AI Learning Specialist

Overview

In this role you enable colleagues to understand and adopt AI, automation and emerging technologies within a law firm. You will blend AI enablement, digital adoption, learning design and business transformation to translate complex tech into practical, safe workflows. You’ll work with Learning & Development, Innovation, Technology and cross‑firm teams to shape how AI is adopted and to build confidence and capabilities. This is a hands-on, non‑traditional training role focused on measurable adoption and impact, not routine IT training.

Responsibilities

• Identify areas where AI, automation and emerging tech add value to roles and processes.
• Run discovery conversations, process mapping and hands-on experiments to explore workflows.
• Translate technical concepts into practical solutions and scenario-based learning for non-technical audiences.
• Design and deliver workshops, digital learning, coaching, toolkits and performance support.
• Facilitate discussions to redesign workflows and promote adoption of new approaches.
• Develop and share practical AI use cases, prompts and good practice.
• Support colleagues to review and apply AI-generated outputs safely and responsibly.
• Measure engagement and adoption, using insights to improve AI enablement.

Key requirements

• Practical knowledge of AI and emerging technology or the ability to develop it quickly
• Understanding of generative AI, LLMs, prompt engineering or workflow automation
• Ability to understand business processes and translate tech for non-technical users
• Experience in learning design, digital adoption, technology enablement or capability building
• Experience using AI-enabled or digital workplace tools
• Knowledge of Microsoft Copilot, Harvey or similar platforms (advantage)
• Strong facilitation, coaching, stakeholder engagement and communication skills
• Understanding of data quality, privacy, risk and responsible AI use
• Collaborative and adaptable approach in a fast-moving area

• facilitation
• coaching
• stakeholder engagement
• AI and emerging technology
• generative AI and large language models
• prompt engineering

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