AI Demand Forecasting for Volatile Ocean Freight Rates

$1,963 per FEU to the U.S. West Coast. $3,150 per FEU to the East Coast. And both numbers can look “wrong” again in a week.

That’s the uncomfortable reality in December 2025: trans-Pacific container pricing is doing the classic sawtooth—GRIs jump rates, then spot slides as capacity and demand drift out of sync. Carriers are responding the only way they can in the short term: fewer sailings, more blanked sailings, and another round of rate pushes as annual contracts come up for negotiation.

Here’s what I think most teams miss: this isn’t just a carrier pricing story. It’s a planning technology story. When rates and sailings move like this, your biggest risk isn’t “paying too much.” It’s making the wrong decision at the wrong time—booking too early, too late, on the wrong coast, with the wrong service level, and then spending January firefighting inventory gaps.

This post is part of our AI in Transportation & Logistics series, and the goal is practical: how AI demand forecasting and optimization can help shippers, forwarders, and logistics leaders stay steady when ocean markets aren’t.

What the latest trans-Pacific volatility is really telling us

Answer first: The Asia–U.S. market is still stuck in a tug-of-war between soft demand and expanding supply, so short-lived rate spikes are the norm—not the exception.

Analysts tracking the lane reported that West Coast pricing fell 6% from an early-month bump to around $1,963 per FEU, while East Coast rates rose 8% to about $3,150 per FEU—yet were still 15% lower than a month earlier. Carriers have managed to keep rates above prior lows (roughly $1,400 per FEU West Coast and $3,000 per FEU East Coast), but that “floor” is being defended with tactical capacity moves rather than genuine demand strength.

The sawtooth problem: GRIs create noise, not clarity

General Rate Increases (GRIs) are designed to reset price expectations. In a soft market, they often do something else: they create a burst of bookings, then a retreat to spot as shippers wait it out.

That matters because ocean freight decisions are rarely isolated. Your ocean booking affects:

• Inland dray and rail schedules
• DC receiving labor plans
• Safety stock positioning
• Customer promise dates and chargebacks

When the price signal is noisy, the entire planning chain becomes noisy.

Blanked sailings are a capacity “dial,” not a fix

Fewer sailings can support rates temporarily, but it can also:

• Increase roll risk (cargo gets bumped)
• Create equipment imbalances (containers in the wrong places)
• Shift volume to alternate ports, stressing inland networks

If you’re treating blank sailings as a carrier issue only, you’re underestimating how quickly it hits inventory outcomes.

Why Asia–Europe is behaving differently (and what that implies)

Answer first: Asia–Europe rates are holding GRIs better because demand is ticking up and lead times remain uncertain, so shippers are buying time with earlier ordering.

On Asia–Europe and Asia–Mediterranean lanes, carriers have been more successful sustaining consecutive GRIs. Rates have stabilized around $2,449 per FEU to North Europe and $3,342 per FEU to the Mediterranean after climbing earlier in the month. Reported volume indicators show gradual improvement on China–Rotterdam since mid-October, with year-to-date Asia–Europe volumes up 8.6% through October.

One driver: pre–Lunar New Year ordering starting earlier than usual. Another: geopolitical risk around the Red Sea, which has already forced diversions and longer voyages over the past year.

Here’s the practical implication for logistics teams: trade lane behavior is diverging. A single global ocean strategy won’t fit January–March 2026 planning.

The December 2025 planning cocktail: LNY + tariffs + geopolitics

The market is juggling three major uncertainty sources at once:

1. Lunar New Year factory closures (two-week production pause)
2. Tariff uncertainty (policy outcomes affecting import timing)
3. Red Sea risk (route choices affecting transit time and reliability)

You don’t need perfect forecasts to operate well. You need decision-grade forecasts—and a way to update them continuously.

Where AI actually helps: turning volatility into better decisions

Answer first: AI improves ocean planning by forecasting demand with uncertainty, optimizing booking timing and routing, and continuously re-planning as rates and sailings change.

“AI in logistics” can sound abstract. In ocean freight, it becomes very concrete, very fast. The highest-value uses fall into three buckets: forecasting, optimization, and exception management.

1) AI demand forecasting that includes uncertainty (not just a single number)

Classic forecasting asks: How many containers will we ship next month?

A better question is: What’s the probability distribution of volume by week, origin, and service level?

AI models can combine signals like:

• Purchase orders and order cadence shifts
• Promotional calendars (retail/CPG)
• Supplier production patterns ahead of Lunar New Year
• Historical booking lead times by lane
• Port congestion indicators and schedule reliability

The output you want isn’t “12,000 TEU.” It’s: “We’re 70% likely to land between 10,800 and 12,600 TEU, with risk concentrated in weeks 3–4.”

That’s the difference between guessing and planning.

2) Rate optimization: choosing when to buy spot vs. lock contracts

About 60% of ocean cargo moves under contract and 40% under spot (and that ratio swings when markets tighten). In a sawtooth market, the wrong mix costs real money.

AI can support rate strategy by:

• Predicting short-term rate softening after GRIs
• Recommending a dynamic “spot allocation cap” by lane and week
• Simulating total landed cost (ocean + inland + inventory carrying cost)

A blunt but useful stance: don’t optimize ocean freight in isolation. Optimize for landed cost and service risk. If blank sailings raise roll probability, the cheapest rate can become the most expensive outcome.

3) Routing and scheduling: fewer sailings means your network needs options

When carriers cut sailings, your best response is optionality. AI optimization is great at finding it.

Common plays AI can evaluate quickly:

• Port diversification: shifting a portion of volume between West Coast and East/Gulf gateways
• Service-level splits: mixing faster and slower services to protect in-stock metrics
• Carrier diversification: balancing allocation across alliances/services to reduce roll concentration
• Mode bridging: using air for a small SKU subset when a roll would cause stockouts

A one-liner worth remembering: “Blank sailings don’t just remove capacity—they remove your ability to be wrong.” The more uncertain the schedule, the more valuable good re-planning becomes.

A practical playbook for Q1 2026 ocean planning (with AI)

Answer first: Build a weekly planning cadence that pairs AI forecasts with operational guardrails: booking windows, safety stock triggers, and exception workflows.

If you’re heading into January contract negotiations and February Lunar New Year impacts, here’s a framework I’ve found works across shipper and forwarder teams.

Step 1: Define the decisions you’re trying to improve

Pick 3–5 decisions that move the needle:

1. Booking lead time (how early to book by lane)
2. Spot vs. contract split (by week and origin)
3. Port pair selection (West Coast vs. East Coast routing)
4. Carrier allocation (diversify roll risk)
5. Expedite triggers (when to pay for speed)

AI should serve these decisions, not create a new dashboard nobody uses.

Step 2: Set “guardrails” that protect service

Volatility punishes vague policies. Use clear thresholds such as:

• If forecasted stockout risk exceeds X%, shift Y% of volume to faster service
• If schedule reliability drops below Z, cap bookings on that service
• If spot rates fall below contract by $N/FEU, expand spot share up to a ceiling

These guardrails keep optimization from making choices that look smart on paper but fail in execution.

Step 3: Run weekly scenario planning (not quarterly)

Ocean markets can change faster than your S&OP cycle. A weekly rhythm is more realistic:

• Monday: update forecasts and rate inputs
• Tuesday: run routing/booking scenarios
• Wednesday: carrier/forwarder alignment and capacity checks
• Thursday: execute bookings and update inland plans
• Friday: exceptions review (rolls, delays, priority SKUs)

The point isn’t to be busy. It’s to shorten the time from “market change” to “decision change.”

Step 4: Automate exception management where it hurts most

You’ll never eliminate exceptions. You can make them cheaper.

High-impact automations include:

• Early warning on blank sailings affecting your bookings
• Predictive ETAs tied to downstream DC receiving schedules
• Auto-rebooking recommendations when roll risk spikes
• Priority scoring for containers based on customer and inventory impact

People also ask: what should shippers do when carriers cut sailings?

Answer first: Protect service by diversifying routes and carriers, booking earlier for high-risk weeks, and using AI to re-plan continuously as schedules change.

In practice:

• Treat blank sailings as a network risk, not just a capacity headline
• Build a two-port strategy for core origins where feasible
• Align procurement and logistics so PO timing reflects transit-time uncertainty
• Use AI-driven forecasts to decide which SKUs deserve premium routing

If you do only one thing: stop making ocean decisions with a single forecast number and last month’s assumptions.

What to do next

Trans-Pacific rates are bouncing because supply and demand still aren’t aligned, and carriers are using GRIs and blanked sailings to manage the gap. Asia–Europe is firmer because demand and lead-time uncertainty are supporting price increases. For shippers and forwarders, the common thread is simple: planning has to get more adaptive.

AI demand forecasting and logistics optimization won’t eliminate volatility, but it will change your posture from reactive to prepared—especially heading into Lunar New Year and tariff-driven import timing shifts.

If you’re building your 2026 transportation strategy, here’s the question that matters: When the next schedule change or rate spike hits, will your team re-plan in hours—or in weeks?