CAIM study guide
CAIM · Work through your exam, one topic at a time.
The Certified Artificial Intelligence Manager (CAIM) is a vendor-neutral credential aimed at people who are accountable for AI outcomes rather than for writing the models themselves: product and programme managers, team leads, consultants, and functional managers moving into AI ownership. It tests whether you can set direction and govern it, build a defensible business case, make sound decisions about data and infrastructure, run delivery across a solution's lifecycle, manage risk and regulatory obligations, organise people and change, and keep systems healthy in production. The CAIM study guide has 7 sections and about 2,132 words.
01AI Strategy and Governance
This domain tests whether you can connect AI ambition to enterprise strategy and install governance that enables rather than blocks delivery. Expect questions on portfolio prioritization, decision rights, policy hierarchy, and risk appetite.
308 words, about 2 min02AI Business Case and Value Realization
This domain tests whether you can build a defensible AI business case and prove value after deployment. Questions often target baselines, total cost of ownership, benefit attribution, and stage-gated funding.
336 words, about 2 min03Data Management and AI Infrastructure
This domain tests the data and platform foundations that make AI repeatable: data quality, lineage, access, contracts, pipelines, feature reuse, and compute capacity. Expect questions on data products, lakehouse patterns, and MLOps infrastructure.
302 words, about 2 min04AI Solution Lifecycle and Delivery
This domain tests how AI solutions move from problem framing to production and iteration. Expect questions on acceptance criteria, baselines, evaluation metrics, human-in-the-loop design, and release management.
286 words, about 1 min05Risk, Ethics, and Regulatory Compliance
This domain tests proportionate AI risk management: impact assessment, bias and fairness, transparency, privacy, security, human oversight, and regulatory mapping. Expect questions on risk tiers, documentation, and third-party models.
306 words, about 2 min06Organization, Talent, and Change Management
This domain tests the operating model, roles, skills, and adoption practices that turn AI capability into routine work. Expect questions on centralization versus federation, role design, workforce transition, and adoption metrics.
306 words, about 2 min07AI Operations, Monitoring, and Continuous Improvement
This domain tests running AI in production: observability, drift detection, incident response, retraining, cost control, and continuous improvement. Expect questions on monitoring metrics, alert thresholds, and change control.
288 words, about 1 min