Cost-Effective AI: Build vs Buy vs Hybrid — Strategic Decision Framework for AI Capabilities Author: Oleh Ivchenko Lead Engineer, Enterprise AI Division | PhD Researcher, ONPU Series: Cost-Effective Enterprise AI — Article 2 of 40 Date: February 2026 DOI: 10.5281/zenodo.18626731 | Zenodo Archive The build-versus-buy decision for AI capabilities requires strategic sophistication beyond traditional IT…
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AI Economics: Data Poisoning — Economic Impact and Prevention
📚 Academic Citation: Ivchenko, O. (2026). AI Economics: Data Poisoning — Economic Impact and Prevention. AI Economics Research Series. Odessa Polytechnic National University. DOI: 10.5281/zenodo.18626697 Abstract Data poisoning represents one of the most insidious and economically devastating threats to enterprise AI systems. Unlike traditional cybersecurity attacks that target infrastructure, data poisoning corrupts the fundamental learning…
The Enterprise AI Landscape — Understanding the Cost-Value Equation
Cost-Effective Enterprise AI Series | Article 1 of 40 | By Oleh Ivchenko DOI: 10.5281/zenodo.18625628 | Zenodo Archive Abstract Enterprise AI spending reached $154 billion globally in 2025, yet 73% of organizations report difficulty extracting measurable business value from their AI investments [1]. This disconnect between investment and return represents the central challenge of our…
AI Economics: Annotation Economics — Crowdsourcing vs Expert Labeling
📚 Academic Citation: Ivchenko, O. (2026). Annotation Economics: Crowdsourcing vs Expert Labeling in Enterprise AI. AI Economics Series. Stabilarity Research Hub, ONPU. DOI: 10.5281/zenodo.18625150 Abstract Data annotation represents one of the most underestimated cost centers in enterprise AI development. While organizations meticulously budget for infrastructure, talent, and model training, annotation costs frequently emerge as budget-breaking…
AI Economics: Data Quality Economics — The True Cost of Bad Data in Enterprise AI
AI Economics: Data Quality Economics — The True Cost of Bad Data in Enterprise AI Author: Oleh Ivchenko Lead Engineer, a leading technology consultancy | PhD Researcher, Odessa Polytechnic National University Series: Economics of Enterprise AI — Article 12 of 65 Date: February 2026 DOI: 10.5281/zenodo.18624306 | Zenodo Archive Data quality stands as the silent…
AI Economics: Data Acquisition Costs and Strategies — The First Economic Gatekeeper of Enterprise AI
📚 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 single model is trained…
AI Economics: Open Source vs Commercial AI — The Strategic Economics of Build Freedom
📚 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 provides…
AI Economics: Vendor Lock-in Economics — The Hidden Cost of AI Platform Dependency
📚 Academic Citation: Ivchenko, O. (2026). AI Economics: Vendor Lock-in Economics — 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 — The Hidden Cost of AI Platform Dependency Author: Oleh Ivchenko Lead Engineer, a leading technology consultancy | PhD Researcher,…
AI Economics: AI Talent Economics — Build vs Buy vs Partner
📚 Academic Citation: Ivchenko, O. (2026). AI Talent Economics — 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…
The Black Swan Problem: Why Traditional AI Fails at Prediction
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