Maersk and Hapag-Lloyd dropped Baltimore from key trans-Atlantic services. Here’s what it reveals about schedule risk—and how logistics AI helps you adapt faster.
AI Route Planning Lessons from Maersk’s Port Swap
Baltimore didn’t lose a trans-Atlantic container call because someone woke up and “felt like it.” It lost it because time became the most expensive commodity in the network.
In mid-December 2025, Maersk and Hapag-Lloyd announced they’re dropping Baltimore from key North Europe–North America services, shifting capacity toward nearby alternatives—most notably Philadelphia on Maersk’s TA3 rotation. The backdrop is the long recovery from the 2024 Francis Scott Key Bridge collapse, plus the plain operational reality that Baltimore requires a 150-mile Chesapeake Bay transit and multiple pilots—extra steps that add days and reduce schedule reliability.
For shippers, forwarders, and anyone responsible for service promises, this is more than a port story. It’s a live example of something I see constantly in transportation and logistics: manual network planning reacts late, while the cost of being late shows up everywhere—inventory, detention, missed production windows, and customer churn. This is exactly where AI in transportation and logistics stops being a slide deck and starts being a practical advantage.
What actually changed—and why it matters
Answer first: The carriers are removing Baltimore calls to protect schedule integrity, replacing it with ports that reduce sailing complexity and recover reliability faster.
Maersk stated Philadelphia will replace Baltimore on its TA3 service. The revised rotation is Southampton – Rotterdam – Hamburg – Wilhelmshaven – Newark – Norfolk – Philadelphia – St. John – Southampton, beginning with a sailing in early January 2026. Hapag-Lloyd also indicated Baltimore will be omitted on certain North Europe–North America services “for schedule recovery.”
This isn’t a minor tweak. A port call is a “node” in a tightly constrained system: vessel windows, berth productivity, pilot availability, tidal restrictions, yard density, rail ramps, and downstream drayage capacity. When one node becomes unreliable, the network does what networks always do—it reroutes.
The hidden reason: schedule reliability beats almost everything
Ocean shipping customers say they care about price. They do—until the supply chain starts missing key dates. When the system is stressed, schedule reliability becomes the product.
Baltimore’s challenges are unusually visible because of the bridge incident and ongoing recovery. But the underlying logic is common:
- Longer approach channels and pilot requirements increase variability.
- Any recovery project (infrastructure, dredging, repairs) adds uncertainty.
- A carrier can’t “make up time” easily once a weekly service slips.
A good mental model: a single delayed port call is rarely a single delayed container. It’s a delayed rotation, a missed berth window in the next port, rolled cargo, misaligned chassis, and a cascade of exceptions.
The operational math behind dropping Baltimore
Answer first: The decision is a classic optimization trade: reduce transit time and variance, even if it requires commercial disruption.
The FreightWaves reporting highlights a key point: calling Baltimore adds several days of transit time versus alternatives like Norfolk and Philadelphia. The Chesapeake Bay approach is long, and vessels require multiple pilots.
From a network design perspective, there are three costs that matter:
- Time cost (mean transit time): extra sailing hours reduce available buffer.
- Variance cost (uncertainty): more steps = more ways to miss the plan.
- Recovery cost: once off-schedule, you pay “interest” at every future port.
Most companies underestimate #2 and #3. They focus on the average transit time and ignore the variability. But variability is what drives expediting, safety stock, and customer escalations.
Baltimore’s volume context makes the impact real
Baltimore has been a major ro-ro hub in the Northeast, with vehicles making up a large share of cargo. The bridge disruption hurt container throughput sharply: container volume fell 41% from 1.26 million TEUs (2023) to an estimated 741,215 TEUs (2024).
That drop matters because carriers rationalize calls based on a mix of:
- Volume density (enough containers to justify a call)
- Revenue quality (contract mix)
- Operational complexity (time, pilots, channel)
- Network value (how the call supports other services)
When volumes drop and complexity rises, the call becomes an obvious candidate for removal.
Where AI would have helped—months earlier
Answer first: AI doesn’t “predict” port changes by guessing headlines; it predicts the economics of reliability—and flags when a node is trending toward removal.
The best logistics AI systems act like early-warning radar for network planning. They don’t wait for a carrier advisory; they continuously learn from signals that humans rarely combine in one place.
Here’s what an AI-driven approach could have surfaced earlier in 2025:
1) Reliability risk scoring for port calls
You can build a port call risk score that updates weekly (or daily) based on:
- Approach time and historical variance
- Pilot and berth delay patterns
- Weather sensitivity (wind/tide constraints)
- Congestion indicators (yard density proxies, berth utilization)
- Disruption recovery milestones and schedule slips
Even without perfect data, a model can identify the ports where variance is accelerating, which is often the “tell” before carriers trim a call.
2) Counterfactual network simulation
The most practical AI in freight planning is not a chatbot—it’s a simulator.
A network simulation can answer questions like:
- If Baltimore is removed, which SKUs face the highest stockout risk?
- What happens to drayage miles if Philadelphia becomes the discharge port?
- Which DCs need to shift safety stock because lead time variance changes?
If you’re a shipper, the value is simple: you can pre-plan a routing guide update instead of scrambling after the advisory.
3) Contract exposure analysis
When a port is dropped, the first scramble is often contractual:
- What percentage of our volume is port-specific in ocean contracts?
- Which customers have delivery windows tied to a particular inland rail ramp?
- Where do we have drayage providers without coverage near the new port?
AI can classify bookings, lanes, and customer commitments to quantify exposure by port, customer, and SKU. That turns “we’re worried” into a number your leadership team can act on.
What shippers should do now (practical playbook)
Answer first: Treat this like a network change event: reroute, rebalance inventory, and rebuild visibility around the new nodes.
If you move trans-Atlantic freight into the U.S. East Coast, assume more network changes will follow in 2026. Carrier rotations are being adjusted to protect reliability and manage cost. Here’s a tight playbook I’ve found works.
Audit your Philadelphia and Norfolk readiness
Start with basics that get overlooked:
- Drayage coverage: Do you have carriers already onboarded for Philadelphia/Norfolk?
- Chassis access: Is your chassis strategy compatible with the port and terminals?
- Appointment rules: Are you set up for local terminal systems and cutoff times?
One weak link (like drayage scarcity) can erase all the gains from a “better” port.
Recalculate lead times using variance, not averages
If you only change your planned lead time by “+2 days” or “-2 days,” you’re missing the point.
Update your planning parameters to include:
- New average transit time
- New standard deviation (or at least a practical buffer)
- Downstream impact on rail/intermodal connections
This is where AI forecasting helps: it’s better at capturing the variability introduced by new routings.
Update routing guides and exception workflows
A port swap triggers more exceptions than people expect:
- different last free day behaviors
- different demurrage/detention patterns
- different customs exam probabilities (depending on terminal flow)
Your routing guide shouldn’t just list the new port. It should specify the new exception rules so teams don’t reinvent decisions under pressure.
What carriers and 3PLs can learn from this decision
Answer first: The winners in 2026 will be the ones who operationalize real-time network monitoring and automate replanning.
This news is a reminder that “planning” is no longer a quarterly exercise. It’s continuous.
For carriers, forwarders, and 3PLs, the opportunity is to treat the ocean network more like an airline treats its schedule: monitor constraints, predict disruptions, and reroute customers with minimal friction.
The AI stack that supports smarter network adjustments
If you’re building or buying, focus on capabilities that reduce time-to-decision:
- Real-time ETAs + anomaly detection (flag drift early)
- Optimization engine for port selection and inland mode choice
- Scenario planning that outputs costs, lead times, and service impact
- Automated customer comms triggered by thresholds (not panic)
A strong stance: if your replanning still depends on a weekly meeting and a spreadsheet, you’re choosing slower decisions on purpose.
Snippet-worthy truth: Reliability isn’t a KPI. It’s a design constraint.
Where this fits in the “AI in Transportation & Logistics” series
This port rotation change is the kind of real-world event that makes the broader theme of AI-driven route optimization and supply chain forecasting feel concrete.
Network nodes will keep shifting—because infrastructure projects, extreme events, labor constraints, and capacity cycles aren’t going away. The companies that outperform won’t be the ones who predict every disruption perfectly. They’ll be the ones who replan faster and with less drama.
If you’re looking at 2026 budgets right now, here’s the question worth asking internally: When the next port call disappears, will we respond in days—or in hours?