Nour Al Hassan on Building Arabic AI from MENA, Why Most Pilots Fail, and Hiring Only A Players

Nour Al Hassan is the Founder and CEO of Tarjama& and Arabic.AI, a UAE-based AI company building Arabic-first language models, enterprise agents, and document intelligence systems for governments and large organisations.

Before Arabic AI, Nour spent more than 16 years building Tarjama& from a bootstrapped translation business into a profitable, technology-led platform serving global enterprises. That long runway of proprietary Arabic data became the foundation for the creation of Arabic AI, enabling a leap into small language models, agentic workflows, and on-prem deployments for highly regulated customers.

She joins the podcast to discuss what it takes to build technology from the region, overcoming internal doubt, why Arabic remains fundamentally underserved in AI, how human-in-the-loop systems will evolve rather than disappear, and why AI adoption fails unless it is driven top-down by leadership rather than delegated to teams.

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Timestamps:

00:00 Introduction
05:09 Learning grit from watching her father build businesses
07:30 Managing energy, self-doubt, and discipline as a founder
10:45 The Arabic translation gap and serving 420 million speakers
18:20 Lessons from buying companies and scaling across MENA
26:30 "We have an elephant in the room we cannot ignore"
35:15 Why global companies treat Arabic as secondary
42:00 Is AI a bubble? Correction vs. collapse, and the Amazon analogy
48:08 Why enterprise AI must be CEO-led and the problem with "POC purgatory"
51:00 The crucial importance of hiring A-players

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