An enterprise AI strategy is more than a collection of pilots. It is a decision system for choosing which opportunities deserve investment, what capabilities must be built first, and how leaders will know whether adoption is creating value.
Days 1–30: establish the decision baseline
Interview business, technology, risk and operations teams. Map high-friction decisions, repetitive knowledge work, data dependencies and regulatory constraints. Score opportunities by business value, feasibility, time to evidence and risk.
Days 31–60: design the capability path
Cover data access, identity, integration, evaluation, security, human oversight and change management. Distinguish reusable platform capabilities from use-case-specific work, so every project does not start from zero.
Days 61–90: prove value and prepare scale
Select one or two use cases with measurable outcomes and a bounded operating environment. Define a baseline, launch an evaluation set, measure adoption and document the controls required for production.
The roadmap test
If a roadmap cannot name the business owner, baseline metric, data dependency, control owner and next investment decision, it is still an idea list. For Dubai, the UAE and the wider GCC, also account for multilingual workflows, data residency and sector regulation.
