When applied intelligence belongs in operational systems
Intelligence belongs where it improves clarity and decision-making—not where it adds visibility without accountability. AI should assist; deterministic logic must remain authoritative where correctness is required.
Intelligence is not a feature category
Operational systems need accurate data, clear workflows, and audit trails. Intelligence—analytics, recommendations, retrieval assistants—belongs where it reduces manual reconciliation or supports repeatable decisions with stable inputs. It does not belong where outcomes cannot be explained or audited.
Good candidates
Document search and summarization with provenance. High-volume classification with human review. Anomaly detection on telemetry with defined escalation paths. Decision-support views that surface exceptions rather than replacing judgment on safety-critical or compliance-critical actions.
Poor candidates
Black-box models on compliance-critical paths. Experiments without an owner in operations. AI layers added because stakeholders expect them—not because a workflow measurably improves. Anywhere deterministic rules already define correct behaviour.
Governance before models
Data quality, access control, and logging come first. A model without governance becomes a liability the first time a regulator or auditor asks how a decision was made. Applied intelligence in mission-critical environments must be explainable by design—and must not replace the logic that correctness depends on.