Key Purpose
- The Head of AI is an executive leadership role responsible for defining and delivering the Discovery Health AI strategy. The successful candidate will bridge technical depth with business acumen, unifying AI initiatives across all business units, establishing responsible AI governance aligned to group standards and demonstrating measurable returns on AI investment. This proven executive must build high-performing team/s, be influential at C-suite level and translate complex AI concepts into tangible business outcomes.
Areas of responsibility may include but not limited to:
- This role requires a blend of proven executive leadership, underpinned by technical expertise. Candidates must demonstrate a sustained track record of leading technology and AI transformation at scale, with clear accountability for outcomes, including:
- 10+ years of progressive leadership in technology, data and product domains, with at least 5 years in a senior executive capacity.
- Demonstrated history of delivering AI and data science initiatives that produced measurable, attributable business and operational returns — not activity metrics, but outcomes.
- Experience owning and managing significant technology budgets, including AI investment decisions, ROI tracking and board-level reporting.
- Proven ability to influence and align C-suite and senior stakeholders, building the organisational consensus required to execute large-scale transformation.
- Experience navigating enterprise change management — driving adoption of new technology and operating models across complex, multi-business-unit organisations.
- Track record of building, growing and retaining high-performing technical teams in competitive talent markets, including experience hiring and developing senior AI and data science talent.
AI Strategy & Commercial Acumen
The Head of AI will define and own the organisation’s AI roadmap. The candidate must demonstrate the ability to connect AI investment to business strategy, not just technical delivery, including:
- Experience designing and executing an enterprise AI strategy, including prioritization frameworks, roadmap governance and alignment to business unit objectives.
- Proven track record of preventing or reversing AI sprawl — consolidating fragmented AI initiatives into a coherent, governed and scalable programme.
- Familiarity with build vs. buy decision-making, including evaluation of third-party AI platforms, large language model providers and cloud-native ML services.
- Experience managing vendor relationships and commercial negotiations with AI/ML platform and infrastructure providers.
- Ability to translate complex AI capabilities into business cases and communicate ROI, risk and strategic rationale to non-technical executive audiences.
Technical Literacy & Architectural Oversight
The role requires sufficient technical depth to evaluate architectural decisions, assess risk, and provide credible leadership to senior technical teams. While candidates are not expected to be hands-on practitioners, literacy across core domains is a must, including:
- Machine Learning & Data Science
- Generative & Agentic AI
- Data Architecture & Engineering
- Cloud & Infrastructure
- Software & Development
Governance, Risk & Responsible AI
- Experience designing and implementing a Responsible AI framework that addresses Fairness, Accountability, Transparency and Ethics (FATE) risks.
- Applied knowledge of AI governance frameworks, including the NIST AI Risk Management Framework (AI RMF) or equivalent.
- Demonstrated ability to manage high-stakes AI risks including model risk outcomes, data privacy and reputational exposure.
- Experience working within regulated industries, with awareness of the compliance, audit and oversight requirements that apply to AI systems.
- Familiarity with South African data privacy regulation (POPIA) and, advantageously, international equivalents (GDPR, HIPAA) relevant to healthcare and financial services contexts.
Collaboration & Communication
A core mandate of this role is unifying AI efforts across a diverse, multi-division organisation. This requires exceptional cross-functional influence and communication capability, including:
- Demonstrated ability to work collaboratively across business units, operating as an integrating force rather than a siloed function.
- Experience establishing and chairing cross-functional AI governance or steering forums.
- Ability to adapt communication style for diverse audiences — from engineering teams to executive committees to board-level stakeholders.
- Strong executive presence with the ability to navigate organisational complexity, manage competing priorities and build support for strategic initiatives.
Personal Attributes and Skills
- Values Driven
- Optimistic and Dynamic
- Effective communicator
- Builds a sense of community in the Department
- Problem Solver
- Learns on the fly
- Results focused
- Resilient
- People Savvy
- Instills trust
At Discovery, Leaders:
- are inspirational leaders who live the values and believe in the core purpose
- are humble
- treat others with care, dignity and respect
- ensure that the business case prevails
- have a bias for action
- understand that people are Discovery's greatest asset
- build an environment for optimal performance
- set ambitious goals and implement the highest standards
- are students and Master of Communication?
- never stop learning
- have and express strong beliefs and views, yet are open-minded and support the chosen path
Education and Experience
The following are essential requirements:
- Min 15 Years industry experience with a clear track record of delivering AI solutions in a highly regulated sector, with a working understanding of the compliance landscape that governs data use, model deployment and clinical or operational risk.
- An undergraduate qualification in a relevant quantitative or technical discipline from a recognised institution, such as:
- BSc Computer Science, Data Science, or equivalent
- BCom in Statistics, Information Systems, or Data Science
- BSc or BEng (Engineering) with a significant IT or data focus
- Equivalent demonstrated experience will be considered where formal qualifications are supplemented by a strong and verifiable career record.
