AI Agents & Automation
Less repetition. More control.
Explore the workflows, AI agents and human checkpoints that shape marketing automation.
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Three perspectives.
One clearer picture.
Open a perspective to explore the questions at the heart of this subject.
01Trigger
Define the event that starts the workflow and the input it needs.
02Action
Keep each automated action specific and its permissions limited.
03Review
Decide where a person checks the output or handles an exception.
The reading room
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New articles, newest first.
When simple automation beats an AI marketing agent
Choose between fixed automation and an AI agent by comparing rules, ambiguity, error costs and maintenance across three everyday marketing tasks.
Read the articleKeep a product launch checklist synchronized with AI
Use an agent to compare approved launch milestones, flag conflicting updates and maintain a traceable checklist without silently changing commitments.
Read the articleMeasure whether a marketing agent is reliable
Evaluate marketing agents with correct completion, unintended changes and human correction effort using a fixed set of representative tasks.
Read the articleKeep client context separate in marketing agents
Protect agency workflows with client-specific retrieval, scoped access and deliberate cross-client tests before AI agents handle confidential material.
Read the articleUse an AI agent to prepare event follow up
Turn permitted event notes into traceable lead summaries and reviewed follow-up drafts while preserving contact preferences and the original context.
Read the articleDesign approval queues for marketing AI agents
Make agent approvals easier to review with clear change summaries, relevant evidence and bounded batches that preserve accountability for important actions.
Read the articleBuild an AI quality check for EN and NL campaigns
Check bilingual campaigns against approved terminology, offers and destination links while separating translation quality from technical completeness.
Read the articleBrowser agent or API for a marketing workflow?
Compare browser agents and APIs on permissions, stability, auditability and maintenance before choosing how an AI workflow updates marketing systems.
Read the articlePrepare an RFP response with an evidence based agent
Build reviewable RFP drafts from approved product evidence, track unanswered questions and keep contractual commitments with accountable reviewers.
Read the articleStop failed API calls from sending campaigns twice
Design campaign recovery around action identifiers, status checks and controlled retries so a timeout does not trigger a second customer message.
Read the articleTurn a good prompt into a reusable marketing skill
Package a recurring marketing task with inputs, examples, completion criteria and review rules so a reusable agent skill does more than repeat a prompt.
Read the articleDecide what a campaign agent should remember
Define reusable context, expiry rules and client boundaries for agent memory so recurring campaigns retain continuity without carrying stale assumptions.
Read the articleBuild an agent that checks landing page claims
Compare landing-page statements with approved product facts and route unsupported claims to a reviewer before AI-generated campaign copy is published.
Read the articleWhen a multi agent campaign workflow is worth it
Compare one agent with specialist roles on the same brief and measure accepted output, coordination costs and correction effort before adding complexity.
Read the articleTest an AI agent before connecting the live CRM
Use realistic sample records and failure cases to test duplicate handling, permissions and write recovery before an agent can change customer data.
Read the articleGive a marketing agent a bounded spending budget
Set per-action limits, cumulative caps and stop conditions for an AI marketing agent, with reviewable changes and reconciliation before wider autonomy.
Read the articleMake competitor research agents separate fact from guess
Require dated primary evidence and changed-page references in automated competitor briefings so speculation does not become a marketing intelligence finding.
Read the articleBuild a campaign agent that alerts before acting
Design campaign monitoring with reliable inputs, anomaly rules and clear escalation before giving an AI agent authority to change performance settings.
Read the articleDesign a reviewed marketing workflow from Slack
Use Salesforce’s MCP campaign-management direction to design a clear request, evidence check and approval path from a team conversation to a platform action.
Read the articlePilot Google Ask Advisor on one marketing problem
Test Ask Advisor with a bounded cross-product diagnosis, clear access limits and a reviewed recommendation before allowing changes to live campaigns.
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MARKAIGEN / CHOOSE YOUR NEXT STEP AI marketing automation is most useful when the trigger, input, action and accepted result are clear. Distinguish an assistant that suggests a change from an agent permitted to execute it. Map human checkpoints, exception handling and spending limits before connecting live systems. Expand autonomy only when the evidence supports the next specific task.Start with a bounded marketing workflow
