What question did this study set out to answer?

The aim is to analyze how organizations can effectively measure and derive value from their AI investments.

February 14, 2026Open Access

The Enterprise AI Landscape — Understanding the Cost-Value Equation

Puntos clave

The aim is to analyze how organizations can effectively measure and derive value from their AI investments.
Analysis of current market structure in enterprise AI
Examination of cost categories associated with AI spending
Review of value measurement methodologies used by organizations
Development of strategic principles for successful AI implementation
Identified that 73% of organizations struggle to extract measurable value from AI investments
Outlined foundational frameworks for understanding enterprise AI economics
Distinguished successful AI implementations from costly failures

Resumen

Enterprise AI spending reached 154 billion globally in 2025, yet 73% of organizations report difficulty extracting measurable business value from their AI investments. This article establishes the foundational framework for understanding enterprise AI economics, examining the current market structure, cost categories, value measurement methodologies, and the strategic principles that separate successful implementations from expensive failures. Part of the Cost-Effective Enterprise AI 40-article research series.

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Authors

Oleh Ivchenko

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Odessa National Polytechnic University

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Connected Papers

Building similarity graph...

Analyzing shared references across papers

The Enterprise AI Landscape — Understanding the Cost-Value Equation

Puntos clave

Resumen

Citation Network

Connected Papers

Discussion

Authors

Actions

Institutions

References and Citations

Citation Network

Connected Papers

Discussion

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