Agentic AI

Supply Chain Insights has launched a dynamic supply chain benchmarking capability within AskLora, developed by Lora Cecere. The product uses a large language model and agent-based workflows to assess twenty maturity questions and generate an actionable benchmark in approximately eight to ten minutes.

The assessment combines six dimensions, including process maturity, organizational design, technology, AI readiness and financial performance. Its initial comparison set draws on thirteen years of research and the Supply Chains to Admire methodology.

Blue Yonder announced recognition as a Leader in the 2026 Gartner Magic Quadrant for Supply Chain Planning Solutions in discrete industries. Its current positioning emphasizes predictive, generative and agentic AI across planning and decision support.

RELEX Solutions published an evidence-oriented overview of Supply Chain AI, emphasizing agentic AI embedded within planning software and its role across complex, multi-stakeholder processes.

Gartner has published its 2026 Global Supply Chain Top 25, with Schneider Electric retaining first place ahead of NVIDIA and Walmart. The research highlights three major themes: autonomous workforces combining people and machines, adaptive physical networks and end-to-end orchestration.

The ranking points to a broader shift in how leading supply chains are evaluated. AI is moving beyond isolated features toward workforce design, connected decision-making and coordination across enterprise and partner networks.

Schneider Electric is cited for its use of generative and agentic AI to improve visibility, prediction and action coordination, making the ranking a useful market signal on the operating-model implications of Supply Chain AI.

Accenture is expanding its AWS business group with new AI products, including an autonomous Supply Chain capability built with Claude on Amazon Bedrock.

The product direction points toward multi-step agentic workflows rather than isolated copilots.

Sunstice has introduced Helios, an agentic AI layer for its supply-chain planning and revenue-growth-management platform. Helios is designed to reduce analytical workload, shorten decision cycles and support more continuous planning under persistent volatility.

The product uses specialized AI agents to diagnose supply-and-demand imbalances, investigate root causes, identify drivers of service and cost performance, and evaluate scenarios against business constraints. An Agent Builder also allows organizations to configure agent behavior around their own planning logic and decision structures.

Sunstice, formerly FuturMaster, introduced Helios, an agentic-AI layer intended to accelerate Supply Chain decisions under uncertainty. The broader platform connects Supply Chain Planning and Revenue Growth Management through one data model, one decision flow and one orchestration layer.

Pigment has rolled out an upgrade to its AI Agents. According to a LinkedIn post by Alexis Fromaget, Pigment’s Analyst, Modeler and Custom Agents can now pull live external context from the web during conversations and use it inside analyses, recommendations and model builds, with source citations included.

The update matters for Enterprise Planning because AI agents are moving from internal assistants toward context-aware planning collaborators. In supply chain and business planning, this can help teams connect internal models with external signals, market information, assumptions and supporting evidence.

For Supply Chain Planning, the relevant signal is not only faster analysis. It is whether external context can be used safely inside governed planning workflows, with traceability, source visibility and clear boundaries between recommendation, validation and execution.

Pigment has published details of Graphite, the patent-pending architecture underpinning its business planning platform. The company describes Graphite as the technology layer designed to support large-scale planning, governed data, real-time visibility and dynamic modeling for enterprise decision-making. The post was published on June 3, 2026 and updated on June 4, 2026.

Graphite is presented around three core pillars: an Elastic Engine for scale and continuous planning, unified and governed data, and Dynamic Modeling to help teams adapt structures, scenarios and relationships as business conditions change. Pigment also positions Graphite as relevant when planning is accessed through an MCP Server, where governance, shared definitions and a semantic layer become critical for both humans and AI agents.

For Supply Chain Planning and IBP teams, the announcement matters because it addresses a common bottleneck in planning modernization: how to combine scale, flexibility and control without fragmenting planning logic across spreadsheets, legacy systems and isolated AI tools. Pigment’s broader platform positioning includes Sales & Operations Planning and Demand & Inventory Planning use cases, alongside finance, sales and HR planning.

The Graphite announcement also connects to Pigment’s earlier 2026 AI planning push. In March 2026, Pigment announced its Modeler Agent and AI Intent Modeling, describing a shift where teams can express planning needs in natural language and generate governed, production-ready models and applications more quickly than through manual configuration.

KBRW shared that it presented how AI Agents are already creating value for large-scale supply chain operations during the Sagard NewGen 2026 Annual AGM. The signal is relevant because Sagard Europe described KBRW’s presentation as an illustration of the agentic AI shift for SaaS customers, including a deployment for a CAC 40 client. More details are available in the LinkedIn post.

For supply chain leaders, the practical relevance is the move from visibility and dashboards toward operational agents that can support exception handling, orchestration and guided action. In KBRW’s domain, this connects Order Management, Fulfillment Orchestration and Smart Steering.

ToolsGroup has launched Decion, an agentic AI platform designed to help planners continuously improve individual supply-chain decisions. The platform positions self-steering as a decision-by-decision model rather than a single fully autonomous planning process.

RELEX Solutions introduced agentic AI capabilities for supply planning diagnostics. The announcement matters because it moves AI closer to planning root-cause analysis, exception explanation and recommended action in retail and consumer goods supply chains.

For Supply Planning, the practical value is faster diagnosis of constraints, shortages and planning exceptions. The governance requirement is that agentic diagnostics remain explainable and that planners retain control over high-impact decisions affecting inventory, availability and service.

Accenture announced an investment in Aera Technology to support AI-enabled supply chains. The announcement is relevant because it connects decision intelligence, agentic workflows and large-scale supply chain transformation services.

For Supply Chain Planning and execution teams, the signal is that autonomous decision support is becoming a consulting and implementation priority, not only a vendor product narrative. Governance will be essential where AI can sense change, recommend action and execute decisions under human oversight.

o9 Solutions has published its approach to Responsible AI, positioning governance as an architectural requirement for enterprise planning agents rather than a separate policy layer. The article describes how o9 applies neuro-symbolic agentic capabilities across Demand Planning, Supply Planning, Commercial Planning and Integrated Business Planning.

The core message is that autonomy in planning needs explicit boundaries: named business ownership, technical ownership, role-based access control, audit logs, decision traces, stop mechanisms and drift monitoring. o9 links these controls to its Enterprise Knowledge Graph, which acts as the structured layer for rules, policies, lineage, constraints and decision context.

For supply chain leaders, the signal is practical: agentic AI in planning is moving from experimentation toward controlled deployment. The relevant question is no longer only whether an AI agent can recommend a plan, but whether the recommendation can be explained, stopped, audited and owned when it affects Inventory, service levels, margin or execution commitments.

Coupa has launched Compose and Catalyst to support the development, deployment and scaling of agentic AI across spend-management workflows. The tools are intended to help customers and partners create agents using Coupa data and process context.

Infios has announced new AI agents embedded into supply chain execution workflows. The agents are designed to operate across orders, warehouses and transportation, supporting orchestration inside operational processes rather than sitting outside them as standalone advisory tools.

The announcement is relevant for Supply Chain Execution because it moves agentic AI closer to real operational workflows: order orchestration, warehouse issue resolution, transportation updates and exception handling. Infios positions the agents as part of its broader execution stack across OMS, WMS and TMS environments.

For logistics and operations teams, the signal is that Agentic AI is moving beyond planning and analysis into time-sensitive execution decisions. This raises practical questions around autonomy, supervision, exception thresholds and how AI-driven actions are recorded inside operational systems.

Coupa highlighted Navi Agent Studio at Inspire 2026, positioning AI agents for autonomous and semi-autonomous tasks across business spend, procurement and supply chain workflows. The signal is relevant because supply chain design and procurement decisions are becoming increasingly AI-assisted.

For Supply Chain Design and planning teams, the practical value is the ability to guide modeling, analysis and decision workflows. The governance challenge is ensuring agents use approved assumptions, version-controlled models and human review before network or procurement decisions are executed.

Microsoft Dynamics 365 Supply Chain Management published guidance showing how agentic AI can connect supply chain data, decisions and execution workflows. The signal is relevant because Microsoft is embedding AI into the applications and productivity layer used by many planners and operations teams.

For Demand Planning, production planning and inventory teams, the practical value is reducing friction between analysis and action. The risk is that agents and copilots must remain bounded by approval workflows, data-quality rules and AI Governance.

E2open published guidance on agentic AI for supply chain management, including orchestrator, pre-built and custom agents embedded directly into supply chain applications. The signal is relevant because E2open’s network model extends AI decision support beyond internal planning teams.

For Connected Supply Chain operations, the practical value is coordinating decisions across demand sensing, logistics, channels, trade and partner workflows. The governance challenge is cross-company control: agents must respect data trust, approval boundaries and AI Governance across multiple organizations.

Logility has launched its Orchestration Center to connect planning, production, supplier management and transportation through real-time agentic workflows. The layer is designed to coordinate decisions and actions across functions rather than optimize each process in isolation.

SAP presented new agentic AI capabilities for manufacturing and supply-chain workflows at Hannover Messe 2026. The announcements connect business data, operational processes and AI-supported actions across industrial environments.

Blue Yonder published analysis connecting multi-enterprise visibility, AI and resilience across planning and execution. The signal is relevant because supply chain AI is moving beyond planning models toward operational coordination across warehouses, transport, retail and trading partners.

For Supply Chain Execution, the practical question is how predictive, generative and agentic AI recommendations travel across execution domains without creating local decisions that increase downstream risk. This makes AI Governance and exception ownership central to adoption.

Logility, now part of Aptean, announced DemandAI+ capabilities that position agentic AI inside supply chain planning workflows. The signal is relevant because planning vendors are moving from AI-assisted forecasting toward AI-supported exception analysis and recommended action.

For Demand Planning, the key question is whether agentic AI improves planner productivity while maintaining traceability of forecast drivers, overrides and business assumptions. This makes Planning Governance central to adoption.

GAINS reported record growth linked to demand for its AI-driven supply chain platform. The market signal is relevant because planning buyers are increasingly looking for decision automation, inventory optimization and agentic support rather than standalone forecasting tools.

For Supply Chain Planning, GAINS’ growth reinforces demand for platforms that connect demand, inventory, replenishment and S&OP decisions. The practical question is how capabilities such as DEO Agentic Agent are governed in daily planning workflows.

FourKites has launched Loft, an enterprise AI platform designed to orchestrate workflows across supply chain systems. The platform extends FourKites beyond visibility by connecting data, decisions and operational actions across enterprise applications.

Loft reflects the shift from monitoring disruptions toward coordinating responses across logistics and execution workflows.

Board and Microsoft highlighted agentic AI capabilities for enterprise planning. The signal for supply chain teams is that planning platforms are increasingly embedding AI agents into workflows that connect finance, operations and performance management.

For S&OP and IBP teams, the practical value is faster scenario support, insight generation and cross-functional planning alignment. The risk is that agents must be governed so that planning assumptions, approval workflows and Human-in-the-Loop controls remain visible.

Aptean has acquired OpsVeda, adding an AI-powered operations command center to its Logility portfolio. The acquisition supports a strategy connecting planning decisions with agentic operational execution.

SymphonyAI announced next-generation CINDE Merchandising Agents for retail, positioning Agentic AI inside weekly sales, promotions, new item launches and merchandising reset workflows.

For supply chain and retail planning teams, the practical signal is that AI is moving from analytics support toward workflow-level assistance. This matters for Retail Planning, Merchandising and replenishment decisions where recommendations need to be explained, validated and coordinated across stores, categories and supply chain operations.

More details are available in the SymphonyAI announcement.

Manhattan Associates has made its AI Agent Workforce commercially available across supply chain and omnichannel operations. The portfolio covers workflows in warehousing, transportation, stores and customer service, extending AI from assistance toward coordinated operational execution.

The announcement signals that agentic capabilities are moving into production environments where recommendations and actions can affect inventory, fulfillment and customer outcomes.

Kinaxis launched Maestro Agents, context-aware digital co-workers embedded in live planning environments to analyze issues, recommend actions and support faster decisions with human-in-the-loop safeguards.

OMP introduced UnisonIQ as an AI layer for supply chain planning and decision support. The signal for planners is that agentic and assistant-style capabilities are moving into advanced planning environments built around constraints, scenarios and feasible response options.

For Supply Chain AI, this is relevant because AI value depends on context: demand, supply, capacity, inventory and production constraints need to be understood before recommendations are trusted. UnisonIQ should therefore be evaluated through explainability, exception logic and Planning Governance.

project44 launched Tariff Analytics to link customer product catalogs with current U.S. tariff rates and support trade-risk analysis inside its agentic Decision Intelligence platform.

RELEX demonstrated agentic AI systems operating within no-code business rules to support unified retail and Supply Chain planning at NRF Europe 2025.

RELEX reported increased investment in Diagnostics, True Inventory and agentic AI capabilities during the first half of 2025, alongside customer expansion.

A Manhattan Associates study found that 61% of organizations expected fully autonomous agentic AI in transportation management within five years, while only 37% had deeply integrated AI and machine learning into their TMS.

Daybreak AI raised $15 million in Series A funding from investors including TPG Growth and Dell Technologies Capital, positioning itself around AI labor for enterprise planning.

The announcement is relevant because Daybreak’s agentic framing targets repeatable planning work, policy-based automation and exception routing back to humans. This connects AI Agents, Supply Chain Planning and human-in-the-loop governance.

More details are available in the funding announcement.