Best AI Agents for Supply Chain in 2026: 14 Agents for Planning, Procurement, and Disruption Response

Blue Yonder and Kinaxis Maestro lead the enterprise planning half of this list, Keelvar and SAP's Joule agents own procurement and sourcing, and project44, FourKites, Pando, and Vorto handle transportation and exception response. Each is evaluated against one question a vendor homepage won't answer directly: does this agent call tools and take multi-step action inside your ERP or WMS, or does it just summarize a dashboard for a planner to act on. Every product below ships a verifiable agentic capability as of August 2026, not a roadmap slide, pricing claims were checked against each vendor's own site this month, and anything still in limited or phased rollout is labeled that way instead of presented as generally available.

This is the supply chain cut of our broader best AI agent platforms roundup; start there if a vertical agent isn't the right shape yet.

An agent runs multi-step work and calls tools on its own. An AI tool assists a person who's still doing the work themselves. That line matters more in supply chain than in most categories, because several names below also show up one level down, as assistive tools rather than agents, in our best AI tools for logistics roundup. Where a vendor appears in both guides, the entry below is scoped to its agentic layer specifically, not the underlying visibility or planning platform it's built on. If you'd rather build a narrower agent than buy a platform, the AI supply chain agent, AI inventory alert agent, and AI procurement agent blueprints walk through what to build and what data it needs.

Updated August 2026. This is a fast-moving corner of enterprise software. Since the start of the year: Kinaxis launched Maestro Agent Studio and plans an agent marketplace later in 2026; SAP pushed Joule past 40 agents, including a Production Planning and Operations Agent expected to autonomously release production orders once conditions are met; Oracle added four new Fusion Agentic Applications for inventory, supplier qualification, and manufacturing readiness; project44 launched a six-agent portfolio at its "decision44" event; FourKites shipped what it calls the first fully agentic ocean freight booking product; and Altana acquired Cervo AI to automate customs entry filing. Re-verify anything cost-critical with the vendor before you budget against it.

Key Facts

• Gartner forecasts spend on supply chain management software with agentic AI will grow from under $2 billion in 2025 to $53 billion by 2030, with 60% of enterprises using SCM software expected to adopt agentic AI features by then, up from just 5% in 2025 (Gartner, via Supply & Demand Chain Executive).
• 87% of operations and supply chain leaders say poor data quality has directly hampered progress on their digital and AI initiatives, and only 37% say they're comfortable assigning an AI agent to execute a full end-to-end process, per PwC's 2026 Digital Trends in Operations survey of 767 operations leaders.
• AI-enabled distribution operations see a 5-20% reduction in logistics cost and a 20-30% reduction in inventory, according to McKinsey's research on gen AI in supply chains.
• Gartner expects over 40% of agentic AI projects to be canceled by the end of 2027, citing unclear business value and inadequate risk controls ahead of raw cost.
• Only 6% of companies report having full visibility across their supply chain, despite ranking it among their top priorities, per a Geodis survey covered by Supply Chain Dive.
• 41% of supply chain companies are currently using AI, up from 30% a year earlier, according to MHI's 2026 Annual Industry Report.

Quick Comparison Table

What Actually Separates These Agents in 2026

Most teams evaluating this category make the mistake CRM buyers made a decade ago: they compare feature lists before answering three questions that determine fit.

1. Is this agent allowed to recommend, or is it allowed to commit? A tool that suggests a reorder quantity is a fundamentally different purchase than one that fires the purchase order or reroutes a container already at sea. Get this distinction wrong and you'll either under-trust an agent that's proven itself or over-trust one that hasn't.
2. Can your data actually support it? An agent that forecasts demand or flags a disruption is only as good as your lead-time accuracy and master data. Most of what looks like a model failure in this category is a data failure wearing a model's name.
3. Does it live inside your ERP and WMS, or sit beside them? SAP and Oracle both ship agents native to their own cloud suites. Kinaxis, o9, and the logistics-focused vendors sit on top of whatever ERP you already run. Neither approach is wrong, but picking the wrong one adds an integration project you didn't budget for.

Recommend vs. Commit: What Each Agent Is Actually Allowed to Do

Kinaxis is explicit about where it sits: its own materials describe Maestro Agents as built to "plan with you, not just for you," with human-in-the-loop guardrails on every recommendation. Blue Yonder describes the opposite design point on its own site: agents that "trigger governed actions against systems of record, WMS, TMS, OMS, not recommendations." Neither claim is wrong. They're different products built for different risk tolerances, and the honest answer to "which is better" is whichever one matches how much your organization actually trusts an agent today. Our broader look at autonomous AI agents ranks products on exactly this question across every category, not just supply chain.

Whatever you land on, pair a commit-capable agent with an AI agent observability tool so there's an audit trail for the day it does something you need to review. Only 21% of organizations have a mature governance model for autonomous agents, even though 73% name data privacy and security as their top AI risk, per Deloitte's State of AI in the Enterprise research. That gap is exactly where a rushed rollout goes wrong.

The Real Constraint Is Your Data, Not the Model

Every vendor on this list will demo a clean forecast or a perfectly timed disruption alert. What the demo doesn't show is what happens when your lead times haven't been updated since a supplier changed factories, or your SKU master has three different names for the same part across two warehouses. PwC's 2026 survey found 87% of operations and supply chain leaders say poor data quality has already hampered their AI progress, and only 30% report meaningful improvement in data quality and reliability even as investment climbs. That's the honest starting point for this whole category: before you evaluate which agent has the best forecast accuracy, evaluate whether your own lead-time and inventory data is clean enough for any agent to trust.

The stakes for getting this wrong are real. Supply chain disruptions lasting a month or longer now happen roughly every 3.7 years on average, and over a decade they can cost a company the equivalent of 45% of one year's profits, per McKinsey Global Institute research. An agent fed bad data doesn't just fail quietly. It gives a confident, wrong answer at the exact moment a disruption is compounding.

ERP and WMS Integration: The Practical Constraint

Two of the platforms below, SAP's Joule supply chain agents and Oracle's Fusion SCM agents, are native to the ERP they run inside: Joule ships inside your existing S/4HANA Cloud subscription, and Oracle's agents ship inside Fusion Cloud SCM. That depth is real, and it's also the whole limitation: an S/4HANA-native agent has little to offer a team running NetSuite or a non-SAP WMS. Kinaxis, o9, and Blue Yonder are built to sit on top of whatever ERP and WMS you already run, trading some of that native depth for portability across a multi-ERP estate, which is common after an acquisition or a regional rollout. The logistics-execution vendors, project44, FourKites, and Pando, sit a layer above both, connecting into SAP, Oracle, and NetSuite alike through APIs rather than living inside any one of them. If your actual bottleneck is security review rather than ERP fit, our broader enterprise AI agent platforms guide ranks platforms on certifications and governance instead.

1. Blue Yonder: Agents That Act, Not Just Advise

Blue Yonder's pitch for 2026 is explicit about which side of the recommend-versus-commit line it's on. Its AI agents, including a Network Ops Agent that traces multi-tier disruption impact through the bill of materials, a Warehouse Agent, a Shelf Ops Agent for retail space planning, and a new Inventory Ops Agent that speeds up supplier order approvals, run on a continuous see, analyze, decide, act loop. The company's own materials are direct about the design choice: agents "trigger governed actions against systems of record, WMS, TMS, OMS, not recommendations," built to close disruptions without waiting on a human in the loop.

That's a real advantage if your team already trusts Blue Yonder's outputs and wants the next step automated. It's a real risk if you don't. The company doesn't publish a separate agent price, and the base planning platform it sits on reportedly starts near $100,000 a year, scaling with SKU and location count, so budget the agent as an add-on to an already sizable contract.

Pricing: Not published for the agent layer. The base planning platform reportedly starts around $100,000/year and scales with SKU and location count, per our AI tools for logistics review. Contact sales for a quote.

Best for: Retailers and distributors already running Blue Yonder who want the next step in disruption response to happen automatically instead of waiting for a planner.

2. Kinaxis Maestro: The Human-in-the-Loop Counterpoint

Where Blue Yonder commits, Kinaxis holds the line at recommend. Maestro Agents are embedded in Kinaxis's concurrent planning environment and are built, in the company's own words, to "plan with you, not just for you." Every agent recommendation carries an explanation of the constraints and trade-offs behind it, and the action itself stays with the planner. Kinaxis introduced Maestro Agent Studio in limited availability in 2026, giving planning teams a no-code way to compose their own agents on the same data and workflows they already use, with a broader agent marketplace planned for later in the year.

Kinaxis reports concrete early results rather than aspirational ones: one pharmaceutical customer cut the clicks needed to identify an inventory risk from 40 to 4, and an electronics manufacturer saved planners more than 30 hours a month on reporting that used to be manual.

Pricing: Not published. Sold through direct enterprise sales; contact Kinaxis for a quote.

Best for: Planning teams that want AI recommendations inside their existing concurrent planning process, with a person confirming every action rather than an agent executing it.

3. o9 Solutions: One Knowledge Graph Behind Every Forecast

o9's agents are built on its Enterprise Knowledge Graph (EKG), which o9 describes as a system of record for planning knowledge that survives employee turnover: when an experienced planner leaves, the reasoning behind their historical decisions stays queryable instead of walking out the door with them. The agents combine generative and agentic AI with the EKG to answer three questions for a planner: what happened and why, what's likely to happen next, and what cross-functional action would improve the plan. That framing puts o9 firmly on the recommend side of the line. It's decision support for a human planner, not an agent that places an order on its own.

o9's customer base is exclusively multibillion-dollar global enterprises, with no publicly documented mid-market tier. Its 2026 operating model, called APEX, is built around what o9 calls agile, adaptive, and autonomous planning, but "autonomous" here describes the planning cycle speeding up, not an agent taking action without a person signing off.

Pricing: Not published. Enterprise-only; contact o9 for a quote.

Best for: Large multinational enterprises that want one explainable knowledge graph behind demand, supply, and cross-functional planning decisions.

4. SAP Joule Supply Chain Agents: Native to S/4HANA

SAP's Joule agents are the right starting point if your system of record is already S/4HANA. Among more than 40 Joule agents SAP has shipped or announced for 2026 across finance, HR, procurement, and supply chain, three are worth knowing by name: a Production Planning and Operations Agent that checks material and capacity availability and, in a phased Q1 2026 rollout, is expected to autonomously validate and release production orders once required conditions are met; an Order Reliability Agent that watches for fulfillment risk such as stock shortages or delivery delays and initiates corrective action before an order is actually missed; and a Supplier Onboarding Agent, launching in Q2 2026, that manages supplier invitations and progress on SAP Business Network.

Core Joule ships inside your existing RISE or GROW with SAP subscription at no separate line item, but heavier agent usage meters through SAP's AI Unit model on top, and SAP hasn't published a flat per-agent price. Outside the SAP ecosystem, none of this has much to offer.

Pricing: Core Joule ships inside existing RISE/GROW with SAP subscriptions; heavier agent consumption meters via SAP's AI Unit model on top. SAP hasn't published a flat per-agent price. Contact SAP for a quote.

Best for: S/4HANA-standardized enterprises that want supply chain agents built directly into the ERP they already run, not a third-party layer on top of it.

5. Oracle Fusion SCM Agents: Native to Fusion Cloud

Oracle runs the same playbook inside Fusion Cloud SCM. In June 2026, Oracle added four new Fusion Agentic Applications built as coordinated teams of specialized agents: an Inventory Planning Command Center that resolves stockouts and availability gaps, a Supplier Qualification Workspace that speeds up supplier onboarding and compliance checks, a Production Readiness Workspace that cuts manufacturing setup errors, and a Kanban Administrative Workspace for continuous, exception-based replenishment. Alongside those, Oracle's Inventory Optimization Advisor Agent recommends safety stock adjustments by analyzing service-level shortfalls, while its separate Inventory Tasking Agent goes further and assigns warehouse tasks to operators automatically based on skill and availability, a genuine commit action, just scoped to internal operations rather than spend.

Every Fusion Cloud customer gets a monthly allotment of Oracle's AI Units at no extra charge, with more capacity sold in packs on top, though Oracle hasn't published a flat per-agent fee.

Pricing: Bundled AI Unit allotment included with every Fusion Cloud subscription; additional capacity sold in packs. No flat per-agent price published. Contact Oracle for a quote.

Best for: Oracle Fusion Cloud SCM shops that want inventory and production agents native to the ERP they already run.

6. e2open: Multi-Enterprise Network Plus a Command-Generating Agent

e2open's advantage isn't a single company's four walls, it's the trading network sitting across them: suppliers, carriers, and trading partners connected on one platform, with AI applied across demand planning, global trade compliance, and transportation coordination. Its Harmony AI Agent takes a natural-language request from a planner and translates it into the specific application command needed to act on it, a genuinely useful decision-support layer for a platform with as many modules as e2open's, though it stops at generating the command rather than executing it unattended.

Pricing runs on two very different tracks. e2open's narrow Carrier Connectivity product starts at $549 a year with API access from $18,000 a year, but that entry tier doesn't include Harmony or the broader Enterprise Suite. The full suite, demand planning, global trade management, and transportation management together, is custom-quoted and undisclosed, with per-partner onboarding adding its own cost on top.

Pricing: Carrier Connectivity starts at $549/year (API access from $18,000/year), but the Enterprise Suite where Harmony runs is custom-quoted. Contact e2open for a quote.

Best for: Companies managing multi-tier supplier and trading-partner relationships that need trade compliance and planning on one connected network, not just their own four walls.

7. project44 Movement AI: Six Agents Built on a Decade of Tracking Data

project44 built its name on multimodal shipment visibility, covered in our AI tools for logistics roundup, and in 2026 it layered a genuinely agentic portfolio on top: a Freight Procurement Agent that benchmarks contracted rates against live market data and automates carrier selection, a Disruption Management Agent that scans global events and initiates a coordinated response before an exception escalates, a Network Operations Agent that resolves carrier data gaps automatically, an Exceptions Management Agent that detects and resolves shipment exceptions across modes, a Slot Booking Agent that manages dock appointment windows, and a Carrier Onboarding Agent that has handled nearly one million automated carrier communications to date.

project44's published results are specific rather than vague: the Network Operations Agent improved carrier data quality by up to 30% and cut resolution time by 75%, and an earlier version of the Freight Procurement Agent reported a 4.1% cut in freight spend with sourcing cycle times down as much as 75%.

Pricing: Not published. Contact sales for a quote.

Best for: Enterprise shippers already running project44's visibility platform who want to move from tracking disruptions to acting on them automatically.

8. FourKites Booking Connect: Autonomous Booking Inside a Threshold

FourKites' Booking Connect for Ocean is one of the cleanest examples of a commit-capable agent with a real guardrail attached. It digitizes carrier rate agreements into structured rate profiles, recommends a carrier across four dimensions (cheapest, fastest, a cost-time blend, and network reliability), and then places the booking itself, autonomously, but only within thresholds and rules an admin sets up front in plain language, which the agent then interprets and applies to every booking. It's built inside FourKites' Intelligent Control Tower, connecting to Order Twin and Inventory Twin data so a booking decision reflects actual stockout risk, not just the cheapest rate on offer.

That threshold model is worth studying even if you don't buy FourKites, because it's a workable answer to the recommend-versus-commit question: let the agent commit, but only inside a boundary a human already approved.

Pricing: Not published. Enterprise subscriptions reportedly start near $75,000/year, per our AI tools for logistics review. Contact sales for a quote.

Best for: Shippers who want autonomous booking execution without giving an agent unlimited authority, ocean freight specifically for now.

9. Pando (Pi): One Agent Team From Procurement to Payment

Pando's Pi is the broadest single agentic offering on this list in terms of the process it covers end to end: freight procurement across modes and geographies (spot and contract), dispatch planning that sets the optimal carrier and modal mix, and freight audit and payment, including invoice validation, discrepancy resolution, and paying the invoice itself. Pando is a two-time Gartner Visionary in the Magic Quadrant for Transportation Management Systems, and its "Logistics Services as Software" positioning is a direct pitch to replace a logistics services headcount line with agents rather than software a team merely uses.

That breadth is also what to interrogate in a pilot. An agent that both audits and pays a freight invoice carries real financial exposure if it's wrong, so ask specifically how disputes escalate before you hand over that step.

Pricing: Sales-led, no public tiers. Fulfillment Cloud is usage-based, tied to shipment or order volume. Contact Pando for a quote.

Best for: Manufacturers, distributors, and retailers that want to automate the full freight lifecycle from sourcing through payment, not just one step of it.

10. Vorto: The Most Autonomous Agent on This List

Vorto commits more decisions without a human than anything else here. Its Autopilot capability predicts demand, sources products from a supplier network automatically, and dispatches carriers and drivers, then reacts to disruptions by rerouting drivers and rescheduling deliveries within microseconds of a parameter changing, including tendering the load and processing payment. Vorto reports customers across energy, agriculture, food and beverage, and metals, including Halliburton, Cargill, Boston Beer, Procter & Gamble, and Nucor, and claims a 66% reduction in trucks needed, a 248% improvement in driver utilization, and $480 million in collective annual savings across its customer base. Those are vendor-reported figures, not independently audited, so treat them as a starting point for your own pilot math rather than a guarantee.

Vorto is the right answer only if your organization is genuinely ready for that level of autonomy, and the wrong first purchase if you haven't yet run a recommend-only agent long enough to trust the underlying data.

Pricing: Not disclosed. Demo and trial available; contact Vorto for a quote.

Best for: Asset-heavy operators (energy, agriculture, metals, food and beverage) ready for closed-loop automation from demand prediction through dispatch, not a phased rollout.

11. Keelvar (Kai): Autonomous Sourcing at Volume

Keelvar is the only vendor Gartner names in both Advanced Sourcing Optimization and Autonomous Sourcing in its 2026 Market Guide for Sourcing Applications, and its Kai agent is built specifically for the high-volume, repeatable sourcing events that eat a procurement team's week. Describe a sourcing request in plain language and Kai classifies the spend category, picks the sourcing approach (RFQ, eAuction, spot buy, or a direct award within preset limits), invites the relevant suppliers, runs the bidding process, evaluates responses against the specification, and recommends an award, without a procurement person managing the event start to finish. Across Keelvar's customer base, 85% of sourcing activity is now automated, and some events complete in under 15 minutes.

Note the phrase "recommends an award": for anything above the preset limit, a human still signs off. That's the approval gate this whole category needs, applied consistently rather than left to chance. If procurement's real bottleneck is the finance handoff after the award, not the sourcing event itself, our AI agents for finance roundup covers the accounts payable side specifically.

Pricing: Fully custom, not published. Contact Keelvar for a quote.

Best for: Procurement teams processing high volumes of repeatable RFQs, spot buys, or auctions that want most of that volume automated end to end.

12. Interos: Multi-Tier Risk Scoring, Not an Execution Agent

Interos belongs on this list for what it watches, not for autonomous action, and it's worth being direct about that distinction before you shop it as something it isn't. The platform monitors more than 400 million companies and scores supply chain relationships across six risk dimensions at once: financial health, cybersecurity posture, ESG compliance, geopolitical exposure, catastrophic event risk, and trade restrictions, rolled into a proprietary i-Score. That's genuinely useful signal for the disruption-monitoring slice of this category, and it's exactly the kind of input an execution agent elsewhere on this list should be consuming. It isn't itself an agent that reroutes a shipment or holds a purchase order.

Pricing: Not published. Contact Interos for a quote.

Best for: Procurement and risk teams that need continuous multi-tier supplier risk visibility feeding into other agents' or planners' decisions, not a platform that acts on its own.

13. Everstream Analytics: Sub-Tier Mapping and Predictive Scoring

Everstream sits in the same category as Interos, and the same honesty applies: it's a risk-intelligence platform, not an agent that takes action. Its Network Mapping builds a digital twin of a company's supplier network to uncover sub-tier relationships that don't show up in a standard vendor list, automated scorecards assess supplier vulnerability on an ongoing basis, and the platform layers AI and NLP over real-time data feeds to generate risk alerts. Everstream was ranked first in three of four use cases in Gartner's 2026 Critical Capabilities for Supplier Risk Management Solutions, which says more about the depth of its scoring than about any autonomous capability.

Pricing: Not published. Contact Everstream for a quote.

Best for: Teams that need deep sub-tier supplier mapping and predictive risk scoring to feed downstream planning or procurement decisions.

14. Altana (Atlas and Cervo): Agentic Trade Compliance

Altana Atlas is built as a shared, cross-company source of truth for global trade: mapping the provenance of goods, classifying them, and assigning the customs compliance attributes a shipment needs to clear. Its 2026 acquisition of Cervo AI pushed Atlas further toward genuine commit-level agentic work, automating the writing of customs entries, including government agency filings, directly from unstructured transactional data. That's a real agentic task, generating and filing a compliance document from raw data rather than just flagging that one is needed, which puts Altana closer to the commit end of this list than a typical risk-monitoring platform.

Pricing: Enterprise, custom. Not published. Contact Altana for a quote.

Best for: Importers, logistics providers, and customs brokers that want customs entry writing and trade compliance classification automated rather than done by hand.

Supply Chain AI Agent Buying Mistakes to Avoid

These mistakes are predictable, whether the buyer is evaluating a $50,000 pilot or a seven-figure rollout.

How to Choose: Decision Framework

Use this table as your final filter once you know whether you need an agent that recommends, one that commits, or a monitoring layer feeding both.

What to Do Next

Pick one agent, not the whole roadmap. If your organization has never let an AI agent touch a live decision, start with a recommend-only platform like Kinaxis or o9 and measure how often you'd have actually taken its suggestion before considering anything commit-capable. If you're further along and the real gap is execution speed, run a 60 to 90 day pilot on one narrow workflow (ocean booking, PO approval routing, disruption alerting) with a hard threshold on what the agent can do without sign-off, and widen that threshold only after it earns it. Before you shop any platform above, spend a week auditing your own lead-time and SKU data. It's the cheapest fix on this list, and the one that decides whether anything else here actually works.