[2604.05345] Dynamic Agentic AI Expert Profiler System Architecture for Multidomain Intelligence Modeling

Computer Science > Artificial Intelligence arXiv:2604.05345 (cs) [Submitted on 7 Apr 2026] Title:Dynamic Agentic AI Expert Profiler System Architecture for Multidomain Intelligence Modeling Authors:Aisvarya Adeseye, Jouni Isoaho, Seppo Virtanen, Mohammad Tahir View a PDF of the paper titled Dynamic Agentic AI Expert Profiler System Architecture for Multidomain Intelligence Modeling, by Aisvarya Adeseye and 3 other authors View PDF HTML (experimental) Abstract:In today's artificial intelligence driven world, modern systems communicate with people from diverse backgrounds and skill levels. For human-machine interaction to be meaningful, systems must be aware of context and user expertise. This study proposes an agentic AI profiler that classifies natural language responses into four levels: Novice, Basic, Advanced, and Expert. The system uses a modular layered architecture built on LLaMA v3.1 (8B), with components for text preprocessing, scoring, aggregation, and classification. Evaluation was conducted in two phases: a static phase using pre-recorded transcripts from 82 participants, and a dynamic phase with 402 live interviews conducted by an agentic AI interviewer. In both phases, participant self-ratings were compared with profiler predictions. In the dynamic phase, expertise was assessed after each response rather than at the end of the interview. Across domains, 83% to 97% of profiler evaluations matched participant self-assessments. Remaining differences were due to s...