United Kingdom · Technology and data · Director/VP (16-20 years)

Director, Responsible AI & Governance

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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Experience bandDirector/VP (16-20 years)
Direct reports5-8 reports
Reports toChief Technology Officer (CTO)
UK framework levelUsually a director, accountable for a division and its numbers

Also advertised as VP of AI Ethics · Head of AI Trust & Safety · Director of Ethical AI · Chief AI Governance Officer

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

OTHM Level 7 Diploma in Artificial Intelligence OTHM Qualifications · Level 7 · covers 1 of 3 standards

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

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

The units you would start with

Ethics, Fairness and Explanation in Artificial Intelligence OTHM Level 7 Diploma in Artificial Intelligence

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

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

Frontier Fluency the next wave, beyond mainstream AI

Foresight Fluency seeing round the corner

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Your Plan Illustration

Built for Director, Responsible AI & Governance

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

Ethics, Fairness and Explanation in Artificial Intelligence OTHM Qualifications · covers 1 of 3 standards Level 7
AI Fluency for Managers and Leaders Chartered Management Institute · covers 1 of 3 standards Level 5
Artificial Intelligence NCC Education Limited · covers 1 of 3 standards Level 5
Introduction to Artificial Intelligence Qualifi Ltd · covers 1 of 3 standards Level 5
Management and Leadership for AI Chartered Management Institute · covers 1 of 3 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 Director, Responsible AI & Governance?

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

AI Policy Advocacy & External Engagement
Quantum Ethics & Future AI Systems

Why each one is rising

The future skills this job leans on

AI Fluencyworking with AI as a thinking partner
Data Fluencyturning numbers into a decision
AI Governance Fluencyusing AI responsibly
Frontier Fluencythe next wave, beyond mainstream AI
Foresight Fluencyseeing round the corner

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 Director, Responsible AI & Governance 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 involves shaping how a business builds and uses AI responsibly. You make sure AI systems do not cause harm, break regulations, or damage reputations.

4What you'd actually use

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

Python Libraries (e.g., AIF360, Fairlearn) Strategic

You won't be writing code, but you'll evaluate the utility, performance implications, and enterprise-wide adoption potential of different fairness and bias-detection libraries. You'll guide your team on which tools to use and why, understanding their strengths and weaknesses.

Explainable AI (XAI) Tools (e.g., SHAP, LIME) Strategic

You'll set the standards for model explainability required for different risk tiers across the business unit. You'll articulate the limitations of various XAI methods to executives and ensure your team is using the right tools for the job.

ML Observability Platforms (e.g., Fiddler AI, Arize AI) Architect

You'll lead the selection and enterprise-wide implementation of an ML observability platform for the business unit, defining core governance workflows and ensuring it integrates with our existing systems. You're building the infrastructure for ethical monitoring.

GRC & Governance Platforms (e.g., ServiceNow GRC, Archer) Strategic

You'll own the GRC module for AI within the business unit. This means using platforms like ServiceNow GRC or Archer to generate board-level risk reports, manage the entire AI model inventory, and ensure our controls are effective and auditable.

Collaboration Suite (e.g., Notion, Miro) Strategic

You'll use tools like Notion or Miro for strategic planning, roadmap development, and high-level programme management for the Responsible AI initiative. You'll be orchestrating complex projects and communicating progress across senior leadership.

Data Platforms (e.g., Databricks, Snowflake) Architect

You'll influence data governance policies at the platform level to embed fairness and privacy by design. This means working with Data Platform leads to ensure our data infrastructure supports ethical AI development from the ground up.

Board Reporting Tools (e.g., Diligent Boards, Tableau Server) Advanced

You'll create and present high-level risk dashboards and strategic updates in tools like Diligent Boards or Tableau Server, translating complex technical and ethical metrics into clear business impact for the C-suite and Board of Directors.

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 choice	Coming in	Where you are now	The step above
Strategic Direction for Responsible AI	Escalate all strategic questions to supervisor.	Propose solutions for specific project-level ethical challenges.	Make recommendations for workstream-level policy changes; consult Director on strategic pivots.
Budget Allocation & Resource Management	No budget authority; request resources from supervisor.	Estimate resource needs for individual tasks; request approval for minor expenses (£500).	Manage project budgets up to £10K; recommend tooling purchases.
Regulatory Compliance & Risk Mitigation	Report identified compliance gaps to supervisor.	Implement predefined controls for low-risk systems; propose minor risk mitigation strategies.	Design and implement controls for high-risk systems; make recommendations for policy updates to ensure compliance.
Team Management & Development	No direct reports; focus on personal development.	Informally mentor new joiners; provide peer feedback.	Formally mentor 1-2 junior analysts; assist with onboarding.

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.

Regulatory Compliance Score

Percentage of high-risk AI systems that are fully compliant with relevant regulations (e.g., EU AI Act, GDPR).

Target · Achieve 95% compliance for all high-risk AI systems within 18 months.

After your team's efforts, our Q4 audit shows 97% of our customer-facing AI models meet all EU AI Act requirements, up from 70% last year. That's a huge win for avoiding fines.

AI Ethics Incident Reduction

Year-over-year reduction in critical post-deployment ethical incidents (e.g., public bias complaints, data misuse allegations).

Target · Reduce critical incidents by 40% year-over-year.

Last year we had three major public complaints about algorithmic bias. This year, thanks to your programme, we've had zero. That's a clear 100% reduction, saving us millions in potential PR damage.

AI Governance Framework Adoption

Percentage of new AI projects that fully adopt the established AI Governance Framework (including AIAs, Model Cards, and Red Teaming).

Target · Achieve 90% adoption for all new AI projects from inception.

Every single one of the 15 new AI projects launched this quarter started with an AIA and a Model Card. That's a massive shift from just a year ago, showing real embedding of our processes.

Team Productivity & Efficiency

Average time to complete a Level 3 Algorithmic Impact Assessment (AIA) for a high-risk system, demonstrating process optimisation.

Target · Reduce average AIA completion time from 15 days to 10 days within 12 months.

Your team managed to streamline the AIA process, cutting the average turnaround time by 30%. This means we can get ethical reviews done faster without compromising quality, speeding up product launches.

Strategic Influence & Thought Leadership

Being seen as the go-to expert for AI ethics, both internally and externally, shaping the company's stance and practices.

You're regularly invited to C-suite strategy meetings to provide input on AI initiatives. You're asked to represent the company at industry forums or regulatory consultations. Legal and Product teams proactively seek your advice early in project lifecycles, not just at the end. You'll be presenting to the board, not just your line manager.

Organisational Culture Shift

Successfully embedding ethical considerations into the DNA of engineering and product development, moving beyond mere compliance.

Engineers are initiating discussions about fairness metrics in daily stand-ups without prompting. Product Managers are including ethical considerations in their initial requirements documents. There's a noticeable shift in language and behaviour across teams, showing that 'Responsible AI' isn't just a buzzword anymore, it's how we do things.

Talent Development & Retention

Building a high-performing, engaged AI ethics team and fostering internal talent.

Your direct reports are consistently hitting their development goals and expressing high job satisfaction in internal surveys. You've successfully mentored a Senior Specialist into a Manager role. We see low regrettable attrition within your team compared to industry averages.

Cross-Functional Collaboration & Trust

Establishing strong, collaborative relationships with key internal and external stakeholders, fostering trust and mutual respect.

You're viewed as a trusted partner by Legal, Engineering, and Product, not just a blocker. Other departments actively seek your team's input and expertise. You're successfully mediating disagreements between technical and legal teams, finding pragmatic solutions that everyone can agree on. External partners speak highly of our collaborative approach to AI ethics.

7Would you like it

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

What people enjoy

Making a Real-World Impact

You'll be leading initiatives that directly prevent harm, protect vulnerable groups, and build trust in technology. Seeing your policies prevent a discriminatory AI from going live, or hearing positive feedback from customers about our ethical stance, will be incredibly rewarding.

Successfully navigating a complex regulatory audit and receiving commendation for our proactive AI governance, knowing your work directly protected the company from significant fines and reputational damage.

Shaping the Future of AI

You're not just reacting to problems; you're actively defining how AI should be built and deployed in a responsible way. This means influencing product roadmaps, setting industry best practices, and contributing to the broader conversation around ethical AI.

Working with the CTO to define the 3-year Responsible AI strategy, which then gets presented to the board and becomes a core pillar of our product development philosophy.

Building and Leading High-Performing Teams

You'll be recruiting, mentoring, and developing a team of passionate AI ethics specialists. Watching them grow, take ownership, and deliver impactful work under your guidance will be a significant source of satisfaction.

Mentoring a Senior Specialist to become an AI Ethics Manager, empowering them to take on more leadership and seeing their team thrive under their direction.

What frustrates people

Being perceived as a blocker to innovation rather than an enabler of responsible innovation.
The constant need to educate and re-educate senior leadership on the nuances and long-term risks of AI ethics.
Resource constraints for ethical auditing and mitigation efforts, especially when competing with revenue-generating features.
The slow pace of change in large organisations, even when the ethical imperative is clear.
Navigating conflicting priorities between different business units or product lines regarding ethical standards.

What this role does not give you

A purely academic or theoretical environment – this is applied ethics in a commercial setting.
A role where you can avoid difficult conversations or confrontations with senior leaders.
A static, predictable environment – the field of AI ethics is constantly evolving.
A role focused solely on technical implementation; you'll be more on strategy and governance.

8Who you work with

This role directly shapes the ethical foundation and regulatory posture of our AI products and services. You'll be instrumental in mitigating significant financial, reputational, and legal risks. Your decisions will influence product roadmaps, engineering practices, and ultimately, our market position as a trustworthy AI provider. Honestly, you're the last line of defence before something goes really wrong.

Inside the business

Chief Technology Officer (CTO)
Chief Product Officer (CPO)
General Counsel & Legal Team
Heads of Engineering & Data Science
Business Unit VPs
Internal Audit & Risk Committees

Outside the business

Regulatory bodies (e.g., ICO, EU Commission)
Industry consortia & standards organisations
External auditors & legal counsel
Academic researchers in AI ethics
Key technology partners & vendors

9What you need before you start

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

At least 16 years of progressive experience in AI ethics, data governance, risk management, or a closely related technical field, with a significant portion in a leadership capacity.
Proven experience building and leading a team of technical specialists (minimum 5+ direct reports).
Demonstrable track record of designing and implementing enterprise-level governance frameworks or programmes.
Extensive experience presenting complex technical and ethical topics to C-suite executives and board members.
Deep understanding of machine learning principles, data science workflows, and software development lifecycles.
Strong familiarity with major AI ethics regulatory frameworks (e.g., EU AI Act, NIST AI RMF).

10What to practise next

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

Advanced Data Lineage & Provenance Systems

As AI systems become more complex and data sources proliferate, understanding the full history and transformations of data (data lineage) becomes paramount for auditing bias and ensuring data integrity. Regulators are increasingly demanding this transparency.

Metadata Management for AI · Immutable Data Ledgers · Automated Lineage Tracking · Data Provenance Auditing

This quarter: Review our current data lineage capabilities with the Data Platform team.
Next 6 months: Research leading data lineage tools and best practices specifically for AI/ML pipelines.
Next 12 months: Develop a proposal for enhancing our data lineage infrastructure to meet future regulatory demands.
Within 18 months: Oversee the pilot implementation of an improved data lineage system for a critical AI project.

Quick win: Schedule a deep dive with our Head of Data Engineering to understand their roadmap for data governance and lineage. Find out what's already in the works.

AI Model Security & Adversarial Robustness

AI models are increasingly targets for adversarial attacks, data poisoning, and model inversion. Ensuring the security and robustness of our AI systems against these threats is a critical ethical and business imperative, preventing misuse and maintaining integrity.

Adversarial Machine Learning · Robustness Testing · Model Security Auditing · Secure AI Development Practices

This quarter: Review our current cybersecurity practices as they apply to AI models with the CISO's team.
Next 6 months: Research best practices and emerging tools for AI model security and adversarial robustness.
Next 12 months: Develop a strategic plan for integrating AI security testing into our Red Teaming programme.
Within 18 months: Oversee the implementation of enhanced AI model security measures for our highest-risk systems.

Quick win: Collaborate with our security team to understand their current concerns regarding AI. There's likely already some overlap, and you can learn a lot from them.

11Staying current once you are in

What people here do to keep up

Regularly attend and present at leading AI ethics conferences (e.g., FAccT, AAAI/ACM AI Ethics and Society).
Publish articles or thought leadership pieces on responsible AI in industry journals or reputable platforms.
Participate in industry working groups or standards bodies focused on AI governance and ethics.
Engage in continuous learning through online courses, executive education programmes, or academic collaborations in emerging areas of AI ethics.
Mentor junior professionals in the field, helping to shape the next generation of AI ethicists.

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.

AI Policy Advocacy & External Engagement

Regulations are still being written, and public perception of AI is volatile. Companies that proactively engage with policymakers and shape the narrative will have a significant advantage. Simply reacting to new laws won't be enough; we need to be part of the conversation.

Regulatory Foresight
Public-Private Partnerships
Stakeholder Mapping (External)
Ethical Storytelling

Quantum Ethics & Future AI Systems

While still nascent, quantum computing and advanced AI architectures (e.g., AGI) will bring entirely new ethical dilemmas that current frameworks aren't equipped to handle. Proactive thinking here will position us as a leader, not a follower.

Quantum Machine Learning Ethics
Autonomous Systems Governance
Long-Term AI Safety
Neuro-Symbolic AI Ethics

13What you’ll use

What you’ll use

Skills this role draws on

Technical

Algorithmic Auditing & Bias Detection
Regulatory Framework Analysis & Interpretation
Algorithmic Impact Assessments (AIA) Design & Oversight
Red Teaming for AI Strategy
Privacy-Enhancing Technologies (PETs) Strategic Application
Explainable AI (XAI) Programme Development

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
From Principal Ethicist / AI Ethics Manager (L5)
3-5 years as an L5
Skills to master
- At L5, you'd have already managed a team and owned a significant product area's ethical strategy. To move to Director, you'd need to expand your scope to an entire business unit, demonstrate strong cross-functional influence at the VP level, and prove your ability to manage a larger budget and headcount. Strategic foresight and external advocacy become paramount.
You're ready to move on when
- Successfully led a major ethical programme from conception to implementation for a significant product line.
- Consistently received positive feedback from VPs and senior leaders on your strategic input and ability to influence.
- Mentored and developed at least two individuals into senior or management roles.
- Managed a budget of £1M+ and demonstrated sound financial stewardship.
2
From Head of Governance / Risk (Non-AI Specific)
5-7 years in a Head of Governance/Risk role, plus 3-5 years with AI focus
Skills to master
- You'd bring deep expertise in enterprise risk management, regulatory compliance, and governance frameworks. The gap to fill would be a deep technical understanding of AI/ML systems, specific AI ethics frameworks (e.g., EU AI Act), and the unique challenges of algorithmic bias. You'd need to quickly get up to speed on the technical nuances.
You're ready to move on when
- Successfully implemented a complex enterprise-wide governance framework for a regulated industry.
- Demonstrated ability to translate regulatory requirements into actionable business processes.
- Completed advanced certifications or courses in AI/ML fundamentals and AI ethics.
- Led a team responsible for managing significant regulatory or compliance risks.
3
From Senior Legal Counsel (Specialising in Tech/AI)
8-10 years as Senior Legal Counsel, plus 2-3 years in AI-specific roles
Skills to master
- You'd have an expert understanding of legal and regulatory landscapes, which is invaluable. The key development areas would be building and leading technical teams, understanding the practical implementation challenges of AI systems, and developing a more proactive, preventative approach to ethics rather than a purely reactive, legal one. You'd need to shift from advising on risk to owning the mitigation programme.
You're ready to move on when
- Successfully advised on complex legal matters related to AI deployment or data privacy.
- Demonstrated ability to work closely with engineering and product teams, understanding their technical constraints.
- Taken on leadership roles in cross-functional projects, even if not directly managing a team.
- Actively engaged with industry bodies or academic research in AI ethics and law.

15Where this role leads

The long view: This work can lead to shaping AI policy across a wider industry, or setting ethical standards at board level. It suits someone who wants technology built for good.

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 Director, Responsible AI & Governance is actually changing.

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 Ethics, Fairness and Explanation in Artificial Intelligence, worked against Director, Responsible AI & Governance.

Ethics, Fairness and Explanation in Artificial Intelligence Level 7

Applied to your work in Director, Responsible AI & Governance

1. To enable the learner to articulate the fundamental ethical dilemmas arising from advancements in artificial intelligence, drawing connections to relevant philosophical frameworks. 2. To enable the learner to critically evaluate the nuances of AI safety and AI alignment debates, considering diverse perspectives and proposed solutions. 3. To enable the learner to identify and explain various sources of bias present within machine learning algorithms and datasets. 4. To enable the learner to apply and interpret common metrics used to quantify bias in AI systems, demonstrating practical measurement skills. 5. To enable the learner to describe and compare different algorithmic fairness approaches designed to mitigate bias, selecting appropriate methods for specific scenarios. 6. To enable the learner to conduct empirical analysis, utilising relevant libraries and tools, to assess and address bias and fairness in machine learning models.

How the thinking builds

1 Remember
2 Understand
3 Apply
4 Analyse
5 Evaluate
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 Director, Responsible AI & Governance plan, free

See Your Progress Grow Illustration

Director, Responsible AI & Governance

Algorithmic Auditing & Bias Detection
Regulatory Framework Analysis & Interpretation
Algorithmic Impact Assessments (AIA) Design & Oversight
Red Teaming for AI Strategy
Privacy-Enhancing Technologies (PETs) Strategic Application
Explainable AI (XAI) Programme Development

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

Director, Responsible AI & Governance is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

VP of Trust & Responsible AI / Chief AI Ethics Officer (L7)
3-5 years in the Director role

From business unit leadership to enterprise-wide leadership, reporting to the CEO/Board.
- Defining enterprise-level AI ethics policies and standards.
- Leading major cross-company ethical transformation programmes.
- Managing relationships with top-tier regulators and government bodies.
- Overseeing the ethical implications of global product launches and market expansion.

Working with AI on the job

Working with AI

Where AI is starting to help

As a Director, your time is gold. You're not just doing the work; you're orchestrating it, setting the vision, and influencing at the highest levels. Imagine reclaiming significant chunks of your week by letting AI handle the heavy lifting of analysis, research, and even first drafts of critical documents. This isn't about replacing your strategic brain; it's about augmenting it.

In the fast-moving world of AI ethics and governance, staying ahead means using every tool at your disposal. Our internal AI Hub offers a suite of applications specifically designed to free up your team's time and amplify your strategic output. You'll be able to focus more on high-level decision-making, stakeholder engagement, and proactive risk management, rather than getting bogged down in the details.

Automated Policy-to-Code Scanning

Use large language models (LLMs) to automatically scan vast code repositories for deviations from our documented ethical policies. This flags potential issues like the use of prohibited data fields or a lack of required logging, catching problems before they become deeply embedded in our systems. Imagine the peace of mind knowing you're proactively checking millions of lines of code.

Bias Subgroup Discovery

Deploy unsupervised learning and clustering algorithms on model error logs to automatically identify and surface poorly-performing demographic or behavioural subgroups. This helps your team uncover hidden biases that weren't predefined in initial testing, allowing for targeted interventions and more equitable AI systems. It's like having an army of data detectives working for you 24/7.

Regulatory Synthesis & Q&A

Access an LLM trained specifically on the latest legal and regulatory documents, including the EU AI Act and NIST frameworks. Quickly get answers to complex questions ('What are the documentation requirements for a high-risk system?') or generate concise summaries for your technical and legal teams. This cuts down hours of legal research, letting you focus on strategic interpretation.

First-Draft Impact Assessments & Reports

Use generative AI to create structured first drafts of Algorithmic Impact Assessments (AIAs) or board-level risk reports based on project briefs and technical documentation. Your team can then audit, refine, and deepen these drafts, drastically reducing the time spent on initial content creation. It's a powerful way to accelerate your governance processes.

Common questions

How do you become a Director, Responsible AI & Governance?

Common routes in include From Principal Ethicist / AI Ethics Manager (3-5 years as an L5), From Head of Governance / Risk (Non-AI Specific) (5-7 years in a Head of Governance/Risk role, plus 3-5 years with AI focus) and From Senior Legal Counsel (Specialising in Tech/AI) (8-10 years as Senior Legal Counsel, plus 2-3 years in AI-specific roles). Times vary with prior experience.

Where can a Director, Responsible AI & Governance progress to?

This role can lead on to VP of Trust & Responsible AI / Chief AI Ethics Officer (3-5 years in the Director role), depending on the skills you build.

What new skills matter most for a Director, Responsible AI & Governance?

Increasingly, AI Policy Advocacy & External Engagement and Quantum Ethics & Future AI Systems. These are the skills our record of this role lists as growing.

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 Director, Responsible AI & Governance 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.

Director, Responsible AI & Governance

Where should we send it?

Two short quizzes about you

Will AI change your work as a Director, Responsible AI & Governance?

What's rising in its place

AI Policy Advocacy & External Engagement

Quantum Ethics & Future AI Systems

Skills this role draws on

Technical

How you actually get there, here

From Principal Ethicist / AI Ethics Manager (L5)

From Head of Governance / Risk (Non-AI Specific)

From Senior Legal Counsel (Specialising in Tech/AI)

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

Roles this leads to

One to one, on the work you already do

Everything else the record holds

The career path, and where it branches

VP of Trust & Responsible AI / Chief AI Ethics Officer (L7)

Where AI is starting to help

Automated Policy-to-Code Scanning

Bias Subgroup Discovery

Regulatory Synthesis & Q&A

First-Draft Impact Assessments & Reports

Common questions

Want a read on where you stand?