A glossary on AI maturity for marketers

- A piece of AI software that can take an instruction and complete a multi-step task on its own, instead of just answering a single prompt. Why it matters: Pam classified building your own AI agents as an expert-level move, so it's the rung most marketers grow into rather than start at.

- A five-rung framework (beginner, developing, intermediate, advanced, expert) for how deeply AI is integrated into a marketer's daily work, drawn from ActiveCampaign's research across 1,000 marketing professionals. Why it matters: knowing which rung you're on tells you what action will actually move you up next, instead of trying to skip three steps at once.

- The practice of writing and structuring content so that AI search tools (ChatGPT, Perplexity, Google AI Overviews) surface and cite it. Why it matters: as AI search replaces parts of traditional search, content that ranks well on Google but poorly on AI engines starts losing visibility. Pam used a GEO score (1–10) as her validation step before publishing.

- ActiveCampaign's high-performance marketing framework. Imagine is the strategy and ideation phase, Activate is execution, and Validate is checking the work and feeding insights back to Imagine. Why it matters: 82% of marketers use AI somewhere, but only 23% use it across all three phases. The gap between those numbers is where most of the productivity gains live.

- A system where two or more AI agents each handle a piece of a larger workflow (one writes copy, another builds a landing page, another analyzes results) and coordinate with each other. Why it matters: it's the expert end of the maturity ladder, and Pam's advice was to understand the simpler options first before trying to assemble a multi-agent stack.

- The instruction you give an AI model: a question, a request, or a paragraph of context plus a task. Why it matters: the gap between a generic prompt ("write a blog post for me") and a specific, file-grounded one is where most of the quality difference between novice and intermediate AI users shows up.

- Using AI specifically as a critic, asking it to surface blind spots, risks, inconsistencies, or alternative perspectives on work you've already done. Why it matters: Pam called this the rung most marketers under-use, and it's where AI compounds the value of every other use case.

- ActiveCampaign's plain-language analytics layer that lets marketers ask questions about their data and run validation prompts directly against campaign performance. Where it lives: under Reports. Help Center →

- The drag-and-drop builder for sequences of triggers, conditions, and actions. For example, "tag a contact when they open this email, then wait two days, then send the next email." Where it lives: under Automations in the main nav.

- A one-time email send to a list or segment, distinct from an ongoing automation. For example, today's newsletter or a webinar invite. Where it lives: under Campaigns in the main nav.

- An AI agent ActiveCampaign ships ready to use inside the platform, so you don't have to build it from scratch. Where it lives: surfaced inside the relevant feature areas. For example, copywriting agents inside the campaign builder.

- A saved filter that groups contacts by behavior, attributes, or list membership. For example, "everyone who opened a campaign in the last 30 days and is in the [VERTICAL] vertical." Where it lives: under Contacts → Segments.