Category: AI Economics

AI Economics: Risk, Cost, and ROI Research by Oleh Ivchenko

AI Economics: Data Acquisition Costs and Strategies — The First Economic Gatekeeper of Enterprise AI

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AI Economics by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18623221  53stabilfr·wdophcgmx
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Academic Citation: Ivchenko, O. (2026). AI Economics: Data Acquisition Costs and Strategies — The First Economic Gatekeeper of Enterprise AI. AI Economics Series. Odesa National Polytechnic University. DOI: 10.5281/zenodo.18623221 Abstract Data acquisition represents the foundational economic challenge of enterprise AI implementation, often consuming 40-80% of total project budgets before a sin...

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AI Economics by Oleh Ivchenko DOI: 10.5281/zenodo.18623221 53stabilfr·wdophcgmx
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AI Economics: Open Source vs Commercial AI — The Strategic Economics of Build Freedom

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AI Economics by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18622040  58stabilfr·wdophcgmx
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Score = Ref Trust (62 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

Academic Citation: Ivchenko, O. (2026). AI Economics: Open Source vs Commercial AI — The Strategic Economics of Build Freedom. AI Economics Series. Odesa National Polytechnic University. DOI: 10.5281/zenodo.18622040 Abstract The choice between open source and commercial AI solutions represents one of the most consequential economic decisions enterprise leaders face today [1]. This paper provide...

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AI Economics by Oleh Ivchenko DOI: 10.5281/zenodo.18622040 58stabilfr·wdophcgmx
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AI Economics: Vendor Lock-in Economics — The Hidden Cost of AI Platform Dependency

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AI Economics by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18620726  56stabilfr·wdophcgmx
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Score = Ref Trust (59 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

Vendor lock-in represents one of the most underestimated economic risks in enterprise AI adoption, with switching costs typically ranging from 2.3x to 5.7x the original implementation investment.

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AI Economics by Oleh Ivchenko DOI: 10.5281/zenodo.18620726 56stabilfr·wdophcgmx
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[t]Trusted87%✓≥80% from verified, high-quality sources
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AI Economics: AI Talent Economics — Build vs Buy vs Partner

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AI Economics by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18619213  53stabilfr·wdophcgmx
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[m]Diagrams7✓Mermaid architecture/flow diagrams. Current: 7
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (54 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

*Scarcity Index: Composite score (1-10) based on demand/supply ratio, salary growth, and time-to-fill

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AI Economics by Oleh Ivchenko DOI: 10.5281/zenodo.18619213 53stabilfr·wdophcgmx
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Score = Ref Trust (54 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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AI Economics: Hidden Costs of AI Implementation — The Expenses Organizations Discover Too Late

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AI Economics by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18617979  64stabilfr·wdophcgmx
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Score = Ref Trust (73 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

Enterprise AI implementations routinely exceed initial budgets by 40-75%, a pattern I have observed repeatedly across my 14 years in software engineering and 7 years specializing in AI systems at a leading technology consultancy. While organizations meticulously plan for obvious expenses such as infrastructure, licensing, and talent acquisition, they consistently underestimate or completely ove...

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AI Economics by Oleh Ivchenko DOI: 10.5281/zenodo.18617979 64stabilfr·wdophcgmx
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Score = Ref Trust (73 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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AI Economics: ROI Calculation Methodologies for Enterprise AI — From Traditional Metrics to AI-Specific Frameworks

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AI Economics by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18617078  57stabilfr·wdophcgmx
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Score = Ref Trust (60 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

Return on Investment (ROI) calculation for artificial intelligence projects presents unique methodological challenges that traditional IT investment frameworks fail to adequately address [2]. Drawing from fourteen years in enterprise software development and seven years of AI research, this article presents a comprehensive analysis of ROI calculation methodologies specifically designed for ente...

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AI Economics by Oleh Ivchenko DOI: 10.5281/zenodo.18617078 57stabilfr·wdophcgmx
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[t]Trusted88%✓≥80% from verified, high-quality sources
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[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]8%✗≥60% of references from 2025–2026. Current: 8%
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[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (60 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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AI Economics: TCO Models for Enterprise AI — A Practitioner’s Framework

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AI Economics by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18616503  63stabilfr·wdophcgmx
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Score = Ref Trust (71 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

Total Cost of Ownership (TCO) analysis for enterprise AI systems presents unique challenges that traditional IT TCO frameworks fail to address adequately. This paper presents a comprehensive TCO model specifically designed for AI implementations, drawing on my fourteen years of enterprise software experience and seven years of AI research at a leading technology consultancy. I propose a four-ph...

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AI Economics by Oleh Ivchenko DOI: 10.5281/zenodo.18616503 63stabilfr·wdophcgmx
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[t]Trusted89%✓≥80% from verified, high-quality sources
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[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
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[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (71 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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AI Economics: Economic Framework for AI Investment Decisions

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AI Economics by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18616115  63stabilfr·wdophcgmx
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[t]Trusted93%✓≥80% from verified, high-quality sources
[a]DOI66%○≥80% have a Digital Object Identifier
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[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]5%✗≥60% of references from 2025–2026. Current: 5%
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[m]Diagrams6✓Mermaid architecture/flow diagrams. Current: 6
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (70 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

Enterprise artificial intelligence investments present unique economic challenges that traditional capital budgeting frameworks fail to adequately address. This article develops a comprehensive economic framework specifically designed for AI investment decisions, integrating uncertainty quantification, option value analysis, and dynamic portfolio optimization. Drawing from fourteen years of sof...

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AI Economics by Oleh Ivchenko DOI: 10.5281/zenodo.18616115 63stabilfr·wdophcgmx
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[t]Trusted93%✓≥80% from verified, high-quality sources
[a]DOI66%○≥80% have a Digital Object Identifier
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[l]Academic52%○≥80% from journals/conferences/preprints
[f]Free Access55%○≥80% are freely accessible
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[w]Words [REQ]4,212✓Minimum 2,000 words for a full research article. Current: 4,212
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18616115
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]5%✗≥60% of references from 2025–2026. Current: 5%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams6✓Mermaid architecture/flow diagrams. Current: 6
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (70 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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AI Economics: Risk Profiles — Narrow vs General-Purpose AI Systems

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AI Economics by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18665626  55stabilfr·wdophcgmx
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[s]Reviewed Sources17%○≥80% from editorially reviewed sources
[t]Trusted83%✓≥80% from verified, high-quality sources
[a]DOI23%○≥80% have a Digital Object Identifier
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Enterprise AI systems exhibit fundamentally different risk profiles depending on their architectural paradigm. This paper presents a comprehensive economic analysis comparing narrow AI systems—purpose-built for specific tasks—with general-purpose AI (GPAI) systems, particularly large language models and foundation models that have proliferated since 2022. Drawing from 14 years of enterprise sof...

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AI Economics by Oleh Ivchenko DOI: 10.5281/zenodo.18665626 55stabilfr·wdophcgmx
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[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
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AI Economics: Structural Differences — Traditional vs AI Software

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AI Economics by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18665628  34stabilfr·wdophcgmx
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In March 2022, a senior architect at a Fortune 500 financial services firm stood before his team with a troubling admission. His organization had spent $47 million over three years building what they called "the most sophisticated fraud detection system in the industry." The system worked—brilliantly, in fact—catching 23% more fraudulent transactions than their previous rule-based approach. But...

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AI Economics by Oleh Ivchenko DOI: 10.5281/zenodo.18665628 34stabilfr·wdophcgmx
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