyback, worth ₹18,000 crore at ₹1,800 per share, represents a 19% premium over CMP and will be conducted via the tender offer route, covering ~2.41% of equity.
Brokerages have largely welcomed the announcement. CLSA, Nomura, and Kotak Institutional Equities retained their positive stance, highlighting near-term support from the buyback alongside stable demand drivers and generative AI investments. Nomura pegged the stock’s upside potential at 24% with a target price of ₹1,880, while Morgan Stanley remained more cautious with an equal-weight call at ₹1,700.
The latest buyback underscores Infosys’ strategy of combining shareholder payouts with investment in growth drivers. With this move, the company continues to balance capital return with long-term investments in digital transformation, cost optimisation, and emerging areas such as generative AI.
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