Identify Initial Use Cases

Campaigns operate with strategies, plans, and playbooks.You can take a similar approach to implementing AI. Start with an initial pilot project by identifying initial implementations for AI that help productivity, and/or have minimal risk or built in safeguards (i.e. drafting something that will be reviewed by a top editor). How do you choose initial use cases? Before selecting tools or building prompts, take a step back and identify where AI can deliver quick, low‑risk wins. The most effective starter use cases typically share the same characteristics: they save time, are repeated often, and already require human review. Ask your team:

• What tasks are the most time‑consuming but routine?
• What work involves drafting, summarizing, or reformatting information?
• What outputs already go through a reviewer before being shared externally?
• What tasks pull information from multiple sources into one place?

Then apply this filter:

• Uses non‑sensitive or approved inputs
• Output is reviewed by a staff lead
• Errors are visible and correctable
• Success meaningfully reduces workload

If a task meets these criteria, it is a strong candidate for an early AI pilot. Examples of what these initial use cases could look like include:  

• Create: Drafting first-pass content fundraising emails, event invitations, volunteer recruitment messages, and social posts then work with colleagues to refine for accuracy, tone, and compliance.
• Edit: Rewriting approved messaging for different channels and audiences (press statements, emails, short social copy), adjusting length and reading level while keeping the core message consistent.
• Research: Summarizing and comparing public information (e.g., news coverage, public reports, legislation summaries) to speed up briefing prep; always verify key facts with primary sources.
• Understand: Analyzing complex information to surface patterns and explain implications. For example, summarize precinct-level election results and flag turnout or margin shifts, then turn the takeaways into plain-language briefs and FAQs for specific audiences. Validate calculations and key conclusions against the source data.
• Catch up: Converting meeting notes into a recap plus action items (owner, due date), and generate a quick summary for staff who missed the discussion.

Use these early efforts as building blocks of knowledge and to demonstrate best practices, such as human review of outputs, and focusing on quality sources of information and data. Once your team is implementing AI in ways that meet your expectations, ramp up to more complex tasks.