Scaling Learning with AI: From Experimentation to Everyday Practice - Chantelle Hodson, Katy O'Donnell, R. Tadelayo Sodipe & Sophie Ward

As AI capabilities rapidly expand, learning teams are moving beyond experimentation and beginning to embed these tools into the core of how learning is designed, delivered, and scaled. But scaling AI effectively is not simply a matter of adopting more tools. It requires thoughtful decisions about where automation adds value, where human expertise must remain central, and how learning teams can build practices that are both effective and trustworthy.

In this session, members of the Thirty Under 30 cohort explore what it means to scale learning with AI in practical, responsible ways. Drawing on their own experiences across design, delivery, accessibility, skills development, and workplace learning, they discuss how AI is beginning to reshape the day-to-day realities of learning work and what it takes to move from isolated experimentation to sustainable operational practice.

Rather than presenting scale as a purely technical challenge, this panel surfaces the judgments, trade-offs, and organisational questions that shape how AI is actually applied in learning. Attendees will leave with a grounded perspective on how emerging professionals are thinking about scale, quality, and human oversight in an AI-enabled future.

Key Topics Include:

• Practical ways AI is being used to scale learning programs today
• Lessons learned from moving beyond pilots and proofs of concept
• Balancing automation with human expertise and oversight
• Common challenges learning teams face when operationalizing AI
• What scalable, AI-enabled learning models mean for the future of L&D