The prioritization framework
Not all agent jobs are good first candidates. The best first jobs are high-frequency, low-risk, tightly scoped, and fast to launch. They are easier to review and build trust before the footprint expands.
The framework has four scoring dimensions: frequency (how often it runs), risk (what happens if it fails), clarity (how obvious the job and outcome are), and rollout speed (how fast you can launch and review it).
Frequency
Daily or multiple times per day. High-frequency jobs generate faster feedback loops.
Risk
Low per-action risk. If the agent makes a mistake, the impact is small and reversible.
Clarity
Clear job, clear owner, clear outcome. The team should understand exactly what the agent is meant to do.
Rollout speed
Fast to launch and review. The job runs in a tool the team already uses, with clear approval logic.
Scoring model
Score each candidate agent job on a 1-3 scale for each dimension. Add the scores. The highest-scoring jobs are usually the best first candidates.
| Dimension | Score 3 | Score 2 | Score 1 |
|---|---|---|---|
| Frequency | Multiple times per day | Daily | Weekly or less |
| Risk | Very low (reversible, low impact) | Low (some impact) | Medium or high |
| Clarity | Clear owner and clear outcome | Mostly clear | Low or unclear |
| Rollout speed | Fast (existing tool, clear logic) | Moderate | Slow (new tool, complex) |
Examples by department
Here are examples of high-scoring agent jobs across sales, support, finance, and operations. These are all reasonable first candidates.
| Department | Agent job | Stack | Total score |
|---|---|---|---|
| Sales | Lead routing | Salesforce | 11/12 |
| Support | Ticket triage | Zendesk | 11/12 |
| Finance | Invoice follow-up | QuickBooks | 10/12 |
| Operations | Meeting follow-up | Slack | 10/12 |
What not to start with
Some agent jobs score low on the framework and make poor first candidates. Here are the most common anti-patterns.
- Low-frequency, hard-to-review jobs. A job that only runs occasionally is harder to review and trust than one that runs often.
- High-risk jobs with financial or legal impact. Do not start with jobs that touch customer payments, contracts, or compliance data. Start with reversible, low-impact jobs.
- Cross-system jobs with unclear ownership. Jobs that span multiple tools are harder to review and approve. Start with a bounded job in one tool.
- Jobs in tools you do not use yet. Do not force a tool migration for the first launch. Start with tools already trusted by the team.
Frequently asked questions
Should we start with the use case that seems biggest?
Not always. Start with the agent job that is high-frequency, low-risk, and easy to review. A smaller job that runs often is usually a better first launch than a large, messy one.
Can we deploy multiple use cases in parallel?
Start with one. Prove the rollout model, keep approvals clear, then expand. Parallel deployment creates ownership confusion when there is no dedicated AI function.
What if the highest-priority use case requires a stack we do not have yet?
Pick a high-priority use case in a tool you already use. Do not force a tool migration for the first launch. The best first agent jobs run in tools already trusted by the team.
How do we know if a use case is too complex for a first launch?
If the job requires cross-system coordination, involves financial writes, or has unclear approval logic, it is probably too complex. Start with a narrow job in one tool with clear inputs and outputs.