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95% of AI projects fail. Score your approach against the three critical patterns that separate success from failure.
The causes of AI project failure are rarely technical. They're strategic: the wrong build-vs-buy decision, the wrong governance structure, or a generic solution applied to a context-specific problem.
This scorecard diagnoses your project against three critical decision patterns: Build vs Buy (are you developing in-house what you should purchase, or purchasing what you should build?), Centralise vs Distribute (is your AI governance structure appropriate for your organisation?), and Generic vs Contextual (is your solution adapted to your specific business context?).
Misalignment in any one of these areas significantly increases your risk of joining the majority of AI projects that fail to deliver value.
The research behind this scorecard's failure patterns
Build vs buy decisions have hidden cost implications
If your risk score suggests a different approach
Assess your organisation's overall AI readiness
Understand realistic costs for your approach
Find the highest-value use cases to target
Most AI projects fail due to three strategic mismatches: wrong build-vs-buy decisions, inappropriate governance structures, and generic solutions applied to context-specific problems. The causes are rarely technical.
Start by diagnosing your current approach against known failure patterns. This scorecard assesses three critical decisions: build vs buy, centralise vs distribute, and generic vs contextual. Misalignment in any area significantly increases risk.
Whether to develop AI capabilities in-house or purchase from vendors. Neither is inherently better — the right choice depends on your capabilities, timeline, budget, and differentiation needs. Getting this wrong is one of the most common causes of failure.
Generic AI solutions work the same regardless of business context. Contextual adaptation means tailoring the AI to your specific data, processes, terminology, and decision patterns. Most AI failures come from deploying generic solutions where contextual adaptation was needed.