Abstract

This study investigates how Artificial Intelligence (AI) is transforming task execution, resource allocation, and efficiency structures in neo–Professional Service Firms (neo-PSFs), with a particular focus on management consulting. We develop a novel task-based framework for consulting work that builds on the professional task taxonomy of Shao et al. (2025) and integrates consulting-specific literature. The resulting framework provides a refined categorization of consulting task types and enables a more granular understanding of how professional work is structured and governed in this domain.

Grounded in Resource Orchestration Theory (ROT), we examine how AI reshapes the structuring, bundling, and leveraging of human and technological resources within neo-PSFs. Empirically, the study draws on semi-structured expert interviews across hierarchical levels and organizational contexts in AI-enabled consulting firms. By systematically comparing conventional and AI-assisted task execution, we assess efficiency gains, time reallocation patterns, and implications for established staffing logics and pyramid-based turnover models.

Our findings extend ROT by conceptualizing AI-assisted task reallocation as a central orchestration mechanism that reconfigures the micro-foundations of professional service delivery. In doing so, the study advances theoretical understanding of AI-driven transformation in professional services work and provides actionable insights for balancing technological augmentation with the preservation of professional identity, quality standards, and client relationships in Management Consultancies.

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