§ 40 — Use Cases
Use Cases
Pattern-level analyses of what works and what fails when supply-chain AI is applied to specific functions and techniques (demand forecasting, inventory optimization, procurement automation, warehouse computer vision), synthesized from the Post-Mortems and corroborated by cited external research (e.g., MIT CTL, SupplyChainBrain, peer-reviewed studies) rather than recycled unsourced industry statistics. Every claim carries a named source and date. Distinct from Post-Mortems (single-deployment accounts) and Readiness (task checklists): this section answers whether a category of AI application actually delivers, and under what conditions it fails, at a pattern level.
Failure pattern: grid-induced cloud outage risk
Source: Belfer Center, Schneider Electric Blog, arXiv
Failure pattern: unvalidated climate scenario modeling
Source: Everstream Analytics
Source: ClimateAi Hurricane Ian case study (2023)
Source: ClimateAi (2023) Hurricane Ian case study
Source: ClimateAi 2023, Clearframe Labs 2026, Kinaxis 2020, RELEX 2026
Failure pattern: image-prompt-injection
Source: CSA AI Safety Initiative, Shen et al., CrossMPI
Source: TrendForce, February 2026
Failure pattern: dependency chain compromise
Source: Cycode, StrikeGraph
Failure pattern: cash-timing gap between net-30 terms and compressed payment schedule
Source: Baker Donelson (2026)
Failure pattern: single-track-architecture
Source: Gartner, ICRON, RELEX, Deloitte
Failure pattern: vendor lock-in
Source: Viewpoint Analysis 2026, Gartner 2025, Lumenova AI 2026, SCMR 2026, Deloitte 2026
Failure pattern: regulatory volatility as non-first-class variable
Source: AI Consulting Network
Source: SiliconValley.com, Supply Chain Management Review
Failure pattern: architectural mismatch
Source: F22 Labs, HiveMQ, MindStudio
Source: Fortune, Business Insider, Object Edge, Palantir Impact, Ethicrithm, Equitable Growth
Source: Nature (2026) Passive heart-rate monitoring during smartphone use
Failure pattern: organizational barriers (trust, literacy, relevance)
Source: OpenAI People-First AI Fund grantees page and Inside Philanthropy analysis
Failure pattern: power as delay variable
Source: Data Center Knowledge, Introl, GEP
Source: Camaréna (2022) Frontiers in Sustainable Food Systems
Failure pattern: co-manufacturing compliance blind spot
Source: FDA Snapchill recall notice; SafetyChain; Food Logistics; Blue Yonder