Connecting first-order evidence to impact pathways
| First-order evidence | Corpus code | Second-order analytical theme | Link to impact pathway |
|---|---|---|---|
| “In early pilots, for example, some companies use AI agents to automate discrete tasks--such as generating initial forecasts or adjusting inventory parameters--while leaving final decisions and oversight to human experts.” (BCG_2026_Supply-Chain-Planning-2026_Why-AI-Alone-Isnt-Enough.pdf; sentence_index 153) | automation_only; discrete task allocation; human oversight | Work is divided into automatable task execution and retained human decision authority | Role design |
| “Organizations are using AI to augment planners by accelerating analysis and automating routine activities, while humans retain accountability for complex tradeoffs and high-impact decisions.” (BCG_2026_Supply-Chain-Planning-2026_Why-AI-Alone-Isnt-Enough.pdf; sentence_index 218) | mixed_auto_aug; division_of_labour; cognitive_complementarity | AI accelerates analysis and routine work while accountability remains attached to human experts | Role design |
| “It is about empowering planners with insights that go beyond numbers, enabling them to make strategic decisions that drive growth and resilience.” (Capgemini_2024.pdf; sentence_index 52) | augmentation_only; cognitive_complementarity | Human judgement is positioned as the strategic complement to AI-generated insight | Role design |
| “They are enabled by AI agents that make decisions and perform tasks without human intervention.” (Accenture_2025_Making-Autonomous-Supply-Chains-Real.pdf; sentence_index 80) | automation_only; autonomous task execution | AI action is located within bounded task segments that can be separated from human participation | Process boundaries |
| “By harnessing an AI agent solution from a US-based decision intelligence company, they automated routine decisions in inventory management while routing exceptions to human experts with contextual data, analysis and recommendations.” (WEF_2025_Frontier-Technologies-in-Industrial-Operations_The-Rise-of-Artificial-Intelligence-Agents.pdf; sentence_index 113) | mixed_auto_aug; division_of_labour; cognitive_complementarity; bounded_autonomy | Routine decisions are automated, while exceptions define the handoff back to human expertise | Process boundaries |
| “Over time, copilots will become standard, and narrowly scoped agents will automate specific decisions within clear guardrails.” (BCG_2026_Supply-Chain-Planning-2026_Why-AI-Alone-Isnt-Enough.pdf; sentence_index 165) | mixed_auto_aug; bounded_autonomy | Guardrails delimit where autonomous decision-making begins and ends | Process boundaries |
| “Various aspects of the supplier identification process can be automated by analyzing supplier performance metrics, price, delivery times, quality, reliability, and market assessment in real time.” (Alvarez-and-Marsal_2024_Generative-AI-in-Supply-Chain_Building-More-Resilient-Supply-Chains.pdf; sentence_index 50 | automation_only; metric-based process automation | AI-enabled work is evaluated through predefined operational and supplier-performance criteria | Performance measurement |
| “DHL has already pushed automation and AI through its warehouse and transport operations, where, among other things, it helps sequence orders, make the most of shipment space and predict volumes.” (DHL_2024_AI service agent.pdf; sentence_index 15) | automation_only; efficiency and prediction claims | Performance is framed as optimization of sequencing, capacity use, and forecast accuracy | Performance measurement |
| “Now, employees can ask the new digital AI assistant, Factory Genius, for help: It can suggest solutions for the specific system problem within seconds, reducing the time required for error diagnosis to a minimum.” (BMW Manufacturing_2025.PDF; sentence_index 4) | augmentation_only; speed and troubleshooting claim | AI value is expressed as faster diagnosis and more efficient decision support | Performance measurement |
| First-order evidence | Corpus code | Second-order analytical theme | Link to impact pathway |
|---|---|---|---|
| “In early pilots, for example, some companies use AI agents to automate discrete tasks--such as generating initial forecasts or adjusting inventory parameters--while leaving final decisions and oversight to human experts.” | automation_only; discrete task allocation; human oversight | Work is divided into automatable task execution and retained human decision authority | Role design |
| “Organizations are using AI to augment planners by accelerating analysis and automating routine activities, while humans retain accountability for complex tradeoffs and high-impact decisions.” | mixed_auto_aug; division_of_labour; cognitive_complementarity | AI accelerates analysis and routine work while accountability remains attached to human experts | Role design |
| “It is about empowering planners with insights that go beyond numbers, enabling them to make strategic decisions that drive growth and resilience.” | augmentation_only; cognitive_complementarity | Human judgement is positioned as the strategic complement to AI-generated insight | Role design |
| “They are enabled by AI agents that make decisions and perform tasks without human intervention.” | automation_only; autonomous task execution | AI action is located within bounded task segments that can be separated from human participation | Process boundaries |
| “By harnessing an AI agent solution from a US-based decision intelligence company, they automated routine decisions in inventory management while routing exceptions to human experts with contextual data, analysis and recommendations.” | mixed_auto_aug; division_of_labour; cognitive_complementarity; bounded_autonomy | Routine decisions are automated, while exceptions define the handoff back to human expertise | Process boundaries |
| “Over time, copilots will become standard, and narrowly scoped agents will automate specific decisions within clear guardrails.” | mixed_auto_aug; bounded_autonomy | Guardrails delimit where autonomous decision-making begins and ends | Process boundaries |
| “Various aspects of the supplier identification process can be automated by analyzing supplier performance metrics, price, delivery times, quality, reliability, and market assessment in real time.” ( | automation_only; metric-based process automation | AI-enabled work is evaluated through predefined operational and supplier-performance criteria | Performance measurement |
| “DHL has already pushed automation and AI through its warehouse and transport operations, where, among other things, it helps sequence orders, make the most of shipment space and predict volumes.” ( | automation_only; efficiency and prediction claims | Performance is framed as optimization of sequencing, capacity use, and forecast accuracy | Performance measurement |
| “Now, employees can ask the new digital AI assistant, Factory Genius, for help: It can suggest solutions for the specific system problem within seconds, reducing the time required for error diagnosis to a minimum.” | augmentation_only; speed and troubleshooting claim | AI value is expressed as faster diagnosis and more efficient decision support | Performance measurement |
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