AI Lead (P-1066880382)
| Company: | Reed Talent Solutions |
|---|---|
| Salary: | Not specified |
| Hours: | Full-time |
| Location: | Bedford, MK40 1SU |
| Job type: | Permanent |
| Posting date: | 20 Oct 2026 |
| Closing date: | 19 Nov 2026 |
Summary
The role
The AI Lead reports to the Head of Data and Analytics and provides senior leadership, coordination and oversight for AI across MaPS.
The role provides a single point of responsibility for aligning AI strategy, investment, delivery priorities and organisational readiness, ensuring AI initiatives support MaPS priorities and deliver measurable value. Working across technology, product, delivery, governance and business teams, the AI Lead will set direction, enable adoption, strengthen oversight and create the conditions for AI work to be delivered effectively by specialist teams.
This role sets the organisational direction and conditions for AI to succeed, while technical development is led by the Lead Data Scientist role who reports into the AI Lead.
Key accountabilities
AI leadership and coordination: Provide senior leadership for AI activity across MaPS, ensuring strategic priorities, delivery capacity, governance and organisational capability are aligned.
AI strategy delivery: Work with senior stakeholders from across the organisation to agree organisational AI priorities and translate into an AI roadmap.
Organisational adoption and embedding: Lead the approach to embedding AI across MaPS by working with the internal AI Product manager, People and Culture team plus operational and specialist teams to prioritise opportunities, remove barriers and support sustained adoption.
Cross-functional partnership: Partner with colleagues in the Technology and Change Directorate, including Software Engineering, Testing, User-Centred Design, Data and Analytics, Solution Architecture, Security and Product teams to ensure the right organisational conditions are in place for AI-enabled processes and solutions to be delivered safely and effectively.
Delivery oversight: Work with Product Managers, Project Managers and Delivery Managers to oversee the portfolio of AI initiatives, manage dependencies, unblock issues and maintain alignment with agreed priorities.
Benefits realisation and value measurement: Work with the Lead Data Scientist to set the approach for defining success, tracking benefits and assessing value from AI investments, ensuring measures are meaningful, proportionate and used by the business to inform adoption and decision-making.
AI capability building: Shape the organisational approach to AI capability building, identifying learning needs, enabling knowledge sharing and supporting colleagues to apply AI responsibly and effectively.
Governance and assurance: Lead the development and application of proportionate governance, risk management and assurance arrangements, ensuring clear routes for escalation, decision-making and responsible AI adoption.
External engagement and horizon scanning: Monitor developments in AI, engage with external partners and communities where appropriate, and identify opportunities relevant to MaPS' strategic objectives.
Team leadership: Lead and develop AI specialists, including line management of the Lead Data Scientist role, providing direction, prioritisation and coaching while enabling the technical team to retain ownership of solution design, build, technical assurance, monitoring and safe deployment.
Skills & experience
AI leadership: Significant experience providing senior leadership for AI initiatives, including prioritisation, coordination, adoption and value realisation across an organisation.
AI Expertise: Strong understanding of AI, machine learning and AI capabilities, opportunities, risks and limitations, with the ability to influence senior and strategic decisions.
Strategic delivery: Experience turning strategic priorities into clear delivery roadmaps, governance routes, resourcing decisions and measurable outcomes.
Stakeholder engagement: Proven ability to influence, challenge and build strong relationships across technical and non-technical communities.
Partnership working: Experience working across product, technology and business functions to deliver change and achieve shared outcomes.
Benefits realisation: Experience setting value measures, overseeing benefits tracking and supporting business ownership of adoption and impact.
Leadership: Strong leadership skills with experience setting direction, developing people, supporting technical specialists, creating collaborative high-performing teams, and operating as an effective member of a senior leadership team.
Communication: Excellent and engaging communication skills, with the ability to explain complex AI concepts in accessible and practical ways, listen actively, and adapt messages for different audiences.
Governance and Risk: Strong understanding of the governance, risk and assurance arrangements needed to support responsible AI adoption at organisational level.
Other
Other
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