AI Enablement Lead

AI Enablement Lead

At Environment Bank, we adopt AI, machine learning and automation to enhance our ability to restore nature at scale and to empower our people to work more efficiently and insightfully, always in a secure, sustainable, and responsible manner.

The AI Enablement Lead will drive real, practical value from AI tools and platforms across Environment Bank. You'll work with colleagues around the business to understand their process and workflows, and identify where AI, and alternative forms of automation, can genuinely improve efficiency, and collaboratively turn those opportunities into working solutions. The function of the role is to bring the right people together to agree which opportunities are worth pursuing, and giving teams ownership of the solutions, so AI capability grows across the business rather than sitting with one person. This includes training people to use AI tools responsibly, effectively and confidently, prototyping automations that eliminate repetitive work, and developing bespoke internal AI skills and tools, always in service of our core mission to restore nature at scale.

Based in our fully remote Data, Systems & GIS team, you'll be the go-to person for AI knowledge across the business, lead AI knowledge-sharing and a network of AI champions, stay current with platforms and capabilities, all while collaborating seamlessly across a distributed team. The role is remote-first, with travel to run workshops and work with teams in person.

Responsibilities:

• Champion the responsible use of AI across the business, staying current with relevant platforms, tools and capabilities so that every new adoption supports our mission to restore nature at scale
• Develop and deliver training, guidance and documentation to help colleagues use AI tools effectively and efficiently in their roles
• Lead structured discovery with teams to map how work is done and identify opportunities across the business where process automation and/or AI-powered tools could improve efficiency or reduce repetitive work, bringing the right people together to agree which are worth pursuing and giving teams ownership of the solutions
• Maintain a prioritised pipeline of AI and automation opportunities, and report progress and value delivered to leadership
• Collaboratively prototype and test new tools and approaches, assessing their suitability for development, and work with colleagues to turn those opportunities into working, implemented solutions
• Enable colleagues to implement simple solutions themselves, and work with the Data, Systems & GIS team to scope, develop and build internal process automation tools and in take them into production
• Create, maintain and update documentation for tools, processes and training materials
• Build a network of AI champions and self-serve guidance so that day-to-day troubleshooting and technical queries relating to AI tools are handled within teams, stepping in on the harder cases
• Establish sensible guardrails and best practices for responsible AI use, balancing productivity gains with data security, quality control and our duty of care to the nature recovery outcomes we deliver