Enhancing recruitment process for early-graduate employees in business consulting: A BPMN case study with AI-driven To-Be solution
In a world increasingly driven by Industry 5.0 and the forces of globalization, employee volatility is on the rise, creating a pressing need for efficient recruitment processes that can identify the right talent for ever-evolving roles. This study focuses on improving the recruitment process for recent graduates by integrating Artificial Intelligence to enhance efficiency. The research addresses the question: “How can the integration of AI tools transform the recruitment process from its current state (“AS-IS”) to an enhanced Industry 5.0 future state (“TO-BE”)?”. To explore this, the study involved direct observation at a Portuguese office of a consultancy that is one of the largest multinational firms offering consulting services. It also included informal discussions with the human resources teams and a review of existing literature. The current recruitment process was mapped by using BPMN 2.0, followed by the design of an ideal future process, an AI-driven model. The results highlight how AI can streamline recruitment tasks, improve candidate selection, and enable more data-driven decisions, providing insights into the future of recruitment in an increasingly digital world.
Authors
- Juliana Salvadorinho (ORCID: https://orcid.org/0000-0001-8424-9310)
- Leonor Teixeira
- Ana Ferreira
Institutions
- University of Aveiro (PT)
Publication Details
- Journal
- Procedia Computer Science
- Published
- 2026-01-01
- DOI
- https://doi.org/10.1016/j.procs.2026.02.236
- Primary Topic
- Employer Branding and e-HRM
- Type
- article
- Field-Weighted Citation Impact
- 0.00