What it actually takes to ship AI in MENA in 2026
A field-tested checklist from production AI work across Egypt and Saudi Arabia: data quality, regulatory pre-flight, bilingual evaluation, and rollout patterns that actually survive contact with users.
A field-tested checklist from production AI work across MENA in 2024–2025.
1. Most AI failures are data failures
The model isn't your bottleneck. The data labelling pipeline, the bilingual edge cases, the policy team's redaction rules — that's where 70% of the rollout time goes. Plan for it from week one, not week ten.
2. Regulatory pre-flight beats post-hoc fixes
SAMA, NCA, Egypt's PDPL — knowing the constraint before you architect saves rebuilding the audit log, the data residency, the consent flows. Get the compliance officer in the kick-off, not the launch.
3. Evaluate in both languages, on real users' phrasing
English benchmarks tell you nothing about how the model handles Egyptian or Saudi Arabic dialect. Build a bilingual eval set from real production traffic — anonymised — and run it on every model version before promotion.
4. Roll out behind a flag, then a percentage, then everyone
Production AI in regulated industries doesn't get a big-bang launch. Internal pilot → 5% rollout → 25% → 100%, each gated on a measurable success metric you defined in week one.
What this gets you
An AI feature that survives contact with users, an audit trail your compliance team can defend, and a team that knows how to ship the next one without external help.