OpenAI’s Codex app, launched in February 2026, has shown rapid early adoption among developers in India, according to a report from Tech-Economic Times. The report characterizes India as one of the fastest-growing AI builder ecosystems globally, while noting that adoption remains uneven across use cases.
Codex user growth after the February 2026 launch
According to Tech-Economic Times, India saw four times growth in “Codex users” in just two weeks after the Codex app launch in February 2026. This metric tracks usage of OpenAI’s AI coding tool. The rapid growth within a short timeframe suggests that packaging the tool into an accessible app format can drive quick adoption among developers.
The report also notes that India shows strong rankings in two areas: coding and data analysis usage. This indicates that the ecosystem’s activity extends across multiple technical functions, not limited to a single use case.
Understanding “Codex users” as a metric
“Codex users” is a product-specific metric that tracks people using OpenAI’s AI coding tool. For observers tracking developer platforms, this metric can serve as an indicator of adoption patterns for AI developer tooling. The four times increase within two weeks suggests that the app distribution and user onboarding were effective in driving rapid usage growth.
Coding assistants often integrate into daily developer workflows, which can contribute to sustained usage. The combination of rapid Codex user growth and strong rankings in coding usage indicates that the product is aligning with active developer workflows.
Uneven adoption: the other side of rapid growth
Despite the growth headline, the report’s framing—India among the world’s most advanced AI users but with uneven adoption—introduces an important nuance. Uneven adoption could reflect concentration in certain developer segments, variable usage across tool capabilities, or differences in how quickly teams integrate AI into production workflows. The source does not specify which dimension is uneven.
The juxtaposition of quick Codex user growth with uneven adoption suggests that rapid onboarding does not automatically translate into consistent, wide-scale usage. This pattern is common in technology transitions: initial experimentation can spread faster than standardized implementation, particularly when teams differ in tooling maturity and reliability requirements.
Coding and data analysis usage
The report ties India’s AI ecosystem strength to both coding and data analysis usage. This combination indicates two different categories of AI work: code generation and assistance, and data analysis tasks. While the source does not specify whether data analysis is driven by Codex or other AI tools, it indicates that India’s AI usage extends beyond programming alone.
AI adoption in an ecosystem can accelerate in one product area—such as coding via Codex—while other areas progress differently. The report’s emphasis on India as a “fast-growing AI builder ecosystem” establishes that the country’s developer community is actively engaging with AI tooling.
Implications for AI product rollout
The Codex app launch demonstrates how quickly an AI developer tool can scale when distributed in an accessible app format. The reported four times growth over two weeks supports the idea that distribution and usability can drive rapid adoption.
At the same time, the report’s “uneven adoption” framing suggests that product usage growth may not be uniform across all user groups or use cases. This could indicate that developers and platform providers may need to address factors beyond access, such as onboarding, integration into existing development processes, and ensuring that different categories of tasks receive comparable levels of support.
Source: Tech-Economic Times