deIntelligence Management is the discipline of systematically capturing, validating, and making experience knowledge available where decisions happen: for people and for AI systems.
The term deliberately sets itself apart from classic knowledge management. Knowledge management administers what has been documented: repositories, wikis, search. Intelligence Management starts one step earlier: with the knowledge that is written down nowhere. That includes decision logic, exceptions, warning signs, and heuristics: the knowledge experienced employees actually work with.
An Intelligence Management system typically runs through four phases: Identify (where does critical knowledge sit, and which part is at risk?), Capture (collection, for instance through AI expert interviews), Consolidate (structuring, contradiction checks, approval), and Enable (delivery as knowledge articles, training, or as context for AI agents).
The second distinction is the outcome: not an archive, but the ability to act. A validated knowledge base with an owner, validity date, and origin per entry is also the foundation chatbots, copilots, and AI agents need to work reliably. Without validated context, AI scales mistakes instead of competence.