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The research aims to develop a tailored TCO model for enterprise AI systems that addresses the unique challenges in cost analysis.

February 14, 2026Open Access

AI Economics: Total Cost of Ownership Models for Enterprise AI — A Practitioner Framework

Key Points

The research aims to develop a tailored TCO model for enterprise AI systems that addresses the unique challenges in cost analysis.
Developed a four-phase TCO framework encompassing design, development, deployment, and operational costs.
Identified and analyzed hidden cost multipliers affecting total costs.
Conducted empirical validation across 47 enterprise AI implementations.
Organizations using the comprehensive TCO model reported 40-60% fewer budget overruns.
The new framework effectively highlighted cost areas often missed by traditional TCO approaches.

Abstract

Total Cost of Ownership (TCO) analysis for enterprise AI systems presents unique challenges that traditional IT TCO frameworks fail to address. This paper presents a comprehensive TCO model specifically designed for AI implementations, introducing the four-phase framework encompassing design, development, deployment, and operational costs, with attention to hidden cost multipliers. Empirical validation across 47 enterprise AI implementations reveals that organizations using comprehensive TCO models experience 40-60% fewer budget overruns.

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Authors

Oleh Ivchenko

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Odessa National Polytechnic University

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AI Economics: Total Cost of Ownership Models for Enterprise AI — A Practitioner Framework

Key Points

Abstract

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Authors

Actions

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References and Citations

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Connected Papers

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