How connected networks, smarter collaboration, and AI are redefining how supply chains operate.
Supply chain leaders are navigating a moment unlike any before. Geopolitical volatility is redrawing trade corridors. Disruption has become the operating condition, not the exception. Transparency mandates are reaching deep into supplier networks. The cost of materials, transportation, and tariffs are all rising. And AI is advancing so rapidly that the gap between early movers and the rest is widening.
All of this must be navigated while simultaneously meeting corporate mandates to support growth and reduce costs, and an industry facing a talent shortage that makes executing this transformation harder still. The response cannot be incremental. It demands a fundamental rethink of how supply chains are designed and operated. Four shifts are defining what that rethink looks like in practice, each centered on a different dimension of collaboration, and each now achievable through advances in supply chain technology: multi-enterprise networks, multi-tier supplier transparency, enterprise alignment, and people working alongside AI.
Multi-enterprise collaboration
Companies have made significant investments in enterprise supply chain technology. Planning, warehouse automation, transportation management. Operations within the enterprise are becoming more sophisticated. However, how companies connect and collaborate across their supply networks has not kept pace. Data still moves through a fragmented patchwork of EDI connections, supplier portals, email threads, and spreadsheets, falling well short of the real-time visibility and cross-partner coordination the business needs.
The shift to connected supply chain operating networks replaces those fragmented connections with a shared environment where suppliers, logistics providers, and customers connect once and collaborate continuously. The result is an operating model where supply chains can sense risk earlier, respond faster, and flex to meet demand.
Multi-tier supplier transparency
For decades, supply chain networks connected companies to their Tier 1 and in some cases Tier 2 suppliers, enabling visibility and collaboration that improved agility, reduced costs, and assured supply. The promise was straightforward: remove inefficiencies, improve on-time delivery, and build stronger supplier relationships. That foundation delivered real value.
The scope of those networks has expanded significantly. Consumer demands for transparency, escalating risk in upper tiers, and a wave of new regulations are driving multi-tier visibility from a competitive advantage to an operational requirement. The Uyghur Forced Labor Prevention Act, the EU Deforestation Regulation, and the EU Digital Product Passport are becoming operational realities. Companies must now prove where and how products were made, whether to meet regulatory requirements, support product claims, or demonstrate that goods were not illegally transshipped to avoid tariffs.
The way companies respond will define whether they build capability or complexity. As supply chains work to break down silos, the compliance response is building new ones. Many companies are standing up disconnected processes and tools for every new requirement, increasing supplier fatigue and fragmenting the very data that should be driving insight. Traceability is not a sustainability workstream. It is a supply chain capability. The companies getting this right embed transparency requirements into existing trade workflows rather than building parallel infrastructure. In doing so they gain more than compliance. Those network connections become the foundation for deeper collaboration, reducing inefficiencies and waste throughout the supply network.
Aligning the enterprise
Managing today’s level of complexity, volatility, and competing business demands requires a new level of flexibility and internal alignment. When procurement, logistics, planning, and finance work from shared data toward shared objectives, supply chains can respond faster, reduce costs, and deliver better outcomes for the business and the customer. That alignment cannot happen across functions working from different data, different systems, and different views of the supply chain. Increasingly, leading organizations are addressing this through command centers that unify planning, logistics, procurement, and finance around a single view of the business. Supplier performance, logistics disruptions, market movements, and regulatory developments are synthesized into one coherent picture. When a port disruption occurs, the command center simultaneously assesses inventory positions, identifies affected customer commitments, and surfaces rerouting options. Decisions that once required days of cross-functional coordination are made faster and optimized for what is best for the business as a whole.
AI-powered operations
The volume of data, the speed of events, and the scale of decisions across today’s global supply chains has outpaced human bandwidth. This is where AI moves from interesting capability to operational necessity. From data acquisition to decision support to autonomous execution, AI is becoming core to how supply chains run.
It starts with trustable data. Without it, even the most sophisticated AI will amplify bad decisions rather than prevent them. AI validates and normalizes data as it enters the system, flagging gaps before they compound into bad decisions. Suppliers at any tier can submit what they have, a PDF, a compliance report, a spreadsheet extract. AI extracts, normalizes, and validates regardless of format or source. The barrier drops from building an integration to sharing a document.
Once data is flowing, AI assistants compress the time between data and decision by automatically performing analysis, summarizing information, and surfacing recommendations that help people make faster decisions. When a new tariff is announced, an AI assistant can immediately calculate the impact on landed costs, model alternative sourcing scenarios, and surface a recommended response, compressing days of analysis into minutes.
AI agents go further still, handling entire processes within functions and across them. Initially working alongside humans who review and approve before action is taken, agents progressively take on more autonomous execution as trust and data quality build, freeing supply chain professionals to govern outcomes rather than manage transactions. An inbound logistics agent, for example, continuously monitors shipment status, identifies priority delays, and automatically reroutes to protect customer commitments without waiting for human intervention. Next will be coordinating across enterprise boundaries, orchestrating across the entire supply chain.
From enterprise optimization to network orchestration
The forces are real. The technology is ready. The companies that will lead the next era are those that collaborate across their networks, align their enterprises, and commit to people and AI working together.
Heidi Benko is VP Product Marketing and Strategy at Infor.
Running Different: The Supply Chain Imperative
How connected networks, smarter collaboration, and AI are redefining how supply chains operate.
Supply chain leaders are navigating a moment unlike any before. Geopolitical volatility is redrawing trade corridors. Disruption has become the operating condition, not the exception. Transparency mandates are reaching deep into supplier networks. The cost of materials, transportation, and tariffs are all rising. And AI is advancing so rapidly that the gap between early movers and the rest is widening.
All of this must be navigated while simultaneously meeting corporate mandates to support growth and reduce costs, and an industry facing a talent shortage that makes executing this transformation harder still. The response cannot be incremental. It demands a fundamental rethink of how supply chains are designed and operated. Four shifts are defining what that rethink looks like in practice, each centered on a different dimension of collaboration, and each now achievable through advances in supply chain technology: multi-enterprise networks, multi-tier supplier transparency, enterprise alignment, and people working alongside AI.
Multi-enterprise collaboration
Companies have made significant investments in enterprise supply chain technology. Planning, warehouse automation, transportation management. Operations within the enterprise are becoming more sophisticated. However, how companies connect and collaborate across their supply networks has not kept pace. Data still moves through a fragmented patchwork of EDI connections, supplier portals, email threads, and spreadsheets, falling well short of the real-time visibility and cross-partner coordination the business needs.
The shift to connected supply chain operating networks replaces those fragmented connections with a shared environment where suppliers, logistics providers, and customers connect once and collaborate continuously. The result is an operating model where supply chains can sense risk earlier, respond faster, and flex to meet demand.
Multi-tier supplier transparency
For decades, supply chain networks connected companies to their Tier 1 and in some cases Tier 2 suppliers, enabling visibility and collaboration that improved agility, reduced costs, and assured supply. The promise was straightforward: remove inefficiencies, improve on-time delivery, and build stronger supplier relationships. That foundation delivered real value.
The scope of those networks has expanded significantly. Consumer demands for transparency, escalating risk in upper tiers, and a wave of new regulations are driving multi-tier visibility from a competitive advantage to an operational requirement. The Uyghur Forced Labor Prevention Act, the EU Deforestation Regulation, and the EU Digital Product Passport are becoming operational realities. Companies must now prove where and how products were made, whether to meet regulatory requirements, support product claims, or demonstrate that goods were not illegally transshipped to avoid tariffs.
The way companies respond will define whether they build capability or complexity. As supply chains work to break down silos, the compliance response is building new ones. Many companies are standing up disconnected processes and tools for every new requirement, increasing supplier fatigue and fragmenting the very data that should be driving insight. Traceability is not a sustainability workstream. It is a supply chain capability. The companies getting this right embed transparency requirements into existing trade workflows rather than building parallel infrastructure. In doing so they gain more than compliance. Those network connections become the foundation for deeper collaboration, reducing inefficiencies and waste throughout the supply network.
Aligning the enterprise
Managing today’s level of complexity, volatility, and competing business demands requires a new level of flexibility and internal alignment. When procurement, logistics, planning, and finance work from shared data toward shared objectives, supply chains can respond faster, reduce costs, and deliver better outcomes for the business and the customer. That alignment cannot happen across functions working from different data, different systems, and different views of the supply chain. Increasingly, leading organizations are addressing this through command centers that unify planning, logistics, procurement, and finance around a single view of the business. Supplier performance, logistics disruptions, market movements, and regulatory developments are synthesized into one coherent picture. When a port disruption occurs, the command center simultaneously assesses inventory positions, identifies affected customer commitments, and surfaces rerouting options. Decisions that once required days of cross-functional coordination are made faster and optimized for what is best for the business as a whole.
AI-powered operations
The volume of data, the speed of events, and the scale of decisions across today’s global supply chains has outpaced human bandwidth. This is where AI moves from interesting capability to operational necessity. From data acquisition to decision support to autonomous execution, AI is becoming core to how supply chains run.
It starts with trustable data. Without it, even the most sophisticated AI will amplify bad decisions rather than prevent them. AI validates and normalizes data as it enters the system, flagging gaps before they compound into bad decisions. Suppliers at any tier can submit what they have, a PDF, a compliance report, a spreadsheet extract. AI extracts, normalizes, and validates regardless of format or source. The barrier drops from building an integration to sharing a document.
Once data is flowing, AI assistants compress the time between data and decision by automatically performing analysis, summarizing information, and surfacing recommendations that help people make faster decisions. When a new tariff is announced, an AI assistant can immediately calculate the impact on landed costs, model alternative sourcing scenarios, and surface a recommended response, compressing days of analysis into minutes.
AI agents go further still, handling entire processes within functions and across them. Initially working alongside humans who review and approve before action is taken, agents progressively take on more autonomous execution as trust and data quality build, freeing supply chain professionals to govern outcomes rather than manage transactions. An inbound logistics agent, for example, continuously monitors shipment status, identifies priority delays, and automatically reroutes to protect customer commitments without waiting for human intervention. Next will be coordinating across enterprise boundaries, orchestrating across the entire supply chain.
From enterprise optimization to network orchestration
The forces are real. The technology is ready. The companies that will lead the next era are those that collaborate across their networks, align their enterprises, and commit to people and AI working together.
Heidi Benko is VP Product Marketing and Strategy at Infor.
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