Managing logistics isn’t supposed to drain your team’s time and energy. But when your workflows run on spreadsheets, scattered data, and enterprise resource planning (ERP) systems that weren’t built for mobile access, even a simple status check can mean hours of chasing emails, refreshing carrier portals, and calling suppliers.
Add tariffs, weather disruptions, and other factors you can’t control, and it feels like your team’s constantly reacting, with no time to plan ahead.
Businesses have made it a priority to tackle these challenges, and they’re looking at artificial intelligence as an essential resource.
According to the 2025 State of AI in operations report from Glide, more than half of businesses in labor-intensive industries like transportation and logistics plan to invest over $100,000 in artificial intelligence this year to improve team efficiency.
But while many of these businesses want to benefit their logistics operations, they haven't figured out which AI technologies to use or how to apply them to their specific workflows.
This article is designed to close that gap. Here are some ways to use AI agents and intelligent automation to improve shipment visibility, reduce costs, and cut manual work across logistics and supply chain management.
1. Pick the best carrier for every shipment
An AI agent can analyze carrier and pricing data to recommend the most cost-effective, reliable, or fastest carrier for each shipment based on your priorities, eliminating the guesswork and manual comparisons that slow down your team.
Finding the right carrier is time-consuming and difficult with many existing logistics systems. Rate data is scattered across multiple carrier portals, outdated spreadsheets, and email threads or worse, undocumented phone calls. Your team wastes time toggling between tabs and chasing reps for quotes.
An AI agent eliminates that manual work. Connect the agent to your carriers’ live APIs and upload your negotiated rate sheets. Feed it your shipment history—what you shipped, destinations, which carriers you used, and what you paid. This helps the agent identify cost patterns and benchmark rates across different routes and service level options.
Then, set specific goals the agent should take into account when helping you pick the best carrier. Here are some examples:
Standard shipments: For standard ground shipments, recommend the cheapest carrier that can deliver the shipment within 7 days.
Expedited orders: For any order marked ‘expedited,’ recommend the fastest possible option that costs no more than 20% above the cheapest option.
Key accounts: For shipments to accounts marked ‘key,’ prioritize the carrier with the highest on-time delivery percentage for that region, regardless of cost.
When you need a quote, give the agent the shipment details like origin and destination, package dimensions and weight, service level requirements, delivery time windows, and priority. The agent weighs all available rate data against those requirements, plus any real-time criteria you choose, such as weather conditions, traffic updates, fuel prices, or regional surcharges, to give your team the best options.
Your operations manager can choose the best carrier from the filtered list and book the shipment.
As you add new shipments, the AI agent uses this data to refine its recommendations over time.
2. Consolidate shipments to reduce costs and improve efficiency
Smaller shipments booked individually can drain both time and budget. An AI agent can analyze your outbound shipments in real time and find shipments that can be combined to save on freight and improve efficiency.
Your operations team is managing dozens of individual bookings with different pickup dates, delivery windows, and destinations. Spotting which ones can be combined requires cross-referencing multiple spreadsheets and carrier schedules—work that takes hours and often happens too late to change bookings. Your business sends them as less-than-truckload (LTL) or less-than-container load (LCL) shipments, paying premium rates to move half-full loads.
An AI agent solves this by continuously monitoring your entire shipment queue and spotting combinations your team would never have time to find manually. Connect it to your ERP to give it access to all shipment data. Then, set parameters for what the agent should consider: promised delivery dates, incompatible goods, carrier-specific requirements, and any warehousing constraints.
When the AI finds shipments that can logically be combined, it flags the recommendation along with a cost comparison to standalone shipments. Your team reviews the recommendation, makes adjustments if needed, and makes the booking based on the approved plan.
With fewer bookings and partial loads to manage, your team moves the same volume more efficiently and at lower cost.
3. Gain visibility to keep operations on schedule
An AI solution gives your operations team accurate, real-time data on where shipments are and when they’ll arrive. That means they can schedule production runs, inbound deliveries, and outbound dispatches without second-guessing delays.
Right now, tracking data is spread over too many places. One team’s checking the carrier portal. Another’s digging through email chains for a tracking number. Someone else is waiting for the warehouse team to check if a shipment has arrived. Even when updates are available, they’re often hours old or inconsistent. If a shipment is running late but no one knows, your production floor might sit idle for half the day waiting.
An AI-powered dashboard brings visibility to your operations. It analyzes connected data sources in real time to build a single, accurate timeline of your shipments. This can include:
Carrier API feeds for official tracking updates
Email updates parsed for delivery confirmations and delays
Historical shipment logs for factors like carrier performance
Real-time data like traffic patterns, weather conditions, and port congestion
You can bring all your shipments together to give your entire team an overview of where each shipment is and its status.
If something goes off track, the system flags it immediately and sends proactive alerts with context—like identifying a specific traffic jam or port congestion as the cause of delays—plus suggested solutions for handling the disruption. Your team can evaluate the agent’s suggestions and reschedule work, hold or reroute the shipment, or reassign site resources.
With early warnings and reliable ETAs, your team can act before delays create downtime.
4. Optimize routes to help shipments reach on time
An AI-powered mobile logistics app supports smarter route planning across the journey, taking into account real-time traffic, vehicle restrictions, and site-specific requirements.
Traditional route planning systems only get you so far. They’re unprepared for hurdles like traffic, accidents, or road closures. Truck routing tools can miss a low-clearance bridge if they're relying on outdated map data. Drivers arrive at a warehouse and spend 20 minutes figuring out which loading dock to use. Every minute a driver spends in a traffic jam, taking a wrong turn, or idling at a confusing delivery site costs money in fuel, wages, and potential late fees.
AI systems continuously analyze live traffic, weather, road closures, and destination maps to find the most efficient path to the destination. The app factors in vehicle type, route restrictions, and customer requirements like temperature-sensitive goods or exact delivery windows when recommending which route to use on the road and at the site.
Here’s how the AI agent handles both legs of the journey.
On-road route optimization: The AI agent analyzes a continuous stream of data, including live GPS feeds from vehicles, traffic and weather reports, delivery schedules, and historical transportation times, to calculate the most efficient path for every shipment. It dynamically adjusts routes in real-time to navigate around new obstacles, ensuring shipments stay on schedule.
On-site navigation: For sites like warehouses or construction zones, the AI agent learns facility layouts and dock availability using geofenced delivery points, site maps, and historical drop-off data. It guides the driver along the best path to a specific loading dock based on factors like real-time availability, vehicle type, operating hours, and load type.
Drivers can upload any relevant photos or voice notes to the app after each delivery, adding to the destination’s data and giving the AI more context to work with.
Over time, the agent improves its recommendations using driver feedback, idle time patterns, and time-stamped entry/exit data to find the most efficient path both on the road and at the destination.
Your deliveries are more likely to arrive on schedule as the agent refines routes and helps drivers avoid common delays. Your operations team gets predictable ETAs they can actually plan around instead of constantly adjusting schedules or reassigning crews because a truck is stuck in the wrong place.
Costco built a custom logistics app with Glide to help its truck drivers at delivery sites. The mobile-adaptive app gives drivers specific information about which drop off spot to use at each Costco location and how to get there—photos of each Costco location, marked with the route the driver should take to avoid parking lots and tight turns.
5. Prevent equipment breakdowns with predictive maintenance
Equipment failures don’t have to catch your team off guard. Predictive maintenance uses AI to analyze patterns in equipment data and predict when vehicles and machinery need maintenance before they break down.
Many teams rely on time-based or reactive maintenance schedules that miss early warning signs of potential failures. A forklift seizing up during loading or a delivery truck breaking down mid-route lead to costly emergency repairs, delayed shipments, and frustrated crews waiting for equipment to come back online.
An AI solution continuously monitors multiple data sources to build a complete picture of equipment health, including:
Fleet telemetry data to track GPS and vehicle diagnostics like engine performance, fuel efficiency, and mileage.
IoT sensors to track variables such as vibration, temperature, or speed irregularities on factory or warehouse equipment.
Past repairs and maintenance logs that help the AI system identify recurring issues, failure rates, or missed intervals.
Audio AI using microphones to capture acoustic data from engines, brakes, or other mechanical components to catch subtle changes before they turn into breakdowns.
Driver or warehouse manager notes through a mobile app, where they can upload photos, voice memos, or add comments about unusual equipment behavior.
When the system detects a potential issue, the AI agent sends a proactive alert and creates a maintenance work order with the relevant diagnostic data attached. For example, it might flag that a particular piece of equipment is showing a 75% probability of mechanical failure within the next 72 hours.
Your team can review the context and schedule repairs before the piece of equipment breaks down.
This kind of predictive analytics extends the lifespan of your equipment, reduces unplanned downtime, and reduces costs from unexpected repairs. For delivery fleets, it also supports safer driving conditions and helps keep your vehicles compliant with transportation and safety regulations.
There’s an added bonus: predictive maintenance makes inventory management more precise. Instead of ordering extra parts “just in case” or scrambling to find them when equipment breaks down, you can stock the right components without tying up cash in unnecessary inventory.
Learn how to use AI for inventory management
Read the guide6. Catch defects before they become a problem
An AI inspections agent is up to five times faster than manual quality checks and more accurate, helping your team stop defects before they enter your inventory or reach a customer.
Manual inspections can’t always keep up with your operation’s demands. A thorough check might take 20 minutes per pallet, which is long enough to back up deliveries and delay production. If specs change mid-project but the checklist doesn’t, inspectors follow outdated steps and approve the wrong materials. Even diligent teams run into issues when timing slips or information gaps widen.
You can use AI inspections agents at key points across your logistics flow to maintain quality without slowing your team down.
At receiving, it flags issues as materials are unloaded—before they’re added to inventory—so damaged goods don’t enter the system.
Before goods leave your facility, it runs a final quality check on finished products and packaging just before shipment, verifying that everything meets your standards.
The AI system processes this input, analyzing the visual data for cracks, dents, color variations, or dimension problems, and creates detailed inspection reports based on your quality standards within seconds. For example, if a photo shows packaging with torn corners or a voice note mentions “this batch is missing a label,” the system flags these items and prevents them from moving forward until your team reviews them.
When the AI solution detects a defect, it automatically notifies your purchasing or quality team and prevents the item from being accepted into stock or shipped out. Your team reviews and approves the report, only spending time on items that require human attention.
7. Automate logistics workflows and reduce manual data entry
Manual data entry and paperwork pull your team away from more complex parts of a logistics operation that actually require their attention. AI technologies automate these tasks so your team can focus on managing the supply chain, not retyping the same information over and over.
Your most skilled people spend their days manually checking purchase orders against packing slips, logging asset scans from the warehouse floor into a spreadsheet, and keying the same information into multiple, disconnected systems. This isn’t just inefficient, it’s also a major source of errors. A single typo in data entry can lead to billing disputes, incorrect inventory counts, or shipping the wrong product.
AI technologies process logistics documents faster and with fewer mistakes—extracting data, generating paperwork, and updating your systems in real time. Here’s how:
Intelligent document processing: The AI system uses technology like Optical Character Recognition (OCR) and Natural Language Processing (NLP) to read and understand documents like Bills of Lading, packing slips, and commercial invoices. It extracts key data, checks it against purchase orders in your ERP, and flags mismatches like incorrect quantities or item codes before they cause issues later in the supply chain. It automatically updates your connected platforms like ERP, inventory management system, and warehouse management system so that all data stays in sync.
Automated document creation: It generates accurate shipping labels by pulling customer addresses from your customer relationship management (CRM) system, package specifications from your inventory management system, and carrier information from your shipment booking tools.
Create status updates: The system tracks each shipment’s progress and uses generative AI to write personalized status updates. It might send “Shipment 245 cleared customs and will arrive at the dock at 2 p.m.” or “ETA for delivery of Shipment 702 is 3:45 p.m. tomorrow.” It delivers these updates automatically via email, SMS, or your logistics software’s chat tool, keeping both internal teams and customers automatically informed of the shipment’s status.
At every step, the system flags any inaccuracies for your team to review. Your team moves faster, makes fewer errors, and focuses on higher-value work while AI handles the manual tasks.
8. Avoid customs delays with accurate, AI-powered documentation
AI technologies help your team generate accurate customs paperwork so your shipments sail through without delays at the border.
Cross-border shipments involve detailed customs paperwork, and relying on manual processes to complete it is both slow and risky. A single error on a customs form can trigger delays, customs fines, demurrage charges, and project setbacks that frustrate customers.
AI solutions reduce these risks by automatically generating and validating customs paperwork with data pulled directly from your existing systems.
Customs form preparation and accuracy checks: The AI system collects product details from your ERP, route data from your transportation management system, and consignee information from your CRM to fill customs forms. The system cross-references this data against customs requirements and flags any missing or inconsistent information before submission.
Intelligent HS Code classification: Based on the item’s description, materials, and intended use, the AI agent recommends the most accurate Harmonized System (HS) code. This significantly lowers the chance of misclassification, which means fewer delays and a lower risk of customs fines.
Your team still reviews the final documents, makes any necessary adjustments, and submits everything on schedule. Document preparation time drops, customs clearance times improve, and international shipments move smoothly across borders.
Learn more about how to use custom software for logistics
Read the guideImprove your logistics operations efficiency with AI
Efficient logistics software should reflect how your team actually works, not force you to adapt to someone else’s system. With Glide, you can build a custom logistics app around your team’s workflows to improve visibility, reduce manual work, and streamline decision-making.
Start by connecting your data and team workflows in one place. Platforms like Glide give you the flexibility to build your custom app—complete with AI features—without relying on developers or writing any code.
Once your system is set up, you can add AI capabilities with Glide’s managed AI setup that takes care of model selection for you. You get the benefits of AI—like more accurate data and fewer repetitive tasks—without the technical overhead.
You have different options for building your app. You might start with a pre-built template and adjust it to your needs, create one from scratch using drag-and-drop components, work with a Glide Expert to build it for you, or reach out to the Glide team. Each method is a path to building an AI-powered logistics app that fits every part of your logistics operations.
