Building an AI strategy: where GCC organisations should start
Many organisations want to adopt AI but don't know where to begin. A practical starting point for private companies and government entities alike.
Key takeaways
- Start with business problems and goals, not tools or vendors.
- Assess readiness across data, skills and governance before scaling.
- Leadership must own AI strategy. It cannot sit with IT alone.
Organisations across the GCC want to benefit from AI. The pressure comes from boards, from competitors and from national agendas such as the UAE’s National Strategy for Artificial Intelligence 2031 and the data and AI ambitions within Saudi Vision 2030. The UAE was also one of the first countries to appoint a minister dedicated to AI, in 2017.
Yet many organisations are unsure where to begin. Should they buy tools, hire data scientists, or automate a process? The answer is to treat AI as a strategic capability rather than a technology purchase.
Our AI strategy canvas
We help leadership teams start with a simple canvas built on our Define, Design, Deploy method. It covers three questions before any tool is chosen.
AI readiness: where are we today?
Assess data quality and access, digital maturity, skills, governance and culture. Without usable data and clear ownership, AI projects stall.
Goals: what should AI help us achieve?
Agree the business and service outcomes AI should support: faster service, better decisions, lower cost, new revenue or improved risk management. Link them to strategy and, for government entities, to national priorities.
Use cases: where will we start?
List candidate use cases and rank them by value, feasibility and risk. Choose a small number of pilots with clear owners and success measures.
Five principles for a strong AI strategy
- Define the problem, not the tool. Start with pain points and opportunities.
- Build governance early. Set policies for data privacy, bias, transparency and accountability before deployment.
- Start small and iterate. Pilot in one process, learn, then scale.
- Develop internal literacy. Leaders and teams need to understand AI well enough to own it and challenge vendors. See AI literacy for leaders.
- Measure and optimise. Track results, user adoption and risk, and refine continuously.
Additional priorities for the public sector
Government entities carry extra responsibilities: public trust, fairness and accountability for decisions that affect citizens. Their AI strategies should add:
- explicit alignment with national AI strategies and digital government plans
- transparency about where AI is used in public services
- strong data protection and security protocols
- capability building so employees can co-design solutions with vendors
From canvas to roadmap
Once leadership agrees readiness, goals and priority use cases, the next step is a phased roadmap: pilots, governance, skills development and scale-up, each with owners and measures. That turns AI from a series of experiments into a managed portfolio.
AI strategy is not about doing more with technology. It is about making better decisions, faster and responsibly.
Frequently asked questions
Where should an organisation start with AI strategy?
With the problems and goals AI should address, followed by an honest readiness assessment of data, skills and governance, then a small set of prioritised pilots.
What is an AI strategy canvas?
A structured tool that helps leadership agree AI readiness, goals and priority use cases on one page before choosing technology or vendors.
How is AI strategy different in the public sector?
Government entities must align with national AI strategies and put greater emphasis on transparency, fairness, data protection and public trust.
First published 22 May 2025. Reviewed and updated 6 October 2026.