Current as of 15 January 2026
AI & Behavioural Tech Glossary
This glossary breaks down the AI and behavioural tech terms you’ll see across the platform so you can understand how it works, not just what it’s called.
AI Role-Play Simulation
Definition: A digital training environment where a learner interacts with a Generative AI avatar to practice real-world conversations.
Why it matters: Unlike static videos, AI role-play adapts to the user's specific input, providing a dynamic "flight simulator" for high-stakes human interactions in, for example, sales and leadership.
Behavioural Marker Analysis
Definition: The use of AI to identify specific linguistic and tonal cues that correlate with successful outcomes, such as empathy in leadership or objection-handling in sales.
Why it matters: It turns subjective feedback ("You sounded nervous") into objective data points ("Your speaking rate increased by 20% during the price negotiation").
Scalable Coaching Ecosystem
Definition: An integrated suite of AI-driven tools that allows an organisation to provide personalized 1:1 coaching to every employee simultaneously.
Why it matters: It removes the "coaching bottleneck," allowing companies to move beyond coaching only their top executives to developing their entire frontline workforce.
Human-in-the-Loop (HITL) Training
Definition: An L&D methodology where AI provides the bulk of practice and data gathering, but human mentors intervene at critical "strategic" junctions based on AI-generated insights.
Why it matters: This ensures that technology augments human expertise rather than replacing it, leading to higher adoption and better ethical outcomes.
Skills Gap Heatmapping
Definition: A data visualisation technique that aggregates AI performance data across a team to show where specific behavioural weaknesses exist.
Why it matters: It allows L&D leaders to stop "guessing" what training is needed and start deploying targeted interventions based on real-time practice data.