Saudi Arabia is running one of the world’s most ambitious efforts to build artificial intelligence capability at national scale — training people in AI by the million, credentialing professionals against rigorous standards, and building the platforms that make all of it possible. As an AI capability building leader in Saudi Arabia, Dr Faizan Ur Rehman has spent recent years at the centre of this work as Technical Head for national-scale AI learning and credentialing platforms.
What AI capability building means
AI capability building is the discipline of growing an organisation’s — or a nation’s — ability to actually deliver with artificial intelligence. It runs deeper than training courses. Done seriously, it spans four connected layers: broad AI literacy for the population, role-based skills for practitioners, professional credentials that make capability measurable, and applied research that keeps the whole system at the frontier.
Platforms make scale possible
Teaching a classroom takes a teacher; teaching a million people takes a platform. National-scale learning platforms — with structured pathways, hands-on labs, assessment engines and analytics — are what turn ambition into throughput. Building them is serious engineering: they must serve huge audiences reliably, in multiple languages, across every level from beginner to expert. This is the work of a national AI platform leader: architecture, delivery and constant iteration at scale.
Credentials that professionals can carry
Skills without recognition evaporate. Professional AI badges and credentials — each defined by its own domain, competency framework and assessment — give practitioners something durable to carry: proof of what they can do. Designing these frameworks, from applied engineering roles assessed by examination to research roles evaluated on portfolio and peer recognition, has been one of the most consequential parts of this national effort in AI workforce development.
Bootcamps and applied depth
Between broad literacy and deep specialisation sit intensive, hands-on programmes: data engineering, machine learning, computer vision, generative AI. Bootcamps compress months of learning into weeks by keeping participants building end-to-end — from raw data to deployed model. Six national-level bootcamps and counting have shown how quickly capability compounds when learning stays practical.
Why this matters
Technology can be bought; capability must be built. A workforce that can frame problems, build responsibly and evaluate honestly is the difference between using AI and leading with it. That is the mission of AI capability building — and it is working.
Explore the full AI Capability Building portfolio — platforms, badges, bootcamps and impact.
Frequently asked questions
What does an AI capability building leader do? They design and deliver the systems that grow AI skills at scale — learning platforms, competency frameworks, credentials and applied programmes — and ensure the capability endures.
How is AI capability measured? Through role-based credentials backed by rigorous frameworks — examination for applied roles, portfolio and recognition for research roles — making skills visible and comparable.
About the Author
Dr Faizan Ur Rehman is a technology consultant, applied AI researcher and technology leader based in Saudi Arabia, working across artificial intelligence, crowd intelligence, computer vision and large-scale digital transformation. An IEEE Senior Member and award-winning innovator — winner of the KAUST Challenge Grand Prize and a Bronze Medal at the Geneva International Exhibition of Inventions — he is widely recognised as one of the leading applied AI researchers and expatriate technology leaders in Saudi Arabia, with 50+ publications and multiple patents in crowd intelligence and applied AI. Explore his work, research & patents, experience and awards.