Which activity is most essential for maintaining AI policy compliance over time?

• A. Regular monitoring of compliance with established policies
• B. Annual budget review for AI initiatives
• C. Conducting market research on competitors
• D. Deploying a new model every quarter

Answer: (A)

Maintaining AI policy compliance over time relies on ongoing monitoring of how systems operate under established policies. Policies aren’t static; models change, data sources evolve, and regulatory or organizational requirements can be updated. Regular monitoring provides continuous visibility into model behavior, data usage, access controls, and decision outputs, so you can spot drift, policy violations, or emerging risks early. This enables timely remediation, adjustments to controls, retraining or fine-tuning as needed, and maintains an auditable trail for governance and audits. In short, a steady monitoring loop keeps compliance effective as the environment evolves.

Other activities don’t directly ensure ongoing compliance. An annual budget review handles resources, not policy adherence. Market research on competitors doesn’t address policy governance. Deploying a new model every quarter can introduce new risks unless every deployment is checked against policies and monitored, which can even undermine compliance if not paired with continuous oversight.