Data-Engineered Intelligence: An AI-Driven Framework for Scalable and Compliant Tax Consulting Ecosystems

Abstract

In this article, we present a conceptual framework for data-engineered intelligence to support tax consulting ecosystems. We illustrate how this framework can be used to increase the performance and compliance of process-driven services and to make strategies more accountable. To implement the framework in practice, we propose a three-layer architecture that integrates data-serving platforms, AI-assisted intelligence services, and process-driven consultation models. We illustrate the framework with examples and show the arising implications for the implementation of projects. With our research, we shed light on the rapid integration of AI with data analysis into management consulting projects and therefore impact both academic and empirical communities in a very direct way. For practitioners, our insights might stimulate discussions on how to redesign future tax consulting ecosystems to leverage the potential of AI. Our framework implies that services must be flexible, scalable, and compliant - characteristics that are sought after in addressing major challenges in the consulting industry today.