XR-CareerAssist @ SalentoXR 2025

XR-CareerAssist, one of the Open Call winners of VOXReality, was presented at the International Conference on Extended Reality, Salento XR 2025, held in Otranto, Italy (June 17–20, 2025). The project uses VR and AI to make career planning dynamic, personalized, and engaging.

The paper, “Transforming Career Development Through Immersive and Data-Driven Solutions,” focuses on XR-CareerAssist to address the limitations of traditional career counseling, often seen as boring, inflexible, and hard to access.

The system uses VR goggles and AI to create an immersive environment. Users interact with a 3D avatar that understands multiple languages, visualize career paths with interactive maps, and get personalized advice from a database of over 100,000 real career profiles. It also features voice commands for natural interaction.

The paper details the system’s design, built on a vast database of CVs, and describes how AI models work together. Future plans include testing with 25-40 real users.

Real-World Impact: Sarah’s Journey with XR-CareerAssist

Consider Sarah, a 35-year-old IT manager in the UK with 10 years of experience, aiming to become a Chief Officer. XR-CareerAssist helps her directly:

  • Immersive Start: Sarah puts on a MetaQuest 3 headset and enters a virtual environment with a 3D avatar.
  • Voice Interaction: She simply states her current role, experience, and Chief Officer aspiration.
  • Instant Analysis: The system quickly finds 1500 similar profiles, showing that such professionals typically work across 3 sectors and that reaching Chief Officer takes about 15 years.
  • Visual Career Map: Sarah sees an interactive Sankey diagram (flowchart) displaying various paths from Manager to Chief Officer over the next 10 years, including industry detours.
  • Multilingual Support: The system automatically translates everything into French if Sarah prefers, due to her work with a French company.
  • Personalized Insights: The AI-powered avatar explains visualizations, points out necessary skills, and highlights high-success career moves. Sarah can actively ask questions via speech.

This example shows how XR-CareerAssist offers data-backed, visual, and highly personalized guidance, empowering users to make informed career decisions.

2_Using Augmented Reality and Machine Learning for Captioning in Theatrical Experiences #183-poster for SalentoXR - V1_page-0001
Poster for the paper presented in SalentoXR 2025

Abstract: The rapid evolution of technology has created opportunities to transform traditional career guidance methods into dynamic, immersive, and data-driven solutions. XR-CareerAssist, is an innovative platform, that aims to provide career insights and enhance user engagement by integrating Extended Reality (XR) and Artificial Intelligence (AI) technologies. A dedicated tool is built and presented, which analyses over 100,000 anonymised professional profiles. This tool is a key-component of XR-CareerAssist and is used to visualise career trajectories, industry trends, and skill pathways through interactive and immersive experiences. Features such as virtual reality (VR) environments, voice-based navigation, multilingual support, and AI-driven 3D avatars empower users to explore career paths dynamically and intuitively. By merging robust data analytics with immersive visualizations, XR-CareerAssist not only boosts user engagement but also improves accessibility and aids in the clear interpretation of career trajectories. This study explores the envisioned scenarios, highlights results from initial testing with the CV Analysis tool, and examines how XR-CareerAssist enhances career guidance and training, fostering personalised and impactful career development in a globalised job market.  

Keywords: Career Guidance, Career Maps, Artificial Intelligence, LLMs, Virtual Reality

Full Article: “Transforming Career Development Through Immersive and Data-Driven Solutions” by N.D. Tantaroudas (Institute of Communication and Computer Systems, Greece), A. J. McCracken (DASKALOS-APPS, France), I. Karachalios (National Technical University of Athens, Greece), E. Papatheou (University of Exeter, UK), V. Pastrikakis (CVCOSMOS Ltd, UK)

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