UK

United Kingdom · Marketing · Principal/Manager (12-16 years)

Manager, AI Marketing

Here is the whole job, in plain words. What it is, what you decide, how you're judged, how people get here and where they go next. Then the part no course gives you: twelve AI tutors who learn your work.

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One email: what AI is changing in this job, and where to start free. With a link back here. Nothing else follows unless you confirm your address.

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  • Experience bandPrincipal/Manager (12-16 years)
  • Direct reports5-8 reports
  • Reports toDirector, Marketing AI & Automation
  • UK framework levelUsually a manager, or the deepest specialist in a team

Also advertised as Principal AI Marketing Strategist · Head of Marketing AI · AI Marketing Lead

Built on 43,079 real UK job descriptions we analysed · grounded in qualifications employers recognise

Two short quizzes about you

1From this job to a course

The qualifications matched to this job

NCC Education Level 5 Extended Diploma in Computing with Data Science NCC Education Limited · Level 5 · covers 2 of 7 standards
Level 6 Award in Data-led Decision Making Institute of Sales Professionals · Level 6 · covers 1 of 7 standards
CMI Level 5 Diploma in Leading AI Transformation Chartered Management Institute · Level 5 · covers 1 of 7 standards
CMI Level 5 Certificate in Leading AI Transformation Chartered Management Institute · Level 5 · covers 1 of 7 standards
Qualifi Level 5 Extended Diploma in Computer Science Qualifi Ltd · Level 5 · covers 1 of 7 standards

Matched from the standards this job is measured against: a suggestion, not an official ruling.

The units you would start with

Artificial Intelligence NCC Education Level 5 Extended Diploma in Computing with Data Science
Data-led Decision Making Level 6 Award in Data-led Decision Making
Apply the Concepts of Data Science to Computer Engineering NOCN Level 5 Diploma in Computer Engineering (Information Technology and Data Science)
AI Fluency for Managers and Leaders CMI Level 5 Diploma in Leading AI Transformation
Introduction to Artificial Intelligence Qualifi Level 5 Extended Diploma in Computer Science

The future skills this job leans on

AI Fluency working with AI as a thinking partner
AI Governance Fluency using AI responsibly
Automation Fluency building AI into how work runs
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Your Plan Illustration

Built for Manager, AI Marketing

5 units that map to this job, from the qualifications that cover it.

  1. Artificial Intelligence NCC Education Limited · covers 2 of 7 standards Level 5
  2. Data-led Decision Making Institute of Sales Professionals · covers 1 of 7 standards Level 6
  3. Apply the Concepts of Data Science to Computer Engineering NOCN · covers 1 of 7 standards Level 5
  4. AI Fluency for Managers and Leaders Chartered Management Institute · covers 1 of 7 standards Level 5
  5. Introduction to Artificial Intelligence Qualifi Ltd · covers 1 of 7 standards Level 5
These are the real units behind this job, in the order they rank for it. Nothing here is marked done, because this plan has not been started by anyone yet. Yours would fill in as you go.

2AI and this work

Will AI change your work as a Manager, AI Marketing?

Nobody can say exactly how. Here is what this job is being asked for next, and where to start.

The new skills this role is being asked for

  • Ethical AI & Explainable AI (XAI) Governance
  • AI-Powered Customer Journey Orchestration
Why each one is rising

The future skills this job leans on

We'll only ever tell you what we can actually back up. No hype, no scare tactics.

What happens when you start

Next, a free account. We build your Manager, AI Marketing plan as you set up, starting with a Future Fluency module on using AI in your job. No card.

Your first Future Fluency module is free. After that, your AI tutor is £70 a month.

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3What this role really is

This job means leading a team that uses AI to shape and run marketing campaigns. It calls for setting direction, coaching specialists, and showing the real impact of AI on business results. It blends technical understanding with commercial thinking, more about strategy than writing code.

4What you'd actually use

The tools this job runs on, and how well you'd need to know each one.

HubSpot Marketing Hub Strategic

Architecting complex automation sequences, defining enterprise data models within the CRM, evaluating platform capabilities for new initiatives, owning the vendor relationship and roadmap.

Segment (Customer Data Platform) Architect

Designing the enterprise-wide customer data strategy, governing data quality and privacy compliance across all sources and destinations, making decisions on new integrations and data flows.

Dataiku (AI / Machine Learning Platform) Strategic

Owning the MLOps strategy for marketing, deciding which business problems are suitable for Dataiku vs. other solutions, championing AI literacy and adoption across the marketing organisation.

Jasper / Copy.ai (Generative AI Content) Strategic

Setting enterprise policy on generative AI usage, ethics, and plagiarism, evaluating and selecting new generative AI platforms for the marketing organisation, defining brand voice profiles at scale.

Google Analytics 4 (GA4) Strategic

Defining the cross-platform measurement strategy, interpreting attribution model outputs to inform multi-million pound budget allocation, ensuring data integrity for strategic reporting.

Tableau Architect

Governing the Tableau Server environment for the marketing department, designing the 'single source of truth' dashboards for executive reporting, ensuring data visualisation standards are met.

PostgreSQL Strategic

Advising on database schema design for marketing analytics, optimising query performance for large-scale data sets, ensuring data accessibility for team's analytical needs.

5What you get to decide, and how that grows

Power in a job isn't your title. It's what you're allowed to decide. Here's how it grows as you move up.

The choiceComing in Where you are nowThe step above
Team Hiring & Performance No authority; provides input on candidate fit. Interviews candidates; provides feedback to hiring manager. No direct performance management. Makes recommendations on hiring, provides input on performance reviews for mentees.
Budget Allocation (within function) No authority; follows budget guidelines. Proposes small project expenses (e.g., £1K-£5K) to manager for approval. Recommends project budgets up to £25K; consults on larger spend.
AI Model Deployment & Strategy Executes deployment steps under supervision; no strategic input. Deploys models for specific campaigns; proposes model improvements. Leads model development and deployment for workstreams; makes recommendations on model strategy.
Vendor Selection & Management No authority; uses existing tools. Researches new tools; provides input on feature sets. Recommends specific tools or features for projects up to £50K; manages relationships with existing vendors.

6How you'll be judged

The scoreboard, and what is not on it. The hard targets, how often each is actually looked at, and the quiet signals that never reach a dashboard.

Marketing-Sourced Pipeline Value
The total value of sales opportunities generated directly through AI-driven marketing programmes managed by your team.
Target · Generate £5M - £10M in new pipeline annually

Your team's AI-optimised lead nurturing programme contributes £2.5M to the sales pipeline in Q3, exceeding the £2M target.

Customer Acquisition Cost (CAC) Reduction
The percentage decrease in the average cost to acquire a new customer, specifically attributable to AI-driven optimisations.
Target · Reduce CAC by 10-15% year-on-year

By using AI for predictive ad targeting and budget allocation, your team helps drop the average CAC from £150 to £130, a 13.3% reduction.

AI Programme Return on Investment (ROI)
The financial return generated from specific AI marketing initiatives (e.g., a new CLV model, a personalisation engine) compared to their cost.
Target · Achieve a minimum 3:1 ROI on all major AI marketing programmes

A new AI-powered recommendation engine costs £250K to build and run, but generates £800K in incremental revenue, giving you a 3.2:1 ROI.

Team Productivity Uplift
The measurable increase in output or efficiency of your team, often through automation or better processes you've implemented.
Target · Increase team output by 20% within 12 months (e.g., more campaigns, faster analysis)

After implementing new AI tools and workflows, your team is able to launch 30% more A/B tests per quarter without increasing headcount, showing a clear productivity gain.

Team Development & Retention
How well you're building, mentoring, and retaining your team of AI Marketing Specialists.
  • Low voluntary attrition rate (below 10%), positive feedback in skip-level meetings, team members successfully promoted, strong engagement scores in internal surveys, active participation in professional development.
Strategic Influence & Roadmap Adoption
Your ability to shape the overall marketing strategy through AI insights and ensure your team's roadmap is aligned and adopted by senior leadership.
  • Your AI marketing roadmap is formally approved and funded, other departments actively seek your team's input on strategic projects, you're regularly presenting to the wider leadership team, and your recommendations are acted upon.
Data Governance & Ethical AI Practices
Ensuring all AI marketing activities are compliant with privacy regulations and adhere to our internal ethical guidelines.
  • No compliance breaches (e.g., GDPR fines), clear documentation of data sources and model biases, proactive involvement in developing internal AI ethics policies, regular audits of AI model fairness and transparency.
Innovation Pipeline & Capability Building
Your success in identifying, piloting, and embedding new AI capabilities and tools that keep us ahead of the curve.
  • Launch of 2-3 new, impactful AI marketing capabilities annually, successful pilot programmes, positive feedback on the value of new tools, team members are upskilled in emerging technologies.

7Would you like it

Both sides. What people enjoy, and what grinds them down.

What people enjoy
Building and Developing a High-Performing Team

You'll spend time coaching your specialists, helping them unblock technical issues, celebrate their successes, and plan their career growth. You'll get a real kick out of seeing your team members develop new skills and take on bigger challenges.

One of your junior specialists successfully deploys their first predictive model into production, and you feel immense pride in their achievement, knowing you helped guide them there.

Driving Tangible Business Impact through Innovation

You're motivated by seeing your team's AI programmes directly contribute to the company's P&L—whether that's through increased revenue, reduced costs, or better customer retention. You love connecting the dots between complex models and real-world commercial results.

Your team's new CLV model leads to a 15% increase in high-value customer retention, directly impacting the company's annual revenue targets, and you're the one presenting those results to the board.

Shaping the Future of Marketing with AI

You're excited by the idea of being at the forefront of AI in marketing, constantly exploring new possibilities, and setting the strategic direction for how our organisation uses these powerful tools. You want to build a truly 'smart' marketing function.

You successfully champion the adoption of a new generative AI platform that revolutionises our content creation process, positioning the company as an industry leader in AI-powered marketing.

What frustrates people
  • The 'Garbage In, Garbage Out' Reality: Your team will still spend a huge chunk of their time cleaning and wrangling inconsistent data from various systems before they can even get to the 'cool' AI stuff. It's a constant battle.
  • The 'Just Sprinkle Some AI On It' Request (from above): You'll get vague, high-level requests from senior leaders who think AI is a magic wand. Your job is to translate that into something actionable for your team, which can be exhausting.
  • Explaining the Black Box (to the Board): Trying to explain why an AI model made a specific recommendation to a sceptical executive, without resorting to overly technical jargon, is a skill you'll hone out of necessity.
  • The Hype Cycle Treadmill: You'll constantly be asked about the 'next big thing' (e.g., GPT-5, Sora) and will need to manage expectations about what's actually feasible to implement this quarter versus what's just marketing hype.
  • Battling the HiPPO (Highest Paid Person's Opinion): Presenting a data-driven recommendation from your team's model, only to be overruled by a senior leader's 'gut feeling' can be incredibly frustrating. You'll need to learn to influence and persuade.
  • Proving Incremental ROI (the long game): The impact of your team's work is often a 5% lift here, a 10% improvement there. It can be a struggle to prove the massive cumulative value against a single, flashy traditional campaign that gets all the glory.
  • Privacy Police: Navigating the minefield of GDPR, CCPA, and other privacy regulations that constantly limit the data you can use. You'll need to guide your team to find clever, compliant workarounds, which isn't always easy.
What this role does not give you
  • A perfectly clean, ready-to-use dataset for every project.
  • Guaranteed immediate adoption of every AI model your team builds.
  • A quiet, predictable environment where priorities never shift.
  • A role where you only focus on technical execution and don't have to deal with people or politics.

8Who you work with

Your work here directly impacts our ability to acquire and retain customers efficiently, driving millions in pipeline value and revenue. You'll be shaping our entire AI marketing strategy, building a critical capability for the business, and developing the next generation of AI marketing talent. Get it right, and you'll be a key driver of our competitive advantage. Get it wrong, and we'll be playing catch-up for years.

Inside the business
  • Director, Marketing AI & Automation (your boss, for strategic alignment)
  • Head of Product (for aligning AI initiatives with product roadmaps)
  • Sales Leadership (to ensure AI-driven leads are high quality)
  • Finance Director (for budget approval and proving ROI)
  • Head of Data & Analytics (for data infrastructure and governance)
  • Brand & Content Leads (for AI-generated content guidelines)
Outside the business
  • Key MarTech Vendors (e.g., HubSpot, Dataiku, Segment)
  • Industry Peers & Forums (for insights and best practices)
  • External Consultants (on specific AI projects or ethical guidelines)

9What you need before you start

Not a wish list. The things you would be expected to already have.

  • Proven experience leading and mentoring a team of technical specialists (minimum 3 years).
  • A track record of managing significant marketing budgets (e.g., £500K+) and demonstrating clear ROI.
  • Experience in setting strategic direction and building multi-year roadmaps for a functional area.
  • Deep expertise in at least two core AI marketing domains (e.g., predictive analytics, personalisation, generative AI).
  • Demonstrable ability to translate complex technical concepts into clear, actionable business insights for senior leadership.
  • Experience with data governance, privacy regulations, and ethical considerations in AI.

10What to practise next

Where the job is going, and what to do about it starting this week.

Advanced MLOps & Productionisation

Critical within 12 months—it's not enough to build a model; it needs to be reliably deployed, monitored, and maintained in production. As we scale our AI efforts, robust MLOps practices are essential to prevent model drift, ensure uptime, and deliver consistent value.

Model Monitoring & Alerting · Automated Retraining & Deployment · Version Control for Models & Data · Scalable Infrastructure for AI

  • This month: Review your team's current MLOps practices. Where are the biggest bottlenecks or risks?
  • Month 2: Research best practices for MLOps in a marketing context. Look at how other companies manage their production models.
  • Month 3: Work with your Data & Analytics counterparts to define a shared MLOps roadmap and standard operating procedures for marketing AI models.
  • Month 4: Oversee the implementation of a new model monitoring dashboard for your team's most critical production model.

Quick win: Implement automated alerts for any production model whose accuracy drops by more than 5% in a given week. It's a simple start to proactive monitoring.

Data Mesh & Data Product Thinking

Important within 18 months—as our data landscape grows, a centralised data lake becomes a bottleneck. Moving to a data mesh approach, where data is treated as a product owned by domain teams, will be crucial for scaling AI initiatives and fostering data literacy across marketing.

Domain-Oriented Data Ownership · Data as a Product · Self-Serve Data Platforms · Federated Governance

  • This month: Read Zhamak Dehghani's 'Data Mesh' book. It's a game-changer.
  • Month 2: Identify 1-2 key marketing datasets that could be reframed as 'data products' for your team.
  • Month 3: Start discussions with our central Data & Analytics team about their long-term data strategy and how a data mesh approach could benefit marketing.
  • Month 4: Propose a pilot project where your team 'owns' and serves a specific marketing data product to another internal team.

Quick win: Create a clear 'data contract' for one of your team's most used datasets, outlining its schema, update frequency, and quality metrics. Treat it like a product spec.

11Staying current once you are in

What people here do to keep up
  • Regularly attending industry conferences (e.g., Marketing AI Conference, CDPs for Marketers Summit) to stay abreast of the latest trends and network with peers.
  • Subscribing to leading AI/ML research journals and marketing technology blogs to keep your knowledge current.
  • Actively participating in online communities or forums dedicated to AI in marketing, sharing insights and learning from others.
  • Mentoring junior talent, either formally or informally, to solidify your own understanding and leadership skills.
  • Taking advanced online courses in areas like deep learning, reinforcement learning, or advanced statistical modelling, even if you're not coding them daily, to maintain technical literacy.

12The rising capability

The rising capability

Zavmo analysis

What's rising in its place

This is where the work is heading, and the higher pay with it. Get fluent here and the shift stops being a threat and starts being your edge.

Ethical AI & Explainable AI (XAI) Governance

Critical within 6 months—regulatory bodies are getting serious about AI ethics, and consumers are demanding transparency. We can't afford to have 'black box' models making decisions without understanding why. Brand reputation and legal compliance are at stake.

  • Fairness & Bias Detection
  • Transparency & Interpretability
  • Privacy-Preserving AI
  • Accountability Frameworks

AI-Powered Customer Journey Orchestration

Important within 12 months—customers expect seamless, hyper-personalised experiences across every touchpoint. We need to move beyond individual campaign optimisation to orchestrating entire journeys with AI. It's about delivering the 'next best action' consistently, not just in one channel.

  • Real-time Decisioning Engines
  • Dynamic Content Optimisation
  • Cross-Channel Cohesion
  • Reinforcement Learning for Journeys

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • Predictive Lead Scoring (Strategic Oversight)
  • Multi-Touch Attribution (MTA) Modeling (Strategic Definition)
  • Customer Lifetime Value (CLV) Modeling (Programme Ownership)
  • Personalisation & Recommendation Engines (Architectural Design)
  • A/B/n Testing & Experimentation Design (Culture & Governance)
  • Prompt Engineering & LLM Fine-Tuning (Standard Setting)

14The pathway

The pathway

How you actually get there, here

How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.

  1. 1

    Lead AI Marketing Strategist (L4)

    3-5 years as a Lead

    Skills to master

    • Mastering programme ownership, influencing senior stakeholders without direct authority, beginning to define strategic approaches for specific AI marketing domains (e.g., lead scoring).

    You're ready to move on when

    • Successfully owned and delivered 2-3 major AI marketing programmes end-to-end.
    • Consistently provided informal mentorship and guidance to junior team members.
    • Demonstrated ability to translate complex business problems into clear, actionable AI solutions.
    • Proactively identified and championed new AI tools or methodologies that delivered measurable impact.
  2. 2

    Senior AI Marketing Specialist (L3)

    5-7 years as a Senior Specialist

    Skills to master

    • Deep technical expertise in building and deploying AI models, leading complex projects, and effectively communicating technical outcomes to non-technical audiences. Starting to mentor junior colleagues.

    You're ready to move on when

    • Successfully led 3-5 complex AI marketing projects from conception to deployment.
    • Consistently delivered projects on time and within scope, even with ambiguous requirements.
    • Received strong feedback on your ability to mentor and unblock junior team members.
    • Proactively identified and resolved significant technical challenges in AI model development or deployment.
  3. 3

    Marketing Manager (with strong AI/Data focus)

    5-8 years as a Marketing Manager

    Skills to master

    • Proven leadership and team management skills, deep understanding of overall marketing strategy, and a strong, demonstrable interest and experience in integrating data science and AI into marketing campaigns.

    You're ready to move on when

    • Successfully managed a marketing team of 3+ individuals, achieving team goals and developing talent.
    • Consistently delivered marketing campaigns that exceeded targets, using data-driven insights.
    • Actively sought out and implemented AI/data solutions in previous roles, even if not a core focus.
    • Demonstrated a strong understanding of the technical capabilities and limitations of AI in marketing.

15Where this role leads

The long view: This work can lead to roles such as chief marketing technology officer or head of data and analytics, shaping AI and data strategy across a whole organisation.

The ten Future Fluencies

Zavmo analysis

The credential is what you can do today. These are what keep you valuable.

A qualification proves you can do the job as it's defined today. These ten are what decide whether you're still the obvious person for it in five years. They're the capabilities employers are now writing into senior roles faster than people are learning them. Zavmo weaves them through whatever you study, so you come out with both: the credential and the fluency.

The highlighted ones are the Fluencies your role leans on hardest, from how Manager, AI Marketing is actually changing.

Where it leads

Roles this leads to

How you would learn this

One to one, on the work you already do

A tutor sets the task against your own job and marks the reasoning, at your pace. There is no cohort to fall behind.

A lesson from Artificial Intelligence, worked against Manager, AI Marketing.

Artificial Intelligence Level 5

Applied to your work in Manager, AI Marketing

This unit aims to provide learners with an understanding of Artificial Intelligence (AI) and its applications, enabling them to apply AI search strategies and knowledge representation techniques to solve problems. Learners will also assess techniques for reasoning with uncertain knowledge and understand machine learning techniques, demonstrating a comprehensive knowledge of AI principles and applications.

How the thinking builds
  1. 1 Remember
  2. 2 Understand
  3. 3 Apply
  4. 4 Analyse
  5. 5 Evaluate
  6. 6 Create
An illustration of a Zavmo lesson, built from this role’s own route. The unit, its objective and every criterion above are the awarding body’s own words, not an example.

It is £70 a month, billed monthly. Your free first module is Future Fluency, and you can cancel any time.

Start my Manager, AI Marketing plan, free
See Your Progress Grow Illustration
Manager, AI Marketing
  • Predictive Lead Scoring (Strategic Oversight)
  • Multi-Touch Attribution (MTA) Modeling (Strategic Definition)
  • Customer Lifetime Value (CLV) Modeling (Programme Ownership)
  • Personalisation & Recommendation Engines (Architectural Design)
  • A/B/n Testing & Experimentation Design (Culture & Governance)
  • Prompt Engineering & LLM Fine-Tuning (Standard Setting)
This is your Mind Palace on learn.zavmo.ai. Every skill above comes from this role's own record, not an example borrowed from another job. A node lights up when you evidence it, and what you build stays yours between jobs. That is the part a course cannot do.

16The detail, folded away

Everything else the record holds

The career branches in full, how AI is already showing up in the day-to-day, and the questions people ask about this job. Here when you want them, out of the way while you decide.

Where it leads next, rung by rung

Where it leads

The career path, and where it branches

Manager, AI Marketing is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

  1. Director, Marketing AI & Automation (L6)

    3-5 years in the Manager role

    From managing a team to leading a business unit or major functional area, owning the multi-year roadmap and significant P&L.

    • Multi-year AI Roadmap Definition Creating a 3-5 year vision for AI in marketing, securing budget, and driving execution.
    • Cross-functional AI Integration Leading initiatives to embed AI across marketing, sales, and product functions.
    • M&A Due Diligence (AI/Tech focus) Evaluating potential acquisitions from an AI and MarTech perspective.
    • Industry Thought Leadership Representing the company as a leading voice in AI marketing.
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, as a manager, your time is gold. You're juggling strategy, team development, stakeholder management, and still trying to stay ahead of the curve. What if AI could give you back a significant chunk of that time, not just for your team, but for you?

This isn't about AI replacing your job; it's about AI making you a more effective, strategic, and less stressed leader. We're talking about tools that help you plan better, manage your team more efficiently, and communicate your vision with crystal clarity, all while cutting down on the tedious bits. Imagine having a super-smart assistant for your most critical management tasks.

Strategy & Roadmap Assistant

Use AI to synthesise market trends, competitor analysis, and internal performance data. It can quickly draft initial strategic proposals, identify white-space opportunities, and even suggest multi-year roadmap components, giving you a massive head start on planning sessions. No more staring at a blank page for hours.

Team Performance & Coaching AI

Imagine an AI that analyses your team's project outputs, identifies common roadblocks, and even suggests personalised training resources for each specialist. It can flag potential burnout risks or skill gaps before they become big problems, freeing you up for high-impact coaching conversations instead of endless data digging.

Vendor & Tech Stack Evaluator

When you're considering a new MarTech platform or AI tool, use specialised AI to quickly compare feature sets, analyse pricing models, read reviews, and even simulate potential ROI based on your specific business needs. This cuts down weeks of manual research and helps you make smarter, faster procurement decisions for your budget.

Executive Comms & Board Prep

Generate executive summaries, board reports, and complex stakeholder presentations from raw data, team updates, and strategic documents in minutes. AI can translate technical model metrics into business-friendly language, create compelling narratives, and even suggest visualisations, ensuring your message lands perfectly every time.

Common questions

Common questions

How do you become a Manager, AI Marketing?

Common routes in include Lead AI Marketing Strategist (3-5 years as a Lead), Senior AI Marketing Specialist (5-7 years as a Senior Specialist) and Marketing Manager (with strong AI/Data focus) (5-8 years as a Marketing Manager). Times vary with prior experience.

Where can a Manager, AI Marketing progress to?

This role can lead on to Director, Marketing AI & Automation (3-5 years in the Manager role), depending on the skills you build.

What new skills matter most for a Manager, AI Marketing?

Increasingly, Ethical AI & Explainable AI (XAI) Governance and AI-Powered Customer Journey Orchestration. These are the skills our record of this role lists as growing.

Free tools

Want a read on where you stand?

Three free tools, no account needed. Each one ends with a role, a level and a way in.

Read the Zavmo manifesto to understand how you will be taught Meet your tutors

Or try another one

17Where to go from here

Other roles at Level 5

Same depth of qualification, different job. Useful if the work appeals but this particular role does not.

 More jobs in marketing

Stay in the field you know and move sideways rather than up.
If you leave this industry

The skills built here, leading AI strategy, managing technical teams, and driving measurable results, apply across data-intensive industries such as FinTech, e-commerce, SaaS, and consultancies working on AI transformation.

This role profile is © 2026 Growth Engineering Technologies Ltd. Built from UK occupational standards and regulated qualification data, and written for Zavmo.

You're not behind. You're right on time. The shift is only just beginning. Your role won't look the same in two years. Be the one who leads the change, not the one it happens to. Start my Manager, AI Marketing plan, free What happens next: a free account, then we build your plan as you set up. No card. Build your plan, see your roadmap and meet the twelve tutors matched to you. All free. When you're ready to start learning, it's £70 a month, billed monthly. Cancel any time and billing stops.