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Copyright © 2025
Copyright © 2025
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Role Purpose
The Head of AI & Advanced Analytics Translation and Enablement is the organisational bridge between business ambition and technical execution for AI and analytics initiatives. This role ensures that advanced analytics solutions are identified, designed, implemented, adopted, and sustained in a way that delivers measurable business value.
By combining analytics translation, stakeholder engagement, change management, and solution monitoring, the postholder drives adoption at scale, ensures responsible AI use, and enables the organisation to maximise its AI and analytics investments.
Key Responsibilities
1. Strategy & Roadmap
Define and own the AI & Advanced Analytics Translation and Enablement strategy.
Align AI/analytics initiatives with corporate objectives, market opportunities, and operational priorities.
Maintain a roadmap that reflects both transformational opportunities and quick-win use cases.
2. Analytics Translation
Translate complex AI/analytics concepts into actionable business language for stakeholders.
Identify and frame high-impact use cases in collaboration with business units.
Partner with technical teams to ensure solutions are designed for real-world business application.
3. Enablement & Adoption
Develop enablement frameworks to equip business teams with the skills and confidence to adopt AI/analytics solutions.
Lead the design of training, workshops, and communications to improve AI literacy across the organisation.
Build feedback loops to ensure deployed solutions remain relevant and well-used.
4. Change Management
Lead change management strategies for AI/analytics rollouts, ensuring smooth adoption and minimal disruption.
Address organisational resistance through targeted interventions and stakeholder engagement.
Track and report on adoption metrics, identifying opportunities for improvement.
5. Monitoring & Continuous Improvement
Oversee solution monitoring to track performance, model drift, and business impact.
Partner with MLOps and data engineering teams to ensure solutions remain performant and compliant.
Ensure feedback from monitoring informs iterative improvements.
6. Governance & Ethics
Ensure AI/analytics initiatives comply with relevant regulations (e.g., GDPR, EU AI Act) and internal governance standards.
Embed responsible AI principles, including fairness, transparency, and bias mitigation, into all initiatives.
Act as a trusted advisor on AI ethics to business and technical leaders.
7. Leadership & Collaboration
Lead and develop a cross-functional team of analytics translators, adoption specialists, and monitoring leads.
Foster collaboration between data science, engineering, and business teams.
Represent AI & Advanced Analytics at senior leadership forums.
Key Skills & Experience
Significant leadership experience in AI, advanced analytics, digital transformation, or related roles.
Demonstrated success in analytics translation and business engagement.
Strong understanding of AI/ML concepts, data engineering, and analytics platforms.
Expertise in change management and solution adoption best practices.
Proven ability to manage cross-functional teams and influence at senior levels.
Knowledge of AI governance, regulatory requirements, and ethical considerations.
Performance Measures
Percentage of AI/analytics initiatives delivering target ROI.
Solution adoption rates across business units.
Improvement in AI literacy and engagement scores.
Stability and reliability of deployed models in production.
Stakeholder satisfaction with translation and enablement support.
Why This Role Matters
AI and advanced analytics offer transformative potential, but only if the right problems are solved, users adopt the solutions, and models remain effective over time. This role ensures that every AI/analytics investment delivers measurable, sustainable value - by connecting strategy, execution, and adoption.