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A 90-Day Roadmap for Piloting AI Agents in Event Marketing

Writer: Caylee Donaldson
Caylee Donaldson
5 hours ago
2 min read

You don't need a year to prove the model. You need 90 days, one clear use case, and the discipline to measure honestly. Here' s the roadmap I take every client through.


A practical, three-phase plan to get from "we should look at AI agents" to "we have one in production with measurable outcomes." Built for a team with a small headcount and a real budget — not an enterprise transformation programme.


Phase 1: Audit & anchor (days 1–30)


You don't have an AI problem yet — you have a data and use-case problem. This phase forces honesty about both.


  • Audit your attendee data: where does it live, who owns it, how clean is it?

  • List every candidate use case across the lifecycle (target: 10–15).

  • Plot them on the prioritisation matrix.

  • Pick one Quick Win to pilot.

  • Baseline the metric you'll measure improvement against (e.g. registration completion rate, follow-up open rate).

  • Write the guardrails: what is this agent not allowed to do?

Phase 2: Build & bound (days 31–60)


Pick a platform you already pay for if you can. Build narrow. Test against your own judgement before you test in the wild.


  • Choose your platform — prefer enterprise CRM-embedded agents first (Agentforce, Breeze, Microsoft's Sales Qualification Agent).

  • Configure the agent in research-only or observation mode.

  • Apply hard limits: what it can offer, what it can spend, what it can promise.

  • Build a kill switch — a single command that pauses the agent across all channels.

  • Run a two-week internal shadow test: agent suggests, human approves.

  • Document every edge case it gets wrong. Update prompts.

Phase 3: Ship & measure (days 61–90)


Limited launch. Compare to baseline. Document the playbook so the second agent takes half the time.


  • Launch to a defined segment (one event, one region, one persona).

  • Compare to baseline after two weeks of live data.

  • Calculate fully-loaded cost: platform + ops + time.

  • Document prompt structure, guardrails, integration map, kill-switch test.

  • Make a binary decision: scale, refine, or kill.

  • If scaling, identify the next Quick Win and start Phase 1 again.

Your Sample KPI Dashboard


Five metrics, reviewed monthly, that prove the pilot is working:

 

  1. AI-attributed pipeline (£): Pipeline directly linked to AI-driven workflows.

  2. Hours saved per marketer per week: Measured via weekly self-report and audit.

  3. Deflection rate (%): Inbound enquiries resolved without human intervention.

  4. Personalisation engagement uplift: Open/click rates on AI-personalised vs. controlled sends

  5. Incident count: Governance issues, hallucinations, vendor breaking changes per month.


The one non-negotiable


Don't skip guardrails. SaaStr's rogue agent gave away $2,000 of free tickets to their flagship event because no one defined what the agent could not offer. The financial cost was modest. The reputational cost — and the case for AI agents internally — was much higher.

Want a 90-day roadmap built for your own team and budget? Get in touch to get started.

Sources & further reading

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