Pillar 8 — Sustaining, Optimization & Lifecycle
The AI system that delivered value at deployment will not continue to deliver value without active governance. Models drift as underlying data changes. Data quality degrades as source systems evolve. Regulatory requirements change as new frameworks come into force. Vendor systems update, sometimes without notice.
Without sustaining disciplines, a well-governed programme becomes an undocumented dependency within 18 months.
The AI Lifecycle framework
The Legal AI OS defines five AI Lifecycle stages:
Concept — Use case identified; governance assessment initiated; AI BoM entry created (pending).
Build — System configured, tested, and validated against quality and risk standards; AI BoM entry completed.
Deploy — System in production; governance controls active; performance baseline established.
Operate — Active system under continuous governance; quarterly performance review; AI BoM kept current.
Sunset — System decommissioned; data handling confirmed; AI BoM entry closed; lessons captured.
The four Pillar 8 capability domains
8.1 — AI Lifecycle Governance
Governance checkpoints at each Lifecycle stage: what must be documented, who approves each transition, and what evidence is required.
8.2 — Optimisation Cadence
Quarterly performance review cadence; model revalidation schedule; vendor update response protocol.
8.3 — DPS Refresh Cycle
Annual DPS review; governance evidence pack update; regulatory change scan; re-submission to board.
8.4 — Sunset Governance
Structured decommission process; data deletion confirmation; dependency review; post-sunset lessons.
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Blueprint 2026 — Chapter 12 of 15. Part of the Legal AI OS Blueprint 2026: The Defensibility-First Operating Manual.
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Five-stage AI lifecycle from Concept to Sunset within the Legal AI OS
Treat every AI system as a living asset: governed at each lifecycle stage, optimised on a fixed cadence, and decommissioned with the same rigour as its initial approval.