What does this research mean for the field?

A multi-cloud strategy can optimize AI workloads while minimizing lock-in costs and enabling arbitrage opportunities. Novelty: ClaimNovelty.NOVEL_FINDING. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

The aim is to analyze the economic implications of multi-cloud strategies, focusing on arbitrage and lock-in costs.

March 3, 2026Open Access

Multi-Cloud Strategy Economics: Arbitrage, Lock-In Costs, and AI Workload Optimization

Key Points

The aim is to analyze the economic implications of multi-cloud strategies, focusing on arbitrage and lock-in costs.
Analyzed economic models related to multi-cloud strategies
Evaluated the impact of arbitrage on cost efficiencies
Assessed lock-in costs associated with cloud providers
Examined optimization techniques for AI workloads
Identified key arbitrage opportunities in multi-cloud settings
Outlined the cost implications of vendor lock-in
Demonstrated improved efficiencies in AI workload optimization through multi-cloud strategies

Abstract

Research article: Multi-Cloud Strategy Economics: Arbitrage, Lock-In Costs, and AI Workload Optimization

Multi-Cloud Strategy Economics: Arbitrage, Lock-In Costs, and AI Workload Optimization

Key Points

Abstract

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