The pathway
How you actually get there, here
How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.
- 1
Senior AI Learning Strategist (L3)
3-5 years in previous roleSkills to master
- Deep expertise in a specific area of AI learning (e.g., adaptive content, skills ontology), strong project management, initial experience mentoring junior colleagues, and a solid track record of delivering complex learning programmes.
You're ready to move on when
- Successfully led 2-3 major AI learning projects from design to deployment.
- Consistently sought out for technical advice by peers and junior team members.
- Demonstrated ability to influence cross-functional teams without direct authority.
- Proactively identified and proposed solutions for architectural challenges in existing systems.
- 2
Learning Technology Lead / Solutions Architect (from another company)
8-12 years overall experienceSkills to master
- Proven experience designing and implementing large-scale learning technology ecosystems, strong vendor management, deep technical understanding of system integrations, and a clear vision for how AI can enhance learning outcomes.
You're ready to move on when
- Can articulate a clear vision for AI in learning based on previous experience.
- Has successfully managed complex system integration projects involving HRIS, LMS, and other platforms.
- Demonstrates strong leadership capabilities, even if not in a direct people management role previously.
- Possesses a portfolio of architectural designs or implemented solutions.
- 3
Data Scientist / ML Engineer (with L&D interest)
8-12 years overall experienceSkills to master
- Strong background in machine learning, data modelling, and MLOps, coupled with a genuine interest in applying these skills to solve learning and development challenges. Will need to quickly pick up learning science and instructional design principles.
You're ready to move on when
- Has built and deployed ML models in production environments.
- Can demonstrate strong data analysis and visualisation skills.
- Expresses a clear passion for the intersection of AI and human development.
- Quickly grasps the nuances of learning data and its ethical implications.