Individual applications
How the map is scored. Each use case is ranked by a composite score across five weighted criteria – Strategic Value (25%), Financial ROI (20%), Implementation Safety (20%), Feasibility (20%), and Differentiation Potential (15%). The opportunity is then assessed against the three constraint layers – Substance, Structure, and Governance – to show where content infrastructure sets the performance ceiling.
The value ranges are illustrative, not predictive. The full £3.8–7.5M figure assumes mid-market conditions and loaded staff costs in the £40–80K range. Actual figures will vary by organisation size, salary band, operating model, process maturity, and current content infrastructure state. Click any card to see the specific infrastructure requirements behind the rank.
Cautionary Baseline
The Universal Default – and why it sits below all 30
Content Generation
The use case every vendor leads with. AI drafts, rewrites, and produces content at scale – blog posts, emails, social copy, product descriptions. It requires no infrastructure. That's exactly why it creates no advantage.
The Three Constraint Layers
What determines your performance ceiling across all 30
Accuracy, completeness, clarity, voice consistency. This sets the quality ceiling for what AI can retrieve and surface. Fragmented, contradictory, or shallow content produces fragmented, contradictory, and shallow AI outputs – regardless of model sophistication.
Taxonomy, metadata, content models, semantic relationships. Determines retrieval precision – whether the right content surfaces in the right context. Without structure, retrieval is probabilistic. The model can only find what the architecture makes findable.
Ownership, workflows, standards, maintenance. Determines whether quality is sustained over time. Even strong Substance and Structure degrade without Governance. AI systems operating on degrading content see performance decline regardless of what the model is capable of.