Professional Development Analytics: A Smart Model for Industry 5.0

This paper presents a novel AI-driven conceptual smart model designed to help organizations enhance workforce professional development by upskilling and reskilling employees while fostering job satisfaction and staying competitive in their markets; this novel model is called Professional Development Analytics (PDA). The model’s main focus is to provide a new design model that concentrates on how artificial intelligence (AI) can optimize personalized training and how it can improve employees’ technical and soft skills, enabling companies to create their talent map at the same time. By compiling personnel data and their roles within the company, AI is able to create detailed and personalized profiles. In the next stage, this information is classified, analyzed, and used to enhance current skills while also predicting future training needs. These processes result in the creation of personalized learning paths, where AI recommends customized courses tailored to each employee’s unique needs. The system will be automatically fed and adjusted by means of the gathered data and continuous feedback from the employees and their supervisors. The proposed AI tools are powered by machine learning, deep learning, natural language processing, generative AI and data analytics. Our model aims to support learning and development departments by delivering precise, personalized training solutions that address employees’ unique needs, enabling skill development and professional growth through an automated and customized process.

Authors

Institutions

Publication Details

Journal
Applied Sciences
Published
2025-02-16
DOI
https://doi.org/10.3390/app15042057
Citations
8
Primary Topic
AI and HR Technologies
Type
article
Field-Weighted Citation Impact
22.11
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Professional Development Analytics: A Smart Model for Industry 5.0

Raúl Santiago Campión, Ramón Palau, Natalia Tusquellas
8 citations
Applied Sciences
AI and HR Technologies
22.11
article

Professional Development Analytics: A Smart Model for Industry 5.0

Raúl Santiago Campión, Ramón Palau, Natalia Tusquellas
article en
8 citations

Abstract

This paper presents a novel AI-driven conceptual smart model designed to help organizations enhance workforce professional development by upskilling and reskilling employees while fostering job satisfaction and staying competitive in their markets; this novel model is called Professional Development Analytics (PDA). The model’s main focus is to provide a new design model that concentrates on how artificial intelligence (AI) can optimize personalized training and how it can improve employees’ technical and soft skills, enabling companies to create their talent map at the same time. By compiling personnel data and their roles within the company, AI is able to create detailed and personalized profiles. In the next stage, this information is classified, analyzed, and used to enhance current skills while also predicting future training needs. These processes result in the creation of personalized learning paths, where AI recommends customized courses tailored to each employee’s unique needs. The system will be automatically fed and adjusted by means of the gathered data and continuous feedback from the employees and their supervisors. The proposed AI tools are powered by machine learning, deep learning, natural language processing, generative AI and data analytics. Our model aims to support learning and development departments by delivering precise, personalized training solutions that address employees’ unique needs, enabling skill development and professional growth through an automated and customized process.

Applied SciencesVol. 15(4)
Navarrabiomed (ES), Universitat Rovira i Virgili (ES)
Openalex Percentile: Top 1%
AI and HR Technologies
22.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.