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Emeritus · AI portfolio

Turning experimental programs into a scaled AI learning portfolio.

A portfolio-building mandate across Generative AI, Machine Learning, Agentic AI, and RAG: identify the right market signals, turn them into credible learning products, and create an operating rhythm that could compound.

12programs built and scaled
$2M → $8Mportfolio run-rate
~1 yearoperating window

The opportunity

AI demand was moving quickly from broad curiosity toward specific capabilities. The portfolio needed sharper market positioning, program packaging, and a practical operating model for launch and iteration.

What I owned

Portfolio strategy, program proposition, go-to-market planning, launch execution, growth iteration, and cross-functional alignment across product, content, engineering, academic operations, and sales.

How the portfolio was built

The work combined zero-to-one launches, turnarounds of existing programs, advanced portfolio expansion, and selected global rollouts. The visible program mix includes GenAI, ML, Agentic AI, and RAG.

Outcome

The portfolio grew from approximately $2M to $8M in run-rate. The key result was not only more programs, but a repeatable way to translate an emerging AI topic into a viable learning-business proposition.

Global partner portfolio

GTM and growth work with international university partners.

MIT xPROMIT xPRO portfolioGlobal portfolio GTM and growthUC Berkeley Executive EducationUC Berkeley portfolioGlobal portfolio GTM and growthImperial Executive EducationImperial College portfolioGlobal portfolio GTM and growth

Program portfolio

AI learning programs launched, scaled, and optimised for the India market.

Named programmes and portfolio groups from a broader 12-program AI learning portfolio developed with university partners in India and abroad.