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

Director, AI Ethics & 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 reports5-10 reports
Reports toChief Technology Officer (CTO)
UK framework levelUsually a director, accountable for a division and its numbers

Also advertised as VP, Responsible AI · Head of AI Trust & Safety · Chief Ethicist (Technical) · Global Director, AI Risk & Compliance

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

Foresight Fluency seeing round the corner

Systems Fluency seeing the whole picture

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Your Plan Illustration

Built for Director, AI Ethics & 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, AI Ethics & 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 Geopolitics & International Standards Leadership
AI Incident Response & Forensics Leadership

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
Foresight Fluencyseeing round the corner
Systems Fluencyseeing the whole picture

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, AI Ethics & 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 role sets out how AI is built and used, weighing up the ethical risks and turning them into clear policy. Decisions here affect an organisation's reputation and its standing with regulators.

4What you'd actually use

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

GRC & Privacy Platforms (OneTrust, ServiceNow GRC) Strategic

Using the platform for enterprise-level reporting to regulators, defining control libraries, and overseeing the configuration of assessment templates for the entire organisation.

Data Governance & Cataloging (Collibra, Alation) Strategic

Setting enterprise-wide data classification policies, ensuring proper data lineage documentation, and defining data stewardship roles within the tool to support ethical AI practices.

Model Explainability & Fairness Toolkits (Python w/ SHAP, LIME, Fairlearn) Strategic

Understanding the capabilities and limitations of these tools to set technical standards for model transparency and fairness, guiding your team on their appropriate application and interpretation of outputs.

Collaboration & Documentation (Jira, Confluence, Microsoft Teams) Advanced

Managing the overall AI ethics programme backlog, designing and overseeing review workflows, creating executive reporting dashboards, and ensuring comprehensive, accessible documentation for the entire function.

BI & Reporting Dashboards (Tableau, Power BI) Advanced

Defining the key ethical AI KPIs for executive dashboards, overseeing their design and implementation, and using them to monitor enterprise-wide AI risk and compliance status.

Enterprise Data Platforms (Databricks, Snowflake, Azure ML) Architectural

Advising on the implementation of ethical guardrails and governance controls at the platform level, ensuring our core data and ML infrastructure supports responsible AI by design.

Board Reporting Software (Diligent, BoardVantage) Expert

Preparing, reviewing, and presenting critical AI risk and governance materials directly to the Board of Directors and executive leadership team.

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
AI Product Launch Approval (High Risk)	Escalate to Senior Specialist for review and recommendation.	Provide initial risk assessment and propose mitigations to Lead Ethicist.	Make a clear 'go/no-go' recommendation to Director, with detailed risk/mitigation analysis.
New AI Ethics Policy Introduction	Provide research support on existing standards.	Draft sections of policy based on established templates.	Design and lead the drafting of new policy, gaining cross-functional input.

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 Policy Compliance Rate

Percentage of relevant technical teams and projects adhering to mandatory AI ethics policies and guidelines.

Target · 98% compliance across all Tier-1 AI projects and relevant technical staff.

Achieving 99% completion of mandatory AI ethics training for all new technical hires in Q4, and internal audits showing only 1% non-compliance in high-risk project documentation.

Board AI Governance Confidence Score

The rating assigned by the Board of Directors on the effectiveness of our AI governance and risk management framework.

Target · Maintain 'High Confidence' or 'Green' status on the quarterly enterprise risk dashboard presented to the Board.

Presenting a clear, comprehensive AI risk report to the Board in Q2 that results in their unanimous endorsement of our current strategy and a 'Green' rating for AI governance.

Strategic Responsible AI Integration

Number of major business units that have successfully embedded measurable responsible AI objectives into their annual strategic plans.

Target · Embed measurable responsible AI objectives into the annual plans of at least 3 major business units within 12 months.

Working with the Retail and Financial Services business units to include 'reduce algorithmic bias in credit scoring by X%' and 'improve transparency of product recommendations by Y%' as key objectives for the next fiscal year.

Significant Regulatory Fines Avoided

The absence of any material fines or penalties related to AI ethics, data bias, or non-compliance with AI-specific regulations.

Target · Zero significant regulatory fines or public sanctions related to AI ethics.

Successfully navigating a new EU AI Act audit without any major findings or penalties, saving the company potential fines of £5M+.

External Reputation & Thought Leadership

Our company's standing as a recognised leader and trusted voice in the responsible AI space, influencing industry standards.

Regular invitations to speak at major industry conferences, citations in reputable publications, active participation in policy discussions with regulatory bodies, positive media coverage on our AI ethics initiatives, and our ability to attract top talent in the field.

C-Suite & Executive Trust

The degree to which the executive leadership team proactively seeks your counsel and integrates your recommendations into strategic decision-making.

Being consistently included in early-stage strategic planning sessions for new AI initiatives, executive sponsorship for AI ethics programmes, direct requests for your input on high-profile AI-related issues, and the visible adoption of your advice in public statements or product roadmaps.

Culture of Responsible Innovation

The extent to which AI ethics is genuinely embedded into our product development lifecycle, moving beyond mere compliance to proactive ethical design.

Product and engineering teams initiating AI Impact Assessments early in the design phase without prompting, internal 'champions' for responsible AI emerging across departments, a noticeable shift in how teams discuss ethical considerations (e.g., 'What are the unintended consequences?' rather than 'Is this legal?'), and robust internal challenge mechanisms for ethical concerns.

7Would you like it

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

What people enjoy

Shaping Industry Standards

You'll spend time researching emerging regulatory frameworks, engaging with industry consortia, and actively contributing to discussions that will define the future of AI governance. You're driven by the idea of setting the benchmark for responsible AI, not just following it.

Leading our company's submission to a government consultation on AI regulation, or presenting our internal AI ethics framework at a global tech conference.

Preventing Real-World Harm

The thought of an AI system causing unintended harm keeps you up at night (in a good way, mostly). You're motivated by the tangible impact of your work in protecting vulnerable groups, ensuring fairness, and building systems that genuinely serve humanity. This isn't abstract for you; it's deeply personal.

Successfully stopping the deployment of a new feature after an AI Impact Assessment revealed a high risk of discrimination against a protected group, then working with the team to redesign it responsibly.

Building Organisational Trust

You believe that trust is our most valuable asset. You're driven to build robust governance structures, transparent processes, and a culture where ethical considerations are as important as technical performance. You want our customers, employees, and regulators to genuinely trust our AI.

Developing and rolling out an enterprise-wide 'Model Card' standard, ensuring every deployed AI model has clear documentation on its purpose, limitations, and performance metrics, thereby increasing internal and external transparency.

What frustrates people

Being seen as a roadblock rather than an enabler of innovation.
Recommendations being deprioritised due to short-term commercial pressures.
The constant struggle to quantify the preventative value of ethical governance.
Explaining complex sociotechnical issues to those who prefer simple technical fixes.
Navigating rapidly changing and often conflicting global AI regulations.

What this role does not give you

A predictable, stable regulatory environment.
Unquestioning acceptance of your recommendations without significant persuasion.
A clear, easy-to-quantify ROI for all your initiatives.
A role where you're primarily hands-on coding or building models.
A quiet, low-pressure environment.

8Who you work with

This role directly shapes our enterprise-wide AI strategy, influencing product development, market positioning, and our overall risk profile. Your leadership will define our reputation as a responsible AI innovator, significantly impacting customer acquisition, investor confidence, and talent retention. Frankly, you're building the guardrails for our future growth.

Inside the business

Chief Technology Officer (CTO)
Chief Legal Officer (CLO)
Chief Risk Officer (CRO)
Heads of Product & Engineering
Data Science & Machine Learning Leads
Internal Audit & Compliance Teams
Executive Leadership Team (ELT)
Board of Directors

Outside the business

Regulatory Bodies (e.g., ICO, EU Commission)
Industry Consortia & Standards Organisations
External Auditors & Legal Counsel
Academic & Research Institutions
Key Technology Partners & Vendors
Public & Media (in crisis situations)

9What you need before you start

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

Extensive experience (10+ years) leading AI ethics, governance, or responsible technology programmes in a large, complex technical organisation.
Proven track record of influencing C-suite and Board-level stakeholders on strategic technology and risk issues.
Demonstrable experience building and managing high-performing teams, including managers and principal-level individual contributors.
Deep understanding of the technical lifecycle of AI/ML models, from research to deployment and monitoring.
Experience navigating complex regulatory environments and translating legal requirements into actionable technical and process changes.
A strong public profile or demonstrable experience representing an organisation externally on sensitive technical or ethical topics.

10What to practise next

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

Explainable AI (XAI) for Non-Technical Audiences

Regulators, customers, and board members increasingly demand transparency from AI systems. You'll need to guide your teams on how to build XAI features and, crucially, how to translate complex XAI concepts into clear, understandable explanations for non-technical stakeholders.

Global vs. Local Explanations · Counterfactual Explanations · Audience-Specific Explanations · Limitations of XAI

This quarter: Have your team present a 'deep dive' on a specific XAI technique (e.g., SHAP) and its application to one of our products.
Next 6 months: Work with Product and UX teams to design user-facing explanations for an AI feature.
Next 12 months: Develop internal guidelines for 'Board-ready' XAI explanations.
Ongoing: Read academic papers and industry reports on the latest in XAI and its practical applications.

Quick win: Challenge your team to explain a complex model's decision to you as if you were a regulator, using only plain language and simple visuals.

AI Governance in Multi-Cloud & Hybrid Environments

Our AI systems aren't confined to a single cloud provider or on-premise infrastructure. Managing ethical risks, data sovereignty, and compliance across diverse, distributed AI deployments—often involving multiple vendors—adds significant complexity to governance.

Data Lineage & Provenance Across Clouds · Model Deployment & Monitoring Consistency · Vendor Risk Management for AI Services · Decentralised AI & Federated Learning Ethics

This quarter: Map out our current AI deployments across different cloud providers and identify potential governance gaps.
Next 6 months: Develop a 'vendor risk assessment' framework specifically for third-party AI services.
Next 12 months: Work with our Cloud Architecture team to embed ethical controls into our multi-cloud deployment pipelines.
Ongoing: Attend workshops or webinars on cloud governance best practices, with a focus on AI.

Quick win: Review the terms and conditions of our major cloud providers for their stance on AI ethics and data usage, and discuss with Legal.

11Staying current once you are in

What people here do to keep up

Active participation in relevant industry consortia (e.g., Partnership on AI, Responsible AI Institute) and standards bodies (e.g., IEEE, ISO).
Regularly attending and speaking at major AI ethics, governance, or responsible technology conferences.
Publishing thought leadership articles or whitepapers on emerging AI ethics challenges and solutions.
Mentoring junior talent within the AI ethics and technical communities.
Engaging with academic research and collaborating on projects at the intersection of AI, ethics, and society.

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 Geopolitics & International Standards Leadership

The 'AI race' is increasingly a geopolitical one, with different regions (EU, US, China) developing divergent regulatory approaches and ethical norms. As a global company, navigating these conflicting standards and influencing their development will be critical for market access and reputation.

Regulatory Harmonisation vs. Divergence
Digital Sovereignty & Data Localisation
International Standards Bodies (e.g., ISO, IEEE)
Ethical Diplomacy

AI Incident Response & Forensics Leadership

As AI systems become more complex and pervasive, incidents of unintended harm, bias, or misuse are inevitable. Leading the rapid, transparent, and effective response to such incidents—from technical root cause analysis to public communication—will be a defining leadership challenge.

AI Incident Classification & Severity
Root Cause Analysis for Algorithmic Failures
Crisis Communications & Public Relations
Post-Incident Learning & Remediation

13What you’ll use

What you’ll use

Skills this role draws on

Technical

Responsible AI Frameworks & Operationalisation
Sociotechnical Systems Analysis (Enterprise-scale)
Algorithmic Auditing & Bias Mitigation (Strategic Oversight)
Ethical Risk Assessment & Triage (Enterprise Program Design)
Policy Drafting & Governance Implementation (Enterprise-wide)
Stakeholder Deliberation & Conflict Resolution (Executive Level)

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
Principal Ethicist / AI Ethics Lead (L4)
3-5 years at L4
Skills to master
- Architecting end-to-end ethics review frameworks, managing cross-functional programmes, and influencing senior stakeholders on specific technical ethics issues.
You're ready to move on when
- Successfully led the implementation of a major new AI ethics programme across multiple product lines.
- Consistently provided strategic guidance that prevented significant ethical incidents or regulatory issues.
- Built a strong reputation for pragmatic problem-solving and effective stakeholder management.
- Demonstrated ability to mentor and indirectly lead junior team members.
2
Manager, AI Ethics & Governance (L5)
2-4 years at L5
Skills to master
- Managing a team of ethics specialists, owning a significant budget, and acting as the primary advisor to product VPs on ethical strategy and risk.
You're ready to move on when
- Successfully managed and developed a high-performing team of AI ethics professionals.
- Consistently delivered on departmental objectives within budget and scope.
- Proven ability to influence executive-level product and engineering decisions.
- Demonstrated leadership in navigating complex ethical dilemmas and driving consensus.
3
Senior Legal Counsel (AI Focus) or Chief Risk Officer (with AI Specialism)
5-8 years in a senior legal/risk role with heavy AI focus
Skills to master
- Deep understanding of AI-specific legal and regulatory frameworks, enterprise-wide risk management, and translating legal requirements into operational controls. You'd need to build out your technical understanding of AI systems considerably.
You're ready to move on when
- Successfully advised on complex AI-related litigation or regulatory investigations.
- Developed and implemented enterprise-wide AI risk assessment methodologies.
- Demonstrated ability to bridge the gap between legal/risk and technical teams.
- A strong desire and proven ability to lead a dedicated AI ethics function.

15Where this role leads

The long view: This work can lead to board level roles overseeing AI governance, or to advising organisations on responsible AI strategy.

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, AI Ethics & 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, AI Ethics & Governance.

Ethics, Fairness and Explanation in Artificial Intelligence Level 7

Applied to your work in Director, AI Ethics & 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, AI Ethics & Governance plan, free

See Your Progress Grow Illustration

Director, AI Ethics & Governance

Responsible AI Frameworks & Operationalisation
Sociotechnical Systems Analysis (Enterprise-scale)
Algorithmic Auditing & Bias Mitigation (Strategic Oversight)
Ethical Risk Assessment & Triage (Enterprise Program Design)
Policy Drafting & Governance Implementation (Enterprise-wide)
Stakeholder Deliberation & Conflict Resolution (Executive Level)

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

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

Enterprise-wide strategic authority, P&L £10M+, board governance, investor relations, market shaping.
- Defining enterprise-wide AI risk appetite and strategic posture.
- Leading M&A due diligence and integration from an enterprise ethics perspective.
- Developing long-term (3-5 year) vision for responsible AI that shapes company direction.
- Managing relationships with major global regulators and policymakers.
Chief Technology Officer (CTO) or Chief Risk Officer (CRO)
5-7 years in the Director role

Broader enterprise leadership, full P&L accountability for a major function, overall technology or risk strategy.
- Defining overall technology roadmap or enterprise risk framework.
- Leading major technology investments or risk mitigation programmes.
- Developing and executing M&A strategy for technology or risk.
- Building and nurturing relationships with key technology partners or risk insurers.

Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, as a Director, your biggest constraint isn't a lack of ideas—it's a lack of time. Time to think, time to strategise, time to engage with those critical stakeholders. The good news? AI isn't just for product teams anymore. We're actively using AI tools to cut through the noise, automate the tedious, and give our leaders back precious hours every week. Imagine what you could do with an extra day or two of focused, strategic time.

In this role, AI won't replace your judgment, but it will certainly augment your ability to lead. You'll use these tools to quickly digest complex information, guide your team more effectively, and proactively identify risks, freeing you up to focus on the truly strategic, high-impact work that only a human can do.

Policy & Regulation Navigator

Use a private LLM to ingest and summarise dense regulatory documents—think the 500+ pages of the EU AI Act and its annexes. It'll extract key obligations, definitions, and prohibited practices, presenting them in a structured, actionable format. This means less time reading dry legal text and more time strategising how to implement it.

Strategic Bias Hypothesis Generator

An AI tool that analyses a project's description and data schema to suggest potential fairness risks and vulnerable subpopulations. As a Director, you'd use this to quickly validate your team's initial assessments, ensuring they haven't missed critical angles, and to guide them towards deeper investigations. It's like having an instant second opinion.

First-Draft Mitigation Library & Reviewer

An LLM trained on our past ethics reviews can generate a first draft of recommended mitigation strategies based on a newly identified risk. For you, this means faster review cycles for your team's work, ensuring consistency and quality, and quickly identifying novel risks that require your direct strategic input. It accelerates your oversight.

Advanced Red Teaming Scenario Creator

Use generative AI to brainstorm creative and unexpected ways a user might misuse a new AI feature. As the Director, you'd leverage this to push the boundaries of our internal 'red teaming' exercises, ensuring we're anticipating the most sophisticated and damaging misuse cases, building more robust defences across the business unit.

Common questions

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

Common routes in include Principal Ethicist / AI Ethics Lead (3-5 years at L4), Manager, AI Ethics & Governance (2-4 years at L5) and Senior Legal Counsel (AI Focus) or Chief Risk Officer (with AI Specialism) (5-8 years in a senior legal/risk role with heavy AI focus). Times vary with prior experience.

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

This role can lead on to VP, Responsible AI / Chief Ethics Officer (3-5 years in the Director role) and Chief Technology Officer (CTO) or Chief Risk Officer (CRO) (5-7 years in the Director role), depending on the skills you build.

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

Increasingly, AI Geopolitics & International Standards Leadership and AI Incident Response & Forensics Leadership. 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, AI Ethics & 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, AI Ethics & Governance

Where should we send it?

Two short quizzes about you

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

What's rising in its place

AI Geopolitics & International Standards Leadership

AI Incident Response & Forensics Leadership

Skills this role draws on

Technical

How you actually get there, here

Principal Ethicist / AI Ethics Lead (L4)

Manager, AI Ethics & Governance (L5)

Senior Legal Counsel (AI Focus) or Chief Risk Officer (with AI Specialism)

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, Responsible AI / Chief Ethics Officer (L7)

Chief Technology Officer (CTO) or Chief Risk Officer (CRO)

Where AI is starting to help

Policy & Regulation Navigator

Strategic Bias Hypothesis Generator

First-Draft Mitigation Library & Reviewer

Advanced Red Teaming Scenario Creator

Common questions

Want a read on where you stand?