A Decision-Making Framework for Integrating Generative AI in Enterprise Workflows: Building vs. Buying
Year: 2025
Type: conference-paper
Abstract: The use of Generative AI (GenAI) in recent years has significantly reshaped workflows across multiple industries, enhancing productivity and competitiveness. Enterprises commonly face the strategic decision to either build proprietary GenAI solutions or buy these services from established vendors. This paper proposes a techno-economic quantitative decision-making framework designed to clarify the "build vs buy" dilemma by quantifying the value derived from GenAI implementations, based on the employee productivity increase. We introduce a model that evaluates the break-even point, the specific number of employees whose cumulative productivity gains justify transitioning from purchasing external GenAI services to building in-house solutions. Our analysis indicates that this threshold varies distinctly by departmental functions and organizational size. Ultimately, this research aims to equip enterprises with actionable insights to inform strategic decisions about GenAI investments.
Source: Econstor (Econstor)
Authors: Alvertos, Konstantinos, Ioannou, Nikos, Kokkinis, Dimitris, Katsianis, Dimitris, Varoutas, Dimitris
Institution: National and Kapodistrian University of Athens
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7113469934
