UK

United Kingdom · Technology and data · Lead (8-12 years)

Lead AI Ethics Strategist

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.

Start my Lead AI Ethics Strategist plan, free

Free to start: a plan built for this role, and a Future Fluency module to try first. No card.

Keep this job description

Where should we send it?

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.

Upskilling a team in this role? Talk to us

  • Experience bandLead (8-12 years)
  • Direct reports3-8 reports
  • Reports toDirector, Responsible AI
  • UK framework levelUsually a manager, or the deepest specialist in a team

Also advertised as Principal Responsible AI Advisor · AI Governance Architect · Senior AI Risk Specialist (Technical) · Head of AI Ethics Operations

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

CMI Level 5 Diploma in Leading AI Transformation Chartered Management Institute · Level 5 · covers 1 of 3 standards
NCC Education Level 5 Extended Diploma in Computing with Data Science NCC Education Limited · Level 5 · covers 1 of 3 standards
CMI Level 5 Certificate in Leading AI Transformation Chartered Management Institute · Level 5 · covers 1 of 3 standards
Qualifi Level 5 Extended Diploma in Computer Science Qualifi Ltd · Level 5 · covers 1 of 3 standards
CMI Level 5 Award in Leading AI Transformation Chartered Management Institute · Level 5 · covers 1 of 3 standards
LRN Level 3 Award in Artificial Intelligence Competence Learning Resource Network · Level 3 · covers 2 of 3 standards

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

The units you would start with

AI Fluency for Managers and Leaders CMI Level 5 Diploma in Leading AI Transformation
Artificial Intelligence NCC Education Level 5 Extended Diploma in Computing with Data Science
Introduction to Artificial Intelligence Qualifi Level 5 Extended Diploma in Computer Science
Management and Leadership for AI CMI Level 5 Award in Leading AI Transformation
Artificial Intelligence Project Design & Communication LRN Level 3 Award in Artificial Intelligence Competence

The future skills this job leans on

AI Fluency working with AI as a thinking partner
Data Fluency turning numbers into a decision
AI Governance Fluency using AI responsibly
Systems Fluency seeing the whole picture
Start my Lead AI Ethics Strategist plan, free
Your Plan Illustration

Built for Lead AI Ethics Strategist

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

  1. AI Fluency for Managers and Leaders Chartered Management Institute · covers 1 of 3 standards Level 5
  2. Artificial Intelligence NCC Education Limited · covers 1 of 3 standards Level 5
  3. Introduction to Artificial Intelligence Qualifi Ltd · covers 1 of 3 standards Level 5
  4. Management and Leadership for AI Chartered Management Institute · covers 1 of 3 standards Level 5
  5. Artificial Intelligence Project Design & Communication Learning Resource Network · covers 2 of 3 standards Level 3
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 Lead AI Ethics Strategist?

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

  • Advanced Prompt Engineering & LLM Governance
  • Socio-Technical System Design for AI
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 Lead AI Ethics Strategist 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.

Start my Lead AI Ethics Strategist plan, free Ready to pay? Subscribe for £70 a month

3What this role really is

This job designs and improves how AI ethics works in practice. It involves building the systems and processes that catch problems before they happen. The work covers fairness, transparency and compliance in AI systems, from early design through to deployment. It means translating regulations into steps engineers can follow, and checking those steps are followed.

4What you'd actually use

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

OneTrust AI Governance / ServiceNow GRC Advanced

Designing and configuring AI risk assessment workflows, control libraries, and policy enforcement mechanisms within the platform. You'll manage the platform for a business unit and ensure its effective use.

Fiddler AI / Arthur AI (Model Explainability & Monitoring) Advanced

Directly using these platforms to conduct deep-dive investigations into model drift, bias alerts, and explainability reports. You'll be setting the standards for how these tools are used for continuous monitoring.

Collibra / Alation (Data Governance & Lineage) Expert

Acting as a key data steward, curating business glossaries for AI-relevant data, validating critical data elements, and using lineage tools to map potential bias propagation pathways in our data pipelines. You'll influence data quality frameworks.

Confluence / Jira / Miro (Collaboration & Documentation) Expert

Designing the Confluence knowledge base structure for responsible AI, creating complex Jira workflows for ethical incident response and remediation, and facilitating workshops with Miro for process design and problem-solving.

AWS SageMaker Clarify / Azure ML Responsible AI Dashboard / GCP Explainable AI Intermediate

Navigating these cloud platforms to review model configurations, audit trails, and responsible AI dashboards directly. You'll be able to interpret their outputs and ensure they align with our governance standards.

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
AI Ethics Process Design Follows established processes; flags potential improvements. Proposes minor improvements to existing workflows; adapts processes for specific projects. Leads the design of new process modules; makes significant improvements to core workflows; consults on overall process architecture.
Risk Assessment & Mitigation Strategy Executes predefined risk assessments; identifies basic risks; suggests standard mitigations. Conducts independent risk assessments for specific products; proposes tailored mitigation strategies for routine risks. Leads complex risk assessments for high-risk systems; designs novel mitigation approaches; makes recommendations to product leadership.
Tool & Platform Selection Uses assigned tools (e.g., OneTrust) for data entry and reporting. Configures existing tools for specific project needs; troubleshoots basic tool issues. Evaluates new features within existing tools; recommends specific tool configurations for complex scenarios; influences tool roadmap.
Team & Talent Development Learns from senior team members; participates in peer reviews. Informally guides new joiners; provides peer feedback on work. Mentors 0-2 junior specialists; conducts code reviews; helps unstick team members from technical challenges.

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.

AI Ethics Process Adoption Rate
Percentage of new AI models or features that follow the established AI ethics review process from conception to deployment.
Target · Achieve >90% adoption for all high-risk models within 12 months.

In Q3, 18 out of 20 new high-risk AI features went through the full ethics review, hitting 90%. We'd then look at why the other two didn't.

Reduction in High-Severity AI Ethics Risks
Year-over-year decrease in the number of 'high' or 'critical' risks identified during pre-deployment reviews that actually make it to production.
Target · Demonstrate a 25% year-over-year reduction.

Last year, 12 high-severity risks were flagged and deployed. This year, we aim for that number to be 9 or fewer, showing our processes are working.

Model Card & Datasheet Completeness
Percentage of new models launched with a complete and accurate Model Card or Datasheet, adhering to our internal standards.
Target · >90% of new models launched with complete documentation within 6 months of policy rollout.

Out of 10 models launched last month, 9 had fully compliant Model Cards, showing good adherence to the new policy you helped design.

Team Mentorship & Development
Successful progression of junior team members under your guidance.
Target · Successfully mentor at least one L2 Specialist to promotion within a 2-year period.

Your L2 report, Sarah, was promoted to L3 after 18 months, largely due to your structured guidance on complex risk assessments.

Influence & Engagement with Engineering/Product
Being seen as a trusted advisor, not just a blocker, by technical teams, leading to proactive engagement on ethical considerations.
  • You're invited to early-stage design discussions for new AI products. Engineering leads proactively seek your input before major architectural decisions. You regularly contribute to technical design documents with ethical considerations.
Process Improvement & Innovation
Your ability to continuously identify bottlenecks and improve our AI ethics governance processes, making them more efficient and effective.
  • You've proposed and implemented at least two significant improvements to our risk assessment workflows in the last year. Your process changes lead to measurable reductions in review time without compromising rigour. You're regularly sharing best practices with peers.
Regulatory Foresight & Translation
Your ability to anticipate upcoming regulatory changes and translate them into practical, actionable requirements for our internal teams.
  • You've presented proactive briefings on emerging AI regulations (e.g., EU AI Act updates) to leadership. Product teams are implementing changes based on your interpretations before official deadlines. Legal team regularly consults you on technical implications of new laws.
Quality of Strategic Guidance
The clarity, practicality, and impact of your recommendations on complex ethical dilemmas and strategic AI initiatives.
  • Your recommendations are consistently adopted by senior leadership. You provide clear, well-reasoned analyses of trade-offs. Your advice helps shape the ethical roadmap for major product lines.

7Would you like it

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

What people enjoy
Making a Tangible Ethical Impact

You'll feel a real sense of purpose knowing your work directly prevents harm, builds fairer systems, and contributes to a more trustworthy technological landscape. Seeing your designed process actually catch a potential bias before launch will be incredibly rewarding.

Stopping a new feature from launching after your process identified a significant fairness issue, then working with the team to re-engineer it ethically.

Solving Complex, Uncharted Problems

The AI ethics space is still relatively new, and there aren't always clear answers. You'll thrive on the intellectual challenge of taking ambiguous regulations or novel AI risks and designing practical, scalable solutions. It's like being a pioneer.

Developing our first internal framework for assessing the human rights impact of generative AI, where no established blueprint exists.

Building & Improving Systems

If you love taking something messy and making it organised, efficient, and robust, you'll love this. You'll get to design workflows, build governance structures, and see your architectural decisions improve how the entire organisation manages AI risk.

Implementing a new, automated workflow in OneTrust AI Governance that reduces the time to complete a high-risk assessment by 30%.

What frustrates people
  • The 'Post-Hoc Sanity Check': Being brought in at the 11th hour to 'ethically bless' a nearly-finished product, making any substantive change politically and technically impossible.
  • Regulatory Whiplash: Trying to build a stable, long-term internal governance framework while the global regulatory landscape shifts under your feet every quarter.
  • Arguing with Math: The exhaustion of explaining to brilliant technical minds that a mathematically optimal solution can still be an ethically catastrophic one.
  • Lacking Enforcement Teeth: Identifying a critical, high-severity risk but having to rely solely on influence and persuasion to stop a launch, with no formal veto power.
  • The Culture Clash: Championing deliberation, caution, and documentation in an engineering culture that often idolises speed, iteration, and shipping code.
What this role does not give you
  • A quiet, predictable routine: Expect constant shifts in priorities and new, unexpected ethical dilemmas.
  • Immediate gratification: Building robust governance takes time, patience, and persistence; wins are often hard-won and incremental.
  • Direct authority over engineering decisions: You'll influence, advise, and guide, but rarely make the final technical call on product features.
  • A purely technical role: You'll be dealing with people, politics, and persuasion just as much as code and models.

8Who you work with

This role directly shapes the ethical posture and regulatory compliance of our AI products across the entire organisation. You'll be instrumental in embedding responsible AI principles into our development lifecycle, reducing enterprise-level risks, and building a foundation for trustworthy AI innovation. Your work ensures we meet our legal obligations and maintain public trust, which, frankly, is invaluable.

Inside the business
  • Product Leadership (VPs & Directors)
  • Engineering Leads & Architects
  • Legal & Compliance Teams
  • Data Science & Machine Learning Teams
  • Internal Audit
Outside the business
  • Regulatory Bodies (e.g., ICO, EU AI Act authorities)
  • Industry Standards Organisations
  • External Auditors and Consultants
  • Academic Research Partners

9What you need before you start

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

  • Proven experience (8+ years) in designing, implementing, and managing AI ethics, responsible AI, or AI governance programmes within a technical organisation.
  • Demonstrable experience in translating complex legal or ethical principles into actionable technical requirements and organisational processes.
  • Strong understanding of the entire machine learning lifecycle, from data ingestion to model deployment and monitoring.
  • Experience leading investigations into AI-related incidents or bias findings, including root cause analysis and remediation planning.
  • A track record of successfully influencing senior technical and business stakeholders to adopt new policies or change existing practices.
  • Experience managing or mentoring a small team of technical specialists.

10What to practise next

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

Enterprise AI Governance Architecture

As AI adoption grows, our governance needs to scale. You'll be thinking about how all our tools (GRC, explainability, data lineage) integrate into a cohesive, auditable system across multiple cloud environments and business units. It's about building the 'operating system' for responsible AI.

Integrated GRC Toolchains · Federated Governance Models · Automated Policy Enforcement · Auditability & Traceability at Scale

  • This week: Review our current MLOps architecture and identify key governance integration points.
  • This month: Map out the data flow and decision points for a high-risk AI system, identifying where governance could be automated.
  • Month 2: Research enterprise-scale AI governance platforms and their integration capabilities.
  • Month 3: Draft a proposal for an integrated AI governance toolchain, outlining its benefits and implementation challenges.

Quick win: Start thinking about 'how does this ethical control get enforced automatically?' rather than 'how do we manually check this?'

11Staying current once you are in

What people here do to keep up
  • Actively participate in industry working groups or consortia focused on AI ethics and governance (e.g., Partnership on AI, IEEE).
  • Regularly attend conferences and webinars on emerging AI technologies, regulatory updates, and ethical best practices.
  • Contribute to internal knowledge sharing sessions, presenting on new ethical challenges or solutions.
  • Engage in continuous learning through online courses or specialised programmes in advanced AI ethics, socio-technical systems, or regulatory compliance.

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.

Advanced Prompt Engineering & LLM Governance

Generative AI and Large Language Models (LLMs) are changing how we build and interact with AI. Your role will shift from governing traditional ML models to also governing the inputs and outputs of these powerful, often opaque, systems. Understanding how to 'steer' them ethically and mitigate their unique risks (e.g., hallucination, data leakage) is paramount.

  • Context Windows & Token Limits
  • RAG Architectures for Ethical Data Sourcing
  • Output Validation & Hallucination Detection
  • Prompt Chaining & Agentic AI Governance

Socio-Technical System Design for AI

We're moving beyond just technical model ethics to understanding the broader human and organisational systems that AI operates within. Your role will increasingly involve designing not just technical controls, but also the human processes, feedback loops, and organisational structures that ensure ethical outcomes.

  • Human-on-the-Loop (HOTL) System Design
  • Organisational Ethics Infrastructure
  • Co-design & Participatory Methods
  • Ethical Debt Management

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • AI Risk Management Frameworks
  • Bias & Fairness Auditing (Methodology Design)
  • Regulatory Translation & Implementation
  • Stakeholder & Human Rights Impact Assessments (Design)
  • Applied Ethical Reasoning & Trade-offs

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

    Senior AI Ethics Specialist (L3) internal promotion

    Roughly 2-3 years at the Senior level.

    Skills to master

    • Deep expertise in leading complex ethical investigations, strong influence skills across multiple teams, and a proven ability to mentor junior colleagues. You'd have already started thinking about process improvements.

    You're ready to move on when

    • You're regularly consulted by peers and managers for complex ethical dilemmas.
    • You've successfully led at least two major ethical remediation efforts from start to finish.
    • You've proactively identified and proposed significant improvements to our existing AI ethics processes.
    • You've taken on informal mentorship roles and helped junior team members grow.
  2. 2

    Technical Lead / Architect (Data Science/ML Engineering) from another company

    Typically 8-12 years in technical roles, with a recent shift towards governance or ethical considerations.

    Skills to master

    • A deep understanding of MLOps and AI system architecture, combined with a strong interest and foundational knowledge in AI ethics. You'd need to quickly get up to speed on regulatory frameworks and ethical theory.

    You're ready to move on when

    • You've designed and implemented complex ML systems in production.
    • You've actively considered and mitigated ethical risks in your previous technical roles.
    • You're passionate about moving into a dedicated AI ethics role and have done significant self-study.
    • You have experience leading technical teams and driving architectural decisions.
  3. 3

    AI Governance Consultant from a Big Four firm

    Roughly 5-8 years in AI governance or risk consulting.

    Skills to master

    • Strong client-facing skills, experience in designing governance frameworks for multiple organisations, and a broad understanding of regulatory landscapes. You'd need to adapt to our specific internal culture and technical stack.

    You're ready to move on when

    • You've led engagements focused on AI risk management and compliance.
    • You're adept at translating regulatory requirements into actionable business processes.
    • You have experience presenting to and influencing senior client stakeholders.
    • You're eager to move from an advisory role to an 'in-house' builder and owner of governance.

15Where this role leads

The long view: This work can lead to senior AI governance roles, such as Director of Responsible AI or Chief AI Ethics Officer.

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 Lead AI Ethics Strategist is actually changing.

Where it leads

Roles this leads to

The record names a next step, but the catalogue has no page for it yet:

  • Principal Ethicist / Manager, Responsible AI (L5)
  • Lead AI Ethics Architect (Individual Contributor track)

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 AI Fluency for Managers and Leaders, worked against Lead AI Ethics Strategist.

AI Fluency for Managers and Leaders Level 5

Applied to your work in Lead AI Ethics Strategist

By completing this unit, learners will know how to evaluate and recommend AI solutions for operational needs. Learners will also be able to make informed judgements about the reliability and accountability of AI systems.

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 Lead AI Ethics Strategist plan, free
See Your Progress Grow Illustration
Lead AI Ethics Strategist
  • AI Risk Management Frameworks
  • Bias & Fairness Auditing (Methodology Design)
  • Regulatory Translation & Implementation
  • Stakeholder & Human Rights Impact Assessments (Design)
  • Applied Ethical Reasoning & Trade-offs
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

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

  1. Principal Ethicist / Manager, Responsible AI (L5)

    Approximately 3-5 years in the Lead AI Ethics Strategist role.

    This is a step into direct people management and setting the ethical strategy for a major business unit or a critical enterprise-wide initiative. You'd own a larger scope and manage managers.

    • Enterprise Risk Management Integration Integrating AI ethics risks into the broader enterprise risk framework.
    • External Representation Representing the organisation in industry forums or regulatory discussions.
    • Advanced Policy Development Drafting and owning high-level, company-wide AI ethics policies.

  2. Lead AI Ethics Architect (Individual Contributor track)

    Approximately 3-5 years in the Lead AI Ethics Strategist role.

    This pathway deepens your technical expertise and architectural influence without taking on direct people management. You'd become the ultimate technical authority on AI ethics systems.

    • Cloud AI Governance Architectures Designing and overseeing the implementation of responsible AI controls within complex multi-cloud environments.
    • Automated Compliance Engineering Building tools and frameworks that automatically enforce ethical policies within CI/CD pipelines.
    • Advanced Model Debugging & Explainability Developing novel techniques for understanding and mitigating complex model behaviours.
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, the sheer volume of regulations, technical documentation, and ethical considerations can be overwhelming. But what if AI could help you cut through the noise, automate the tedious bits, and free you up to focus on the truly strategic, human-centric challenges? It can.

As a Lead AI Ethics Strategist, your time is best spent designing robust processes and tackling complex, nuanced problems. We're not talking about replacing your judgment, but augmenting your capabilities. Imagine offloading the grunt work to AI, allowing you to focus on the 'why' and the 'how' of ethical AI.

Automated Policy & Regulatory Scanning

Use a specialised Large Language Model (LLM) to automatically cross-reference our internal AI model documentation and design specifications against the latest internal policies and external regulations (like the EU AI Act). It'll flag non-compliance, missing evidence, or high-risk language in seconds, saving you hours of manual review. You'll then focus on the nuanced interpretations.

Unsupervised Bias Discovery & Anomaly Detection

Instead of just testing for known biases, apply advanced clustering algorithms to model error logs and performance metrics. This helps you automatically surface previously unknown subgroups where a model is underperforming or exhibiting disparate impact. It's about proactively discovering novel failure modes, letting you focus your deep-dive investigations where they're most needed.

Continuous Threat Synthesis for Foresight

Deploy a Retrieval-Augmented Generation (RAG) system that constantly ingests new AI regulations, academic papers on emerging risks, and public AI failure incidents. You'll get daily, synthesised briefs on evolving threats and best practices, allowing you to update our policies and processes proactively, staying ahead of the curve without drowning in information.

Multi-Audience Report Generation

Take a single, comprehensive technical audit report and, with the help of generative AI, automatically draft multiple tailored versions. This includes a concise executive summary for leadership, a detailed remediation plan with code snippets for engineers, and a non-technical explanation for the legal and communications teams. This ensures everyone gets the information they need, in the format they understand, much faster.

Common questions

Common questions

How do you become a Lead AI Ethics Strategist?

Common routes in include Senior AI Ethics Specialist internal promotion (Roughly 2-3 years at the Senior level.), Technical Lead / Architect (Data Science/ML Engineering) from another company (Typically 8-12 years in technical roles, with a recent shift towards governance or ethical considerations.) and AI Governance Consultant from a Big Four firm (Roughly 5-8 years in AI governance or risk consulting.). Times vary with prior experience.

Where can a Lead AI Ethics Strategist progress to?

This role can lead on to Principal Ethicist / Manager, Responsible AI (Approximately 3-5 years in the Lead AI Ethics Strategist role.) and Lead AI Ethics Architect (Individual Contributor track) (Approximately 3-5 years in the Lead AI Ethics Strategist role.), depending on the skills you build.

What new skills matter most for a Lead AI Ethics Strategist?

Increasingly, Advanced Prompt Engineering & LLM Governance and Socio-Technical System Design for AI. 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 technology and data

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

The skills involved transfer to other regulated industries such as finance and healthcare. They can also lead to work in AI ethics consulting, or with policy-making bodies.

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 Lead AI Ethics Strategist 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.