How AI Supports Coaching in Learning and Development
In learning and development, coaching helps people make sense of information about themselves. That information comes from assessment results and reflection on experience. As self-awareness increases, individuals gain clarity about priorities, goals, and areas for growth. Insight develops when people connect what they learn about themselves to their choices and the context in which those choices occur.
AI contributes to coaching by supporting this sensemaking process. When AI draws on validated assessment results, it keeps reflection anchored in evidence. People gain a clearer view of patterns in their behavior and tendencies in their decision-making. Areas of tension become easier to recognize and examine.
Coaching depends on interpretation. People often recognize that a result feels unexpected or misaligned without understanding the source of that reaction. AI can support interpretation by clarifying what a score captures, how different dimensions interact, and where tradeoffs appear across situations. This support strengthens understanding rather than prescribing action.
Many development challenges reflect gaps between intention and behavior. Assessment results help surface those gaps. Reflection deepens when individuals examine what their data suggests about how they operate across settings, roles, and demands. AI can structure this examination by guiding attention to relevant dimensions and encouraging deliberate consideration.
Context shapes how people understand themselves. Results take on different meanings when viewed through cultural, situational, or environmental lenses. Comparing profiles across contexts encourages perspective-taking and reduces the tendency to treat one’s own experience as the default. This process supports more accurate judgment in unfamiliar or changing environments.
Within myGiide, BridgeIt supports this type of reflection by responding to (and asking) questions based on the users’ assessment results. Each interaction starts with an understanding of the individual’s assessment results and what this will mean for the situation they will be going into (e.g., working or studying in a host country) or the development they hope to achieve (e.g., how to build certain skills). Responses reflect the person’s specific profile rather than generic guidance. The focus stays on helping users interpret what their results suggest about how they operate in unfamiliar or changing environments. This reflection supports effectiveness in new contexts and the development of cultural agility competencies, including perspective-taking, tolerance for ambiguity, curiosity, and humility.
AI adds value in coaching when it supports careful thinking. It helps individuals interpret evidence, consider multiple explanations, and reflect before acting. Over time, this process strengthens judgment and supports meaningful development.
Used thoughtfully, AI becomes a practical extension of coaching in learning and development. It reinforces reflection grounded in evidence and context. That contribution aligns with how people learn and grow.