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A Decision-Making Framework for Integrating Generative AI in Enterprise Workflows: Building vs. Buying

Author

Listed:
  • Alvertos, Konstantinos
  • Ioannou, Nikos
  • Kokkinis, Dimitris
  • Katsianis, Dimitris
  • Varoutas, Dimitris

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.

Suggested Citation

  • Alvertos, Konstantinos & Ioannou, Nikos & Kokkinis, Dimitris & Katsianis, Dimitris & Varoutas, Dimitris, 2025. "A Decision-Making Framework for Integrating Generative AI in Enterprise Workflows: Building vs. Buying," 33rd European Regional ITS Conference, Edinburgh, 2025: Digital innovation and transformation in uncertain times 331248, International Telecommunications Society (ITS).
    • Handle: RePEc:zbw:itse25:331248
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    References listed on IDEAS

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    1. Charles Hoffreumon & Chris Forman & Nicolas van Zeebroeck, 2024. "Make or buy your artificial intelligence? Complementarities in technology sourcing," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 452-479, March.
    2. Humaid Al Naqbi & Zied Bahroun & Vian Ahmed, 2024. "Enhancing Work Productivity through Generative Artificial Intelligence: A Comprehensive Literature Review," Sustainability, MDPI, vol. 16(3), pages 1-37, January.
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