OpenAI Appoints Raghav Gupta to Lead Education in India and APAC

Aug 26, 2025
OpenAI has appointed Raghav Gupta, former Coursera MD, to head its education division in India and the APAC region, as part of its expansion efforts.

OpenAI has appointed Raghav Gupta, the former Asia Pacific Managing Director at Coursera, to lead its education division for India and the Asia-Pacific (APAC) region. This strategic move is part of OpenAI's broader expansion efforts in India, where the company plans to establish its first office in Delhi.

The announcement was made during the OpenAI Education Summit in New Delhi, where Leah Belsky, OpenAI's Vice President and General Manager for Education, highlighted the company's commitment to enhancing AI education in the region. Gupta's role will involve working closely with local teams to drive the adoption and responsible use of OpenAI's products across key audiences.

In addition to Gupta's appointment, OpenAI has launched a Learning Accelerator program in partnership with the Ministry of Education and the All India Council for Technical Education (AICTE). The initiative aims to provide educators with access to OpenAI's latest model, ChatGPT 5.0, to train students and teachers across India. Furthermore, OpenAI has announced a $500,000 grant to IIT Madras to support research on AI's impact on education.

These developments underscore OpenAI's focus on India as a critical market for AI growth, with plans to further invest in the country's burgeoning AI ecosystem.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like AI in Education or Daily AI Brief.

Also, consider following us on social media:

Free newsletter

AI in Education

Weekly newsletter about AI in education. Covers AI-driven software for educators, schools, general innovations and regulatory updates.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.