AI-Powered Avatars as Expert Mentors: Knowledge Transfer and Professional Development within Multimodal Learning Environments - Salvetti, Fernando; Bertagni, Barbara; Pieraccini, Roberto (International Journal of Advanced Corporate Learning (iJAC), 2026)
The growing demand for personalized, scalable, and high-quality learning experiences has accelerated the adoption of AI-powered avatars in professional training, higher education, and organizational learning. These avatars—also referred to as Embodied Conversational Agents (ECAs)—simulate expert mentors who provide adaptive guidance, enabling learners to acquire complex cognitive, behavioral, and communicative skills in realistic scenarios. By leveraging advances in natural language processing, affective computing, and multimodal interaction design, avatars embody a new paradigm of virtual coaching that blends scalability with human-like social presence. This paper presents Mia, an intelligent avatar developed within the e-REAL ecosystem, designed to function as an expert mentor across multiple domains, including healthcare, legal practice, corporate leadership, and education. Unlike generic digital assistants, Mia operates within a human-centric framework that prioritizes empathy, trust, and inclusivity. The avatar’s adaptive capabilities are powered by a layered architecture combining retrieval-augmented generation (RAG), a flexible orchestration system, and real-time speech and gesture synthesis. This architecture ensures reliable knowledge transfer while minimizing hallucinations and aligning with ethical and regulatory standards such as the EU AI Act and GDPR. The introduction of avatars like Mia raises important questions about how embodiment, proxemics, and non-verbal communication influence learning outcomes, particularly in immersive environments where presence and credibility strongly affect engagement. Research on social robotics and immersive virtual environments shows that avatars capable of managing turn-taking, gaze, and emotional tone foster stronger identification and learning retention compared to text-based interfaces. By combining these insights with the flexibility of generative AI, virtual mentors can deliver personalized, repeatable, and unbiased coaching at scale. We argue that avatars such as Mia exemplify the convergence of pedagogy, cognitive science, and technological innovation, pointing toward a future where expert mentoring is no longer bound by time, location, or human availability. In this vision, AI-powered avatars do not replace human educators but amplify their reach, ensuring that high-quality expertise is available across contexts, cultures, and languages.