AI-Enabled Marketing Workflow Lead Model Job Description

Model Job Description: AI-Enabled Marketing Workflow Lead

Role purpose

The AI-Enabled Marketing Workflow Lead turns customer and market evidence into controlled marketing operations. The role designs research, segmentation, content, campaign, testing, and measurement workflows that use generative and agentic AI for bounded work while keeping accountable people in control of sensitive data, public claims, audiences, spend, customer contact, pricing, and external commitments.

This model description can be adapted for titles such as AI Marketing Operations Manager, Growth Marketing and AI Lead, Marketing Automation and AI Manager, Content Operations Lead, Lifecycle AI Manager, or Marketing Experimentation Lead. It is vendor-neutral and does not imply that one person must own every platform or specialist method.

Reporting line and interfaces

The role commonly reports to a Head or Director of Marketing, Growth, Marketing Operations, or Digital. It works closely with Content and Creative, Product Marketing, Lifecycle/CRM, Performance Marketing, Sales and Revenue Operations, Customer Success, Data and Analytics, Product and Engineering, IT and Security, Finance and Procurement, and Legal, Privacy, or Compliance owners.

Core responsibilities

Evidence and research

• Translate a marketing decision into a research question, evidence plan, geography, timeframe, and decision criteria.
• Use approved AI tools to retrieve, structure, compare, and summarize permitted market, customer, competitive, and performance evidence.
• Maintain a source ledger that distinguishes observation, inference, hypothesis, confidence, and unanswered question.
• Validate material claims against original or authoritative sources and record currentness, limitations, and rights.
• Use synthetic respondents or simulated audiences only for hypothesis generation, never as a substitute for consented customer evidence or representative research.

Segmentation and journeys

• Convert evidence into testable segment and journey hypotheses.
• Define inclusion, exclusion, suppression, consent, expiry, and minimum-size rules before activation.
• Document the proposition, expected behavior, confidence, bias risk, and outcome metric for each segment.
• Coordinate activation with authorized CRM, CDP, lifecycle, analytics, and channel owners.
• Escalate sensitive-attribute inference, discriminatory effects, unclear permission, or high-impact use cases.

Content and asset operations

• Build evidence-grounded content briefs and message architectures.
• Define mandatory facts, approved claims, prohibited language, tone boundaries, accessibility needs, rights status, disclosure rules, and review routes.
• Use generative AI to prepare concepts, drafts, variants, adaptations, summaries, and reusable components within the approved brief.
• Maintain version, owner, approval, channel, experiment, outcome, expiry, and retirement records.
• Ensure accountable human review of factual accuracy, brand fit, rights, disclosure, and consumer understanding before release.

Campaign planning and operations

• Translate business objectives into campaign charters with audience, insight, proposition, channel roles, budget and frequency guardrails, dependencies, tests, metrics, and owners.
• Specify handoffs and service expectations across Marketing, Sales/RevOps, Product, Data, Creative, agencies, and governance functions.
• Configure or coordinate approved automation and agent-assisted preparation without assuming that platform access grants decision authority.
• Monitor campaigns, queues, handoffs, and exceptions; route changes through the correct approval gate.
• Make evidence-based recommendations to scale, revise, pause, stop, or investigate.

Testing and measurement

• Define baselines, comparators, hypotheses, primary metrics, guardrails, sample and duration constraints, stopping rules, and decision thresholds.
• Create evaluation rubrics for AI outputs and workflows covering factuality, task completion, policy compliance, brand fit, stability, cost, latency, and escalation behavior.
• Maintain tracking plans, metric definitions, experiment records, dashboards, and decision memos.
• Distinguish attribution from incrementality and communicate measurement uncertainty.
• Reproduce material calculations and investigate data-quality, taxonomy, tracking, or model-output anomalies.

Human-controlled agentic workflows

• Select agent use cases according to decision value, repeatability, data readiness, review burden, reversibility, and failure cost.
• Write a workflow specification naming the trigger, approved context, allowed tools, permissions, prohibited actions, checkpoints, evidence requirements, log fields, stop conditions, exception paths, fallback, rollback, and accountable owner.
• Apply least privilege and coordinate security, privacy, legal, brand, finance, and platform approval where needed.
• Test normal, edge, failure, and adversarial scenarios in a sandbox or simulation before connected use.
• Prevent unattended public publishing, audience modification, paid spend, outbound communication, data export or deletion, pricing, purchasing, contracting, or other external commitment.

Expected work products

The person in this role produces a Research Decision Brief and Evidence Ledger; Segment Hypothesis Cards and Audience Activation Rules; Journey and Opportunity Map; Message Architecture and Governed Content Brief; Asset Variant Matrix and Content QA Record; Campaign Charter and Channel Role Map; Budget and Frequency Guardrail Sheet; Experiment Canvas and AI Evaluation Rubric; Tracking Plan and KPI Tree; Measurement Decision Memo; Agentic Workflow Specification; Tool and Permission Map; Approval Matrix; Exception Log; and Rollback Plan.

Required capabilities

• Practical experience in marketing operations, growth, lifecycle, content operations, product marketing, analytics, experimentation, or an adjacent discipline.
• Evidence-led research and clear source documentation.
• Segmentation, audience, journey, or personalization design using authorized data.
• Campaign planning and cross-functional delivery.
• Content briefing, review, versioning, or asset-governance experience.
• Testing and measurement discipline, including baselines, KPIs, guardrails, and uncertainty.
• Working understanding of generative AI and agentic workflow concepts, tool permissions, evaluations, and logs.
• Ability to translate between marketers, analysts, creative teams, technical teams, and governance owners.
• Strong written judgment: concise briefs, decision records, escalation notes, and executive recommendations.

Preferred evidence

• A portfolio showing a campaign or workflow improved through a controlled test.
• Experience with CRM, marketing automation, analytics, experimentation, content management, or workflow-integration systems.
• Examples of responsible AI use with documented source checks, human approvals, measurement, and rollback.
• Experience working with Sales/RevOps, Data/Engineering, Creative, Finance, Legal, Privacy, or Security partners.

Success measures

Success is assessed through decision quality and operating evidence, not the volume of generated content. Suitable measures include research rework, source accuracy, segment activation quality, content cycle time, first-pass approval rate, experiment throughput and validity, data-quality defects, campaign business outcomes, agent exception rate, approval latency, rollback readiness, and adoption of reusable workflows. Measures should be defined before deployment and interpreted with appropriate comparators and uncertainty.

Operating cadence

• Daily: review failed validations, queued approvals, exceptions, data freshness, complaints, cost or spend anomalies, and rollback readiness.
• Weekly: review research gaps, segment and suppression health, content queues, campaign pacing, experiment integrity, agent evaluations, handoffs, and decisions due.
• Monthly: review business outcomes, data quality, model or workflow drift, permissions, vendor changes, content retirement, complaint patterns, and portfolio priorities.
• Event-driven: stop and escalate when a consequential threshold is crossed, an unapproved action is requested, evidence becomes unreliable, or safe fallback and rollback cannot be demonstrated.

Decision rights and escalation

The role may prepare analyses, propose segments, draft content, design campaigns, run authorized tests, recommend changes, and manage low-risk internal workflows within policy. Final authority follows organizational rules. Public claims, customer contact, sensitive or inferred data, audience activation, paid spend, pricing, destructive change, external commitments, legal interpretation, and high-impact decisions require the designated owner.

The role stops and escalates when evidence is missing or contradictory; consent or rights are unclear; a protected or sensitive attribute could be inferred; the requested action falls outside scope or permission; cost, spend, error, or complaint thresholds are exceeded; measurement cannot support the claim; or a safe rollback is unavailable.

Explicit exclusions

This role does not perform political persuasion, marketing directed at children, covert manipulation, deceptive synthetic media, unconsented data enrichment, or automated high-impact decisions. It is not legal advice, data-science licensure, software-engineering certification, or third-party platform certification. No employment, earnings, compliance, or campaign-performance outcome is guaranteed.