AI Strategy
A structured plan that defines how an organisation will use artificial intelligence to achieve its business objectives, including use case selection, data governance, technology decisions, and implementation sequencing.
Full Definition
An AI strategy is not a technology plan — it is a business plan. It starts with a clear articulation of the business problem, not with a choice of model or platform. A robust AI strategy defines: where AI creates value in your specific context; what data and process foundations must exist first; how you will build, buy, or partner for AI capabilities; how you will govern AI responsibly; and how you will sequence investment to deliver early wins while building toward long-term capability.
Five Components
- Vision and business objectives — what specific outcomes will AI enable?
- AI readiness assessment — what gaps in data, process, or capability must be addressed first?
- Use case portfolio — which AI opportunities to pursue, in what order, and why?
- Technology and talent plan — build vs buy, vendor selection, team upskilling?
- Governance framework — data ownership, model monitoring, risk management, responsible AI principles
Frequently Asked Questions
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Vikrant Chauhan holds CBAP® and CCBA® certifications and has applied these frameworks across 30+ projects in healthcare, SaaS, and fintech.
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