How Careem used technology and vision to become one of the region’s leading movers of people, goods, and money.

A massive, multiyear initiative to transform corporate data at Caterpillar demonstrates what top executives must do to unlock the power of their data assets.

Organizations that resist the push to trade entry-level workers for AI may end up better off in the long term.

The push for control, flexibility, and sovereignty is redefining cloud strategy.

As enterprises turn to algorithmically generated data to sustain AI development, a second-order problem is emerging — one that threatens model accuracy, regulatory compliance, and strategic differentiation.

Dr. Hakim Hacid, Chief Researcher at TII’s AI and Digital Science Research Center, argues that AI’s future will be defined not by model size alone, but by cultural authenticity, accessibility, openness, and real-world value.

Some decisions are narrow and can be modeled; others are wide and require stakeholder alignment. Understand this distinction to use the type of AI that will be most helpful.

When everyone has access to the same idea-generation engine, your remaining edge is the insight that tells you where to point your business. GenAI can surface data and patterns that help you see it.

Systems built into ministries, regulators, banks, and national platforms are quietly shaping results without ever being part of the user experience.

The people who get the best results from AI aren’t the most technical: They’re the most disciplined. Apply this self-audit tool to keep improving your GenAI sessions.