AI Agents by Business Function: Eight Playbooks on Rails

Each playbook follows the AI agent rails method: a weekly routine, condensed rail cards, a 30/60/90-day path and a table of when a vendor agent is enough.

The eight function playbooks

Each row gives a function's agents, its typical levels and the agent we would run first, with the reason. Start there only if that function passes the questions in the next section.

How do you choose a first function?

The best first function is the one that can fail cheaply, measure honestly and name an owner. Loud demand is a poor guide, because the team asking hardest often has the riskiest job. Put these five questions to each candidate.

Choose the function with the most good signs, and treat any warning about ownership as a blocker.

Which functions suit which situations?

Each function makes a good first choice in different circumstances. These are the patterns we would look for.

• Marketing operations is a sensible default. It has the most agents, two of them low risk, and the roadmap's assisted-work stage reads like its job list.
• Compliance, privacy and security suits a team whose DPO is already asking how agents are controlled. Hold back the Policy Drift Checker at first, because it compares rail cards with the ledger, so it needs other rails to exist.
• Platform operations suits a team that already runs on-call. The Cost Watcher reports spend per rail, so it earns its place as soon as a second rail is running.
• Product and growth carries the fewest risks, since every agent stays at L1. If your analysts already read out experiments well, a dashboard may be all you need.
• Lifecycle marketing and customer support sit close to consent and customer text, so they suit teams with some experience, even though each has a safe first agent. Support case text is untrusted, so keep it away from profile data.
• Sales and revenue operations needs one check first. Keep reports by rail and role, and do not rank named sales staff. Annex III point 4(b) of the EU AI Act lists monitoring workers' performance and allocating tasks by individual behaviour as high-risk uses 1, so take advice before any agent touches them.

When is a playbook the wrong answer?

A playbook is the wrong answer when one team has one job. Go straight to the use-case index and write one rail card. It is also more than you need when a vendor's agent does the job on data the vendor already holds, and you accept its controls.

The three agents that work across functions are not a function themselves. The Orchestrator, the Trainer and the VP Marketing agent route work, keep tests current and give leadership a readout. The control plane page shows how they fit around the eight functions.

PrivyCDP's product page describes AI-assisted review of groups, workflows, unusual events and reports, and an MCP-ready interface; the playbooks themselves are a vendor-neutral method, not product features.