The artificial intelligence investment boom of 2024–2026 has collided with an era of escalating geopolitical fragmentation. While global AI spending surpassed $300 billion in cumulative commitments by early 2026, the simultaneous intensification of chip e[REDACTED]rt controls, sovereign AI mandates, and regional conflicts has introduced a new class of repricing risk into AI capital allocation. ...
Container orchestration for AI workloads presents a unique economic challenge: the intersection of expensive hardware (GPUs), bursty demand patterns (training vs. inference), and the operational complexity of multi-tenant scheduling. This article provides a systematic analysis of Kubernetes cost optimization strategies for AI — from GPU partitioning and spot instance economics to autoscaling po...
The Anthropic Economic Index (Massenkoff & McCrory, 2026) identifies computer and mathematical occupations as theoretically the most AI-e[REDACTED]sed occupation group in the U.S. economy, with 94% of tasks rated as feasible for LLM acceleration. Yet observed automation covers only 33% of those tasks — producing a 61-percentage-point capability-adoption gap that is the largest absolute gap of a...
The frontier AI industry is consolidating at a pace that mirrors — and in some dimensions exceeds — the platform monopolization patterns of previous technology waves. As of early 2026, three providers control approximately 88% of enterprise AI API spending, with Anthropic commanding 40%, OpenAI 27%, and Google 21% of enterprise market share. Training costs for frontier models now exceed $100 mi...
The global semiconductor industry, projected to reach $1 trillion in revenue by late 2026, has become the primary arena for a new form of economic warfare: chip nationalism. Nations are pouring hundreds of billions of dollars into domestic fabrication capacity, driven not by comparative advantage but by strategic anxiety. This paper examines the economic cost structure of semiconductor reshorin...
The rapid deployment of autonomous AI agents across enterprise environments has introduced a novel category of insider threat that traditional cybersecurity frameworks are ill-equipped to address. According to the Thales 2026 Data Threat Report, 61% of organizations now cite AI as their top data security concern, while only 34% maintain visibility into where all their data resides. This article...
Paper 3 of 3 in the series "Shadow Economy Dynamics." Builds on Paper 1: Problem Landscape and Paper 2: Scenario Analysis.
In Paper 1 of this series (Ivchenko, Ivchenko & Grybeniuk, 2026a), we established that Ukraine's shadow economy has remained persistently high — between 30% and 45% of official GDP over the decade 2015–2025. We identified two competing feedback loops: a reinforcing cycle where high tax burdens push economic actors into informality, and a balancing mechanism where digitalization increases tr...
The Anthropic Economic Index (Massenkoff & McCrory, 2026) reveals a persistent and structurally significant anomaly: legal occupations exhibit only 15% observed AI e[REDACTED]sure despite theoretical automation potential that rivals software engineering. This article examines the economic architecture of that gap. Unlike healthcare, where clinical decision liability and FDA approval pathways cr...
Ukraine's shadow economy remains one of the largest in Europe, consistently estimated at 30–45% of official GDP over the past decade. This phenomenon directly undermines fiscal stability, distorts market competition, and complicates the country's path toward EU accession. The interaction between tax policy, digital governance, and informal economic activity forms a complex adaptive system where...