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Most B2B teams measure AI content ROI by what they saved on writing. The real budget drain is the operational layer after the draft: keyword validation, internal linking, metadata, and quality scoring. This post breaks down where per-article costs actually go and introduces a lifecycle efficiency score to benchmark your workflow against a fully automated baseline.

MIT data shows 95% of generative AI pilots miss their P&L targets, yet 79% of teams report productivity gains. The gap lives in the six post-generation steps most teams never instrument: keyword validation, internal linking, quality scoring, metadata, performance attribution, and content decay management.