In a move that has captured investor attention, social commerce giant Meesho has detailed plans in its draft IPO papers to earmark a substantial Rs 480 crore from the offer proceeds specifically for paying the salaries of its artificial intelligence (AI), machine learning (ML), and technology teams. This allocation stands out as one of the largest single personnel expense provisions in recent Indian tech listings.
A Deep Dive into Meesho's IPO Allocation Strategy
The proposed salary outlay is part of a broader, aggressive investment plan into technology and growth. According to the filing, Meesho intends to channel Rs 1,390 crore into cloud infrastructure via its subsidiary MTPL and another Rs 1,020 crore into marketing and brand building. Combined, these three buckets present a sharply focused technology-and-growth expenditure profile, distinguishing Meesho among upcoming platform IPOs.
The company's rationale is rooted in its conviction that the next wave of e-commerce growth in India will be disproportionately driven by data science, automation, and personalised discovery. Meesho operates a massive, data-intensive marketplace, handling nearly 1.8 billion annual orders from over 214 million transacting users and a seller base exceeding 575,000. Its "everyday low prices" model is critically dependent on algorithmic pricing, fraud detection, demand forecasting, and logistics optimisation at scale.
Investor Scrutiny and the Rationale Behind the Salary Spend
However, using IPO funds to cover salaries typically draws investor scrutiny. The conventional preference is for fresh capital to be deployed towards hard assets, product expansion, or customer acquisition, especially for a company yet to achieve consistent profitability. Meesho's financials show rising revenues—from Rs 5,730 crore in FY23 to Rs 9,390 crore in FY25—but it remains loss-making on a consolidated basis, with losses widening in Q1 FY26 due to one-time restructuring and ESOP charges.
Analysts suggest understanding Meesho's business model is key to justifying this approach. The company has built a self-reinforcing operational flywheel where product discovery, content, pricing, and delivery all rely on high-velocity machine-learning systems. The filing explicitly states that “retaining and expanding its AI and engineering teams becomes a non-negotiable part of sustaining growth.” The salary allocation is meant for compensating existing team members, replacements, and new hires in ML, AI, and platform engineering.
For a low-margin, high-frequency marketplace like Meesho, even marginal efficiency gains in fulfilment, cloud optimisation, or delivery routing can significantly improve unit economics, making tech talent a direct lever for profitability.
Global Precedents and Meesho's Long-Term Vision
This strategy finds alignment with global platform giants like Amazon, Alibaba, Pinduoduo, and MercadoLibre, which heavily invested in engineering talent during their pre-profit phases, treating technology payroll as long-term capital expenditure to build defensible competitive moats. Meesho's filing appears to follow this playbook, particularly as it aims to consolidate the underpenetrated value e-commerce segment in India.
The company points to improving operating metrics—such as rising order frequency, stronger Net Merchandise Value (NMV) growth, and achieving positive free cash flow in FY24 and FY25—as signs of a stabilising business model. Management's broader thesis is that India's value-conscious shopper base is expanding, e-commerce penetration in non-electronics categories remains low, and the opportunity for a dominant low-AOV (Average Order Value) platform is still vast.
In this context, Meesho argues that investing heavily in technology talent is not an optional expense but a structural necessity to secure its future in the competitive Indian e-commerce landscape.
