π Academic Citation: Ivchenko, O. (2026). AI Economics: Open Source vs Commercial AI β 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 provides…
Category: AI Economics
AI Economics: Risk, Cost, and ROI Research by Oleh Ivchenko
AI Economics: Vendor Lock-in Economics β The Hidden Cost of AI Platform Dependency
π Academic Citation: Ivchenko, O. (2026). AI Economics: Vendor Lock-in Economics β The Hidden Cost of AI Platform Dependency. Economics of Enterprise AI Series. Odesa National Polytechnic University. DOI: 10.5281/zenodo.18620726 AI Economics: Vendor Lock-in Economics β The Hidden Cost of AI Platform Dependency Author: Oleh Ivchenko Lead Engineer, a leading technology consultancy | PhD Researcher,…
AI Economics: AI Talent Economics β Build vs Buy vs Partner
π Academic Citation: Ivchenko, O. (2026). AI Talent Economics β Build vs Buy vs Partner. AI Economics Series. Odesa National Polytechnic University. DOI: 10.5281/zenodo.18619213 Abstract The scarcity of qualified artificial intelligence talent represents one of the most significant economic constraints facing enterprises pursuing AI transformation. With global demand for AI practitioners outpacing supply by an…
AI Economics: Hidden Costs of AI Implementation β The Expenses Organizations Discover Too Late
AI Economics: Hidden Costs of AI Implementation β The Expenses Organizations Discover Too Late Author: Oleh Ivchenko Lead Engineer, a leading technology consultancy | PhD Researcher, Odessa Polytechnic National University Series: Economics of Enterprise AI β Article 7 of 65 Date: February 2026 DOI: 10.5281/zenodo.18617979 | Zenodo Archive Enterprise AI implementations routinely exceed initial budgets…
AI Economics: ROI Calculation Methodologies for Enterprise AI β From Traditional Metrics to AI-Specific Frameworks
π Academic Citation: Ivchenko, O. (2026). AI Economics: ROI Calculation Methodologies for Enterprise AI β From Traditional Metrics to AI-Specific Frameworks. AI Economics Series. Odesa National Polytechnic University. DOI: 10.5281/zenodo.18617078 Abstract Return on Investment (ROI) calculation for artificial intelligence projects presents unique methodological challenges that traditional IT investment frameworks fail to adequately address [2]. Drawing…
AI Economics: TCO Models for Enterprise AI β A Practitioner’s Framework
π Academic Citation: Ivchenko, O. (2026). AI Economics: Total Cost of Ownership Models for Enterprise AI β A Practitioner’s Framework. AI Economics Series. Odesa National Polytechnic University. DOI: 10.5281/zenodo.18616503 Series: Economics of Enterprise AI β Article 5 of 65 Author: Oleh Ivchenko | PhD Researcher, Odessa Polytechnic National University Date: February 2026 Abstract Total Cost…
AI Economics: Economic Framework for AI Investment Decisions
AI Economics: Economic Framework for AI Investment Decisions Author: Oleh Ivchenko Building economic frameworks for enterprise AI investment decisions Lead Engineer, a major technology consultancy | PhD Researcher, ONPU Series: Economics of Enterprise AI β Article 4 of 65 Date: February 2026 DOI: 10.5281/zenodo.18616115 | Zenodo Archive Economic framework architecture for AI investment decisions integrating…
AI Economics: Risk Profiles β Narrow vs General-Purpose AI Systems
AI Economics: Risk Profiles β Narrow vs General-Purpose AI Systems Author: Oleh Ivchenko Understanding risk profiles of narrow vs general-purpose AI systems AI Architect | PhD Researcher, ONPU Series: Economics of Enterprise AI β Article 3 of 65 Date: February 2026 Abstract Enterprise AI systems exhibit fundamentally different risk profiles depending on their architectural paradigm….
AI Economics: Structural Differences β Traditional vs AI Software
The Day the Code Stopped Making Sense 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 workedβbrilliantly, in factβcatching…
Enterprise AI Risk: The 80-95% Failure Rate Problem β Introduction
π Academic Citation: Ivchenko, O. (2026). The 80-95% AI Failure Rate Problem: Enterprise AI Risk Analysis. AI Economics Series. Stabilarity Research Hub, ONPU. DOI: Pending Zenodo registration Executive Summary Enterprise artificial intelligence initiatives fail at rates between 80% and 95%βa staggering statistic that dwarfs failure rates in traditional software development. Despite billions in investment, most…






