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AI-Driven Business Process Automation in International Headhunting: Implementation of No-Code/Low-Code Solutions for Enhanced Operational Efficiency.
Rel. Domenico Augusto Francesco Maisano. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management), 2025
Abstract
This thesis investigates the transformative impact of AI-driven business process automation on the international headhunting industry, a sector characterized by significant operational complexities, legal hurdles, and scalability challenges. The central problem addressed is the pervasive inefficiency stemming from manual, time-intensive, and fragmented recruitment workflows that increase costs and limit strategic agility. Adopting a Design Science Research (DSR) methodology, this project centers on the creation, implementation, and rigorous evaluation of a portfolio of innovative IT artifacts. The research demonstrates the powerful synergy between Artificial Intelligence (AI), No-Code/Low-Code (NC/LC) platforms, and Business Process Management (BPM) principles to engineer a holistic solution. The core of this work is a bespoke, AI-powered automation ecosystem built on a secure, on-premises infrastructure, featuring a suite of targeted solutions that automate critical processes such as intelligent CV screening, automated content generation, and end-to-end lead management.
The implementation of these solutions yielded significant and quantifiable im provements in operational performance
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