AI Transformation Lead

Role overview

About Cognita

Strategy, team and delivery

• Turn the AI vision into a prioritised plan and own its delivery end to end.
• Hire and lead the internal AI team, direct delivery partners, and set standards and ways of working.
• Act as the central intake for AI demand, prioritise use cases and match them to suitable delivery routes.
• Lead the design, build and deployment of agents, automation and end-to-end workflow orchestration from prototype to production.
• Work with Data teams to establish the data foundations for AI solutions.

Enablement, platforms and governance

• Build AI skills and confidence through literacy and training, a champions network, and approved workflows and guidance; lead change management for everyday adoption.
• Shape AI platform and tooling strategy, make build-versus-buy decisions, monitor and evaluate live solutions, and manage vendor licensing and costs.
• Run AI governance, including policy, tool and model inventory, acceptable use and guardrails; work with Legal, Compliance, Data Protection and Cyber Security on risks.
• Track adoption, ROI, efficiency, productivity, revenue and cost gains; scale what works, retire what does not and recommend investments.
• Scan for new AI capabilities and run targeted pilots.

Experience and expertise

• Experience leading an AI or digital transformation programme at scale with measurable adoption and business outcomes.
• Deep applied AI expertise, including generative AI, personal agents, automation and orchestration, and enterprise-scale platform, architecture and delivery implementation.
• Experience launching AI tools and platforms from an early stage, evaluating vendors and integrating tools into enterprise systems.
• Track record deploying generative AI and agentic automation into live business processes with measurable efficiency or productivity gains.
• Experience delivering AI literacy, training or enablement across a large or dispersed workforce.
• Experience building a small technical AI team and coordinating delivery partners and stakeholder networks.
• Experience creating AI-value metrics and reporting for senior stakeholders and investment decisions.
• Experience negotiating and managing AI vendor and partner arrangements, including licensing and contract terms.
• Ability to build credibility with senior leaders and turn AI enthusiasm into prioritised outcomes.
• Sound understanding of responsible AI, governance and risk, including safe, fair and regulation-aligned deployment.

Education and training

• Bachelor’s degree in computer science, data science or a related discipline, or equivalent experience.
• Relevant AI tooling training or certification, such as Anthropic or OpenAI; the source description ends before this qualification is complete.