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An online executive program from Technovation
and Saïd Business School, University of Oxford.
Caring about a problem is the starting point. For 20 years, Technovation has built what comes next. We bring the mentors and tools to build a solution, and the resources to launch it as a business.
Learn frameworks from Oxford faculty and meet the founders already applying them in Qatar, Singapore, the UAE, and Egypt. The finished product is an AI Opportunity proposal you can use to take your organization to the next level or use for your own entrepreneurial endeavor.
This course walks you through building a toolkit, testing it in four real-world sectors, and finally turning your work into a pitch.
Learn why AI helps some organizations excel while others stall, and what that shift means for the future of work. The Technology S-Curve explains how a technology grows slowly at first, then quickly, and why a newer technology eventually overtakes it. The LEVRA framework explains which human capabilities AI can't replace.
Maryam Khalid Alatteyah and Almaha Abdullah Al Sowaidi on using AI for dispatch while directly employing their technicians, because trust was the thing the model depended on.
Safety, regulation, evidence, and trust shape how AI gets built and used. This module explains how data network effects give an AI product a strategic advantage. It also shows how algorithmic bias can appear at each stage, from the patient data used to build a system to the outcomes patients receive. You'll finish with eight ethical principles for evaluating an AI system.
Professor Sally Collins on the move from clinician and researcher to entrepreneur.
Learn how AI is changing who can access financial services and who holds power in the industry. This module covers open banking, data network effects, and leapfrog innovation, where new services skip older banking infrastructure entirely. It also examines the question of who is liable when AI makes a financial error. You'll work through four liability scenarios covering credit approval, fraud detection, investment advice, and general-purpose tools.
Padmini Gupta on building financial services for migrant workers.
Learn why operational data volume and repeatable processes make manufacturing fertile ground for AI, and how small compounding improvements turn into competitive advantage. You investigate a real use case and stress-test your reasoning against an AI tool.
Akanksha Jagwani and Avni Agrawal on detecting defects in semiconductor manufacturing, and why user trust and workflow integration came before accuracy.
This module looks at high-stakes systems where AI shifts costs and benefits among workers, corporations, and the environment. You'll learn why these effects differ sharply by region, and where emerging economies can find a place in the AI supply chain.
Dr Ozge Islegen-Wojdyla on helping hotels, restaurants, and other high-consumption businesses cut energy waste.
AI does not develop evenly across the world. Infrastructure, data availability, regulation, investment, and public trust decide what is possible locally. You work through the tension between global inequality and local strength, then turn your completed workbook into a persuasive recorded pitch.
Time commitment. Self-paced. Core modules run roughly two to three hours each, plus orientation, workbook time, and the capstone.
Faculty. Taught alongside Professor Pinar Ozcan, Thomas Hellmann, Agni Orfanoudaki, and faculty and practitioners from Brazil, Indonesia, Türkiye, Egypt, and Singapore.
The program is for women, and open to three groups in the Technovation community.
You are a woman who mentored or judged with us this season or in any past season.
You went through a Technovation program as a student.
You are a Women Techmakers Member or Ambassador.
Mentor a Technovation team, become a Women Techmaker, or join our accelerator to qualify.
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in the United States
