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From Automation to Agency: A New Era of Supply Chain Intelligence – How Agentic AI is Redefining Value in Manufacturing Supply Chains

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From Automation To Agency: A New Era Of Supply Chain Intelligence – How Agentic Ai Is Redefining Value In Manufacturing Supply Chains

Across manufacturing and process industries, supply chains are operating under intense pressure. Demand and market volatility, disruptions in materials, and a persistent need to “do more with less” have made supply chain agility critical.

Manufacturers have quickly embraced automation on the shop floor, including drones, robots, and sensors optimizing production lines. Yet when it comes to supply chain planning and execution, many organizations still rely on manual analysis, human judgement and delayed decision-making cycles. This is where artificial intelligence, and especially Agentic AI, is emerging as a transformative force.

Modern supply chains are extraordinarily complex. Every decision – whether to reroute shipments, hedge against raw material price changes, or adjust production schedules – ripples through a web of suppliers, logistics partners, and markets.

Traditional approaches to automation and analytics can sometimes struggle to keep pace with this speed and scale. Far too often, planners today are saddled by outdated technology and processes which means they can spend days running reports, generating recommendations, and reconciling data before decisions reach leadership. By then, the window for action may already have closed.

Modern supply chain planning platforms have significantly accelerated the time to make decisions and now agentic AI has the opportunity to take this to the next level. Instead of waiting for people to request insights or write data queries, agents can act autonomously, analyzing, correlating, and recommending actions in near real time. They operate at the speed of business, turning insight into decision at machine speed. insight into decision at machine speed.

What Makes Agentic AI Different?

While most people associate AI in the enterprise with chatbots or assistants, Agentic AI is much more advanced. Beyond simply answering questions, AI agents are part of an intelligent system that perceives, reasons, and acts toward defined business goals. They learn from new data, adapt to changing conditions, and connect both structured and unstructured signals.

AI agents can operate with a goal-seeking mindset: determining not just what’s happening, but what should be done next and why.

For supply chain leaders, that means moving from reactive analysis to proactive decision making. For example, you can ask an AI agent: “Which items have the most urgent supply chain issues right now—and what’s driving them?” In just a moment, the agents can query multiple databases, correlate external data such as commodity price swings, and return a recommendation complete with impact analysis and confidence levels.

Agentic AI Use Cases

Agentic AI’s potential stretches across every layer of the supply chain. Some real world applications include:

Prescriptive Recommendations: Move beyond rigid “if/then” exception management. Agents can generate adaptive, open-ended recommendations based on live data, guiding planners through what to prioritize and how to act. Rather than static rules, recommendations dynamically change to meet objectives and to inject planner preferences.
Root Cause Analysis: When forecasts miss the mark or supply shortages appear, agents can trace contributing factors across demand signals, supplier performance, and market data, explaining why it happened and how to prevent recurrence. This rapid analysis cuts planning time cycles across S&OE and S&OP to support decision-driven, not calendar-driven schedules.
Support for Sales & Operations Execution (S&OE): Agents can monitor the environment, flag issues early and quickly suggest and orchestrate corrective actions to maintain service levels. Autonomous agents can ingest sales, market, weather, operations, shop-floor, transportation and more and then orchestrate decisions and actions (e.g. re-prioritize a work order, re-route a shipment) with internal and external parties.
Hedging Decisions: Too often, hedging is guided by memory or habit, regardless of how well the decision is performed. Agentic AI can leverage its memory of previous decisions, assumptions and outcomes to provide context to evaluate options and support better-informed decisions.
Process Manufacturing Optimization: In industries with multiple formulations, speed and temperature profiles, optimization can be overwhelming. Agentic AI can navigate this multi-variable complexity, testing scenarios and identifying optimal configurations in ways even seasoned planners find difficult to replicate manually.

Crucially, Agentic AI also helps reduce human decision-making fallacies that often undermine supply chain performance. People tend to overvalue recent experiences, assume past successes guarantee future success (gambler’s fallacy), or cling to outdated strategies due to prior investment (sunk-cost bias). Agentic systems, by contrast, evaluate every scenario through an objective data-backed lens. And it can learn from feedback and historical outcomes.

Agent-based simulations can also model and stress-test supply chain scenarios using probabilistic reasoning to present evidence-based scenarios. This means planners can explore multiple “what-if” scenarios instantly, understanding both potential outcomes and the probability of success, as well as the risk and value created by decisions.

Building Trust Through Explainability

For AI to drive value, it must be trusted. In particular, in manufacturing environments with deep complexity and decisions impacting safety, compliance, and profitability – explainability is non-negotiable.

It’s key to embrace a planning solution where Agentic AI emphasizes governance through human-in-the-loop controls, and every recommendation is transparent, traceable, and subject to review before execution. Decision-makers can see why a specific plan was generated, which data informed it, and how alternative actions might affect outcomes.

This combination of autonomy and accountability helps organizations adopt AI responsibly. It ensures that technology amplifies human judgment, rather than replacing it. Over time, consistent, explainable recommendations build confidence, transforming skepticism into strategic trust.

Readiness and Culture

Beyond technology, adopting the latest AI innovations requires organizational readiness. Teams must be empowered to collaborate with AI, interpreting recommendations and shaping continuous improvement. This may require skills development to achieve AI fluency, and a culture that values experimentation and learning.

To build a strong culture around AI, leaders should ask:

Are we fostering a culture that views AI as a partner in problem-solving rather than a threat to established roles?
Do our teams understand how AI decisions are made and when to challenge them?
Are we recruiting or developing talent with AI expertise?

Agentic AI is set to transform decision speed and confidence. But success starts with clarity. Leaders must define the problems to solve, and the value they want to create. It’s not about chasing hype, or deploying AI for its own sake, to see what happens. It’s about focusing intelligence where it delivers the most impact, reducing lag time, increasing resilience, and unlocking new performance frontiers.

Is your organization ready to incorporate AI into your decision-making DNA?

About the Author:

Matt Hoffman is the Vice President of Product and Industry Solutions at John Galt Solutions. Matt specializes in delivering transformational from analysis through execution across a diverse range of clients in manufacturing, distribution, and retail. Matt is committed to ensuring that processes drive solution adoption, resulting in measurable outcomes. Throughout his career, Matt has successfully led software implementations utilizing best-in-class supply chain planning systems, execution systems, and merchandising planning systems.

The post From Automation to Agency: A New Era of Supply Chain Intelligence – How Agentic AI is Redefining Value in Manufacturing Supply Chains appeared first on Logistics Viewpoints.

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Ocean rates tick up to close the year as air peak fades – December 30, 2025 Update

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Ocean rates tick up to close the year as air peak fades – December 30, 2025 Update

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Published: December 30, 2025

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Weekly highlights

Ocean rates – Freightos Baltic Index

Asia-US West Coast prices (FBX01 Weekly) increased 1% to $2,145/FEU.

Asia-US East Coast prices (FBX03 Weekly) increased 10% to $3,364/FEU.

Asia-N. Europe prices (FBX11 Weekly) increased 1% to $2,742/FEU.

Asia-Mediterranean prices (FBX13 Weekly) increased 4% to $4,004/FEU.

Air rates – Freightos Air Index

China – N. America weekly prices decreased 16% to $6.26/kg.

China – N. Europe weekly prices decreased 5% to $3.52/kg.

N. Europe – N. America weekly prices decreased 14% to $2.16/kg.

Analysis

Ocean rates on the major East-West lanes trended up to close the year. Asia – Europe prices increased 1% last week to $2,742/FEU but are 12% higher than mid-month and are up to levels last seen at the tail end of peak season. Asia – Mediterranean rates climbed 4% to reach the $4,000/FEU mark for the first time since early July, with prices 20% higher than during the first half of the month.

Current rate levels are supported by an early start to pre-Lunar New Year demand on these lanes as shippers face longer lead times due to Red Sea diversions. As such, prices are likely to stay elevated or continue climbing as we get closer to the holiday.

Periodic GRIs since October have generally been less successful in keeping rates elevated for very long on transpacific lanes than they’ve been for Asia – Europe trades. Price hikes since mid-December have pushed West Coast rates up 9% to $2,145/FEU and raised prices to the East Coast 15% to $3,364/FEU. But rates will be under upward pressure when transpacific pre-LNY demand picks up, and prices increased to start both 2024 and 2025. The holiday begins later than usual – February 17th – this year, which could mean another rate slide in the near term before demand increases. But if volumes do start to rise to start the new year, rate levels should keep climbing too.

Despite transpacific ocean import contractions and an overall dip in US ocean imports due to the trade war this year, ex-Asia volume strength to Europe, Africa and LATAM – as China diversified trading partners – saw global volumes grow 4% through early Q4.

S&P projects US ocean imports will fall again, by 2%, in 2026, making 2025-2026 – after the 2008-2009 financial crisis years and the 2022 – 2023 unwind from the pandemic – the third instance of consecutive years of US container import contraction over the last two decades. Like this year, observers like BIMCO expect global volumes will continue to grow nonetheless.

Freightos Air Index shows air cargo rates fading post peak season. China-US prices fell 16% to about $6.25/kg, its lowest level since early November. South East Asia – US rates fell 19% to $4.60/kg and transatlantic prices dropped 14% to $2.16/kg. China – Europe prices slid 5% to $3.52/kg and SEA – Europe rates decreased more than 20% to $3.12/kg.

IATA estimates that – after sharp, e-commerce-driven, 11% growth in 2024 – 2025 global air volumes will be 3.1% stronger than last year. IATA also expects this year’s resilience to stretch into 2026 in the form of 2.6% annual growth. Opinions differ as to whether cargo capacity growth will outpace volume growth next year or not, making rate projections for next year difficult as well.

Best wishes for a happy new year

Discover Freightos Enterprise

Freightos Terminal: Real-time pricing dashboards to benchmark rates and track market trends.

Procure: Streamlined procurement and cost savings with digital rate management and automated workflows.

Rate, Book, & Manage: Real-time rate comparison, instant booking, and easy tracking at every shipment stage.

Judah Levine

Head of Research, Freightos Group

Judah is an experienced market research manager, using data-driven analytics to deliver market-based insights. Judah produces the Freightos Group’s FBX Weekly Freight Update and other research on what’s happening in the industry from shipper behaviors to the latest in logistics technology and digitization.

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The post Ocean rates tick up to close the year as air peak fades – December 30, 2025 Update appeared first on Freightos.

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Securing the Chain: The Executive Roadmap to Cyber Resilience

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Securing The Chain: The Executive Roadmap To Cyber Resilience

Call to Action: Download the full guide to gain in-depth insights and practical frameworks that will help you lead the transformation towards a resilient supply chain.

Part 10

Over the past nine sections, we have explored the threats, architectures, governance models, data protections, human factors, response strategies, and partnerships required to secure today’s global supply chains.

But executives don’t just need analysis. They need a roadmap, a structured, actionable framework for building resilience step by step.

This final section offers that roadmap. It is designed for boards, CEOs, CSCOs, and CISOs who must align strategy, investment, and execution to ensure their organizations not only withstand cyber shocks but turn resilience into a competitive differentiator.

1. Principles of the Roadmap

The roadmap is built on five guiding principles:

Resilience, not just security. Assume breaches will happen, plan for rapid recovery.
Ecosystem mindset. Protect not just your company, but the partners who form your chain.
Continuous adaptation. Threats evolve; resilience must be a living system.
Shared responsibility. Cyber resilience spans IT, OT, procurement, logistics, legal, HR, and the C-suite.
Value creation. Resilience isn’t a cost center; it drives trust, revenue protection, and investor confidence.

2. The Five Phases of the Executive Roadmap

Phase 1: Assess

Risk Mapping: Identify critical assets (ERP, WMS, TMS, OT systems) and map interdependencies.
Threat Assessment: Analyze the most relevant attack vectors for your sector.
Gap Analysis: Benchmark against frameworks (NIST, ISO 27001, CMMC).
Supplier Review: Audit third- and fourth-party cyber practices.
Board Engagement: Ensure cyber risks are regularly reviewed in board meetings.

Deliverable: Enterprise-wide cyber risk baseline.

Phase 2: Build

Zero Trust Implementation: Segmentation, IAM, MFA, privileged access controls.
Secure-by-Design Systems: Embed cyber requirements into procurement contracts.
Data Safeguards: Encryption, immutable backups, data provenance protocols.
Governance Models: Establish a cyber risk committee reporting to the board.
Training Programs: Launch cyber awareness across all roles, from forklift drivers to executives.

Deliverable: Core cyber resilience infrastructure.

Phase 3: Pilot

Incident Playbooks: Develop and distribute role-specific response protocols.
Tabletop Exercises: Rehearse ransomware, insider threats, and third-party breaches.
Red Team/Blue Team Drills: Test defenses and refine response.
Supplier Pilots: Run joint simulations with top-tier vendors.
Executive War Games: Pressure-test leadership decision-making in crisis.

Deliverable: Validated, tested resilience processes.

Phase 4: Scale

Supplier Scorecards: Implement cyber rating systems across the supplier base.
Ecosystem Platforms: Deploy secure data exchange and federated identity systems.
Industry Participation: Join ISACs/ISAOs for real-time threat intelligence.
Collaborative Defense: Explore joint SOCs, mutual aid agreements, and sector-wide initiatives.
Global Alignment: Standardize resilience practices across regions.

Deliverable: Resilient, interconnected ecosystem defense posture.

Phase 5: Sustain

Continuous Monitoring: AI-driven threat detection across IT and OT.
Board-Level Dashboards: Track cyber resilience metrics alongside financial KPIs.
Regulatory Compliance: Stay ahead of evolving rules (SEC, NIS2, CMMC).
Cultural Reinforcement: Keep cyber resilience visible in strategy, values, and incentives.
Post-Incident Evolution: Use every incident (internal or external) as a learning cycle.

Deliverable: Enduring resilience as an organizational capability.

3. Metrics That Matter

Executives need quantifiable indicators to measure progress. Suggested metrics include:

Mean Time to Detect (MTTD)
Mean Time to Respond (MTTR).
% of suppliers with validated cyber programs.
% of workforce trained in cyber hygiene.
Backup success rate and recovery time alignment with RTO/RPO.
Board meeting frequency with cyber on the agenda.
Number of red team simulations conducted annually.

4. Embedding Resilience into Strategy

Cyber resilience should not be siloed. It must align with corporate goals:

Growth: Customers prefer resilient partners who won’t fail them in crisis.
Innovation: New technologies (AI, IoT, blockchain) must be secured from inception.
Sustainability: ESG frameworks increasingly include digital risk disclosure.
M&A: Cyber due diligence is now as important as financial due diligence.

Executives must position resilience as a strategic enabler, not a defensive drag.

5. Case Study: Retailer Ecosystem Roadmap

A global retailer implemented the roadmap in five phases:

Assess: Mapped digital dependencies across 1,200 suppliers.
Build: Deployed Zero Trust and encryption across warehouses.
Pilot: Conducted ransomware tabletop exercise with top logistics partner.
Scale: Rolled out supplier cyber scorecards to 400 vendors.
Sustain: Embedded cyber metrics into board dashboards.

Outcome: Faster detection, reduced downtime risk, and improved investor confidence.

6. The Board’s Role

Boards must:

Set tone at the top by prioritizing cyber as strategic.
Allocate capital for resilience initiatives.
Hold management accountable for resilience metrics.
Engage external experts to validate programs.

Cyber resilience is now a governance obligation.

7. The Executive Mandate

For CEOs, CSCOs, and CISOs, the roadmap crystallizes into three imperatives:

Lead visibly. Cyber resilience requires executive sponsorship.
Invest smartly. Prioritize resilience initiatives with highest impact.
Collaborate broadly. Partner with suppliers, customers, regulators, and even competitors.

The message to the organization must be clear: cyber resilience is business resilience.

8. Turning Resilience into Advantage

Resilient companies do more than survive, they thrive:

Customer loyalty: Buyers stick with reliable suppliers.
Investor appeal: Stronger governance attracts capital.
Competitive edge: Cyber maturity becomes a differentiator in bids and partnerships.
Market credibility: Companies seen as resilient can set industry standards.

Executive Takeaways from Part 10

Cyber resilience requires a structured, phased roadmap.
Five phases: Assess, Build, Pilot, Scale, Sustain.
Metrics (MTTD, MTTR, supplier compliance, board oversight) drive accountability.
Resilience must be embedded in growth, innovation, and ESG strategy.
Boards have a fiduciary duty to govern resilience.
Executives must champion resilience visibly and collaboratively.
Cyber resilience is a strategic advantage, not just a defense mechanism.

Conclusion

Cyber resilience in supply chains is no longer optional. It is the currency of trust in a digitized, interconnected world.

This roadmap provides executives with a clear path: Assess, Build, Pilot, Scale, Sustain.
By following these steps, organizations will not only protect themselves but strengthen the entire ecosystem.

Resilient supply chains don’t just survive cyber storms. They emerge stronger, and lead the market forward.

The post Securing the Chain: The Executive Roadmap to Cyber Resilience appeared first on Logistics Viewpoints.

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The State of Transportation Systems: TMS Lessons from 2025

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The State Of Transportation Systems: Tms Lessons From 2025

Transportation management underwent steady but meaningful change in 2025. While dramatic innovation was limited, organizations made progress in modernization, connectivity, and decision support. The theme of the year was not transformation. It was alignment—aligning TMS capabilities with the realities of volatile markets, cost pressure, emissions requirements, and customer expectations for more reliable service.

As companies look toward 2026, the lessons of 2025 offer a clearer picture of how TMS platforms are evolving, where value is being created, and what operational constraints continue to limit performance.

Modernization Accelerated and Became More Practical

Organizations continued to migrate from legacy, on-premise systems toward cloud-native platforms. But 2025 marked a shift: modernization was not pursued for its own sake. Instead, companies moved strategically, often focusing modernization efforts on the most constrained, high-visibility transportation processes.

The winning modernization projects delivered:

Cleaner API connectivity for rates, tenders, and tracking

Modular configurations that avoided monolithic system redesign

Reduced onboarding time for carriers and brokers

Better data freshness across execution and visibility systems

Instead of implementing everything at once, most enterprises adopted incremental modernization—starting with visibility integration, rate automation, or fleet scheduling—and expanding gradually.

In 2026, modernization efforts will continue to focus on practical outcomes like reducing manual load, accelerating tender cycles, and improving ETA reliability rather than chasing sweeping transformations.

Continuous Insights Replaced Periodic Reporting

One of the most notable changes was the widespread adoption of continuous, event-driven transportation monitoring. Companies moved away from static weekly performance reviews toward ongoing visibility into network conditions.

The shift was driven by:

the rise of real-time visibility platforms

better quality location data

improved ETA prediction

more reliable carrier status updates

API-fed telemetry replacing batch uploads

Rather than planning once and reacting later, transportation teams used near-real-time insights to:

reroute shipments

adjust pickup windows

realign labor at docks

escalate exceptions before they reached the customer

This “continuous planning” model reduced the latency between data, interpretation, and action.

In 2026, continuous insights will become standard. Static reporting will remain important for strategic planning, but day-to-day operations will revolve around dynamic decision cycles supported by live data.

AI Provided Targeted, Not Transformational, Wins

AI added value in transportation, but only in narrow, well-defined workflows. The strongest results came from AI’s ability to help evaluate alternates and reduce manual decision time.

Routing and Contingency Recommendations

AI helped planners identify viable alternates during:

weather disruptions

port congestion

driver shortages

regional bottlenecks

sudden capacity changes

These recommendations did not replace planning expertise. They accelerated it. AI functioned as a scenario generator—offering options that humans could refine.

Load Matching and Asset Utilization

AI improved load matching for private and dedicated fleets by analyzing:

empty miles

driver hours

backhaul opportunities

dock availability

These gains helped companies squeeze more productivity from constrained assets.

Exception Prioritization

AI helped reduce noise in exception handling by:

filtering out low-impact alerts

grouping related exceptions

identifying root causes

recommending the best corrective action

In 2026, AI will integrate more deeply into TMS workflows, but its role will remain decision support—not autonomy.

API Integration Emerged as a Competitive Advantage

EDI still dominates transportation, but it showed clear limitations in 2025. Delays in status updates, inconsistent message quality, and slow onboarding pushed companies toward API-first connectivity.

Carriers with strong APIs gained share in:

live tracking

instant rate shopping

automated tender acceptance

more granular status updates

lane-specific performance scoring

Shippers discovered that API-enabled carriers delivered faster, more accurate insights and fewer manual interventions.

In 2026, the shift will continue. EDI will remain for large carriers and structured freight networks, but APIs will power high-volume, time-sensitive, and cross-border operations.

Carbon-Aware Planning Began Its Move Into Execution

Sustainability efforts shifted from reporting to operational decision-making. Transportation teams began using emissions as a planning variable.

Companies applied emissions scoring to:

mode selection

carrier procurement

consolidation decisions

routing choices

lane prioritization

Some organizations used TMS enhancements to compare emissions intensity between alternates during routing decisions.

Early adopters discovered that carbon efficiency often aligned with cost and reliability. Efficient lanes tended to be:

better utilized

more predictable

more consistent in transit times

In 2026, carbon-aware routing will expand as regulators tighten expectations and customer requirements evolve.

Planning Cycles Compressed Under Persistent Volatility

Transportation volatility—capacity swings, geopolitical shifts, weather disruptions, and rising energy costs—forced companies to shorten planning cycles.

Teams moved from:

quarterly → monthly carrier scorecards

weekly → daily lane performance checks

static → rolling forecasts

annual → quarterly bid refreshes for variable lanes

This shift required better tools, better data, and better coordination across planning, procurement, and execution.

In 2026, planning cadence will continue to compress as continuous planning becomes the norm.

Visibility Data Became More Actionable

Visibility tools matured in 2025. The strongest improvements included:

more accurate ETAs

simplified exception categories

more reliable location data

better integrations with telematics providers

higher consistency in stop-level information

Companies used this improved data to:

reduce detention

schedule labor more accurately

improve dock turn times

respond earlier to late pickups or missed connections

In 2026, visibility platforms will integrate deeper with TMS systems so planners can adjust execution directly from the exception screen.

Key Constraints That Persisted

Despite progress, several structural issues remained unresolved:

carrier fragmentation

inconsistent small-carrier data quality

limited multimodal synchronization

slow customs processes in certain regions

capacity uncertainty tied to extreme weather

energy price volatility

Technology softened these constraints but did not eliminate them.

What 2026 Will Require

Companies that want to improve transportation performance in 2026 will need to:

strengthen integration discipline

adopt real-time carrier connectivity

incorporate emissions and energy variables

improve scenario modeling

refine carrier scorecards

build continuous planning behaviors

embed AI into exception and routing workflows

The organizations that succeed will treat the TMS as an active operations platform, not a passive system of record.

Final Takeaway

TMS evolution in 2025 was steady and practical. The systems that delivered the most value improved connectivity, reduced latency, and made planning more responsive. In 2026, transportation management will center on real-time coordination, AI-assisted decisions, and cleaner integration across the entire planning-to-execution spectrum. The companies that modernize incrementally, rather than overhaul everything at once, will see the strongest and most reliable gains.

The post The State of Transportation Systems: TMS Lessons from 2025 appeared first on Logistics Viewpoints.

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