How Is AI Changing Delivery Fleet Management?

The pace of announcements about AI in logistics is only going to keep accelerating. Recently it was Uber Freight’s AI-powered TMS garnering headlines and Gartner’s prediction that AI agents could take over half of logistics tasks in the next five years; next week it will be something else entirely.

It can be hard to keep track, but at the same time it can be hard not to get bogged down in the details. Week-to-week, it’s difficult to separate the signal from the noise and the reality from the hype—but if you step back and look at the larger trend it’s easy to see the huge impact that AI is posed to have on delivery fleet management. 

The question is: what’s coming down the pike, and how do you take advantage of it within your own fleet?

Delivery Fleet Management Is at an Inflection Point

New advancements in AI technology couldn’t come at a better time for fleet managers. Labor shortages haven’t gotten any better in the past few years, customer expectations are famously stringent, and managing costs is a delicate highwire act. 

Enter: AI-powered advancements in routing, customer experience, driver management, and more. 

The future of fleet management and logistics—a future in which AI agents do half the work for you, especially when it comes to managing technology interaction—may seem distant  on the horizon, but the early impact of AI is already here. It’s a powerful force for evolution around tasks and workflows that need to evolve if they’re going to keep meeting delivery fleet managers’ needs. 

Right now, logistics organizations can leverage AI to:

• Streamline and enhance customer delivery experience with the use of AI-powered chat agents
• Improve route efficiency and ETA accuracy by leveraging machine learning to find optimal routes and accurately estimate travel time
• Empower drivers with location intelligence at each stop via an automated voice assistant

In each of these cases, AI makes the humans on your team better at their jobs, and helps you reduce delivery fleet management costs via saved time and reduced disruptions. 

5 Steps to Get Started Using AI to Streamline Delivery Experience

Okay, let’s say the idea of improved customer experience via AI has grabbed your attention. How do you actually make it a reality? 

Here’s a step-by-step framework for implementing an AI agent for customer delivery experience:

1. Enable 2-Way Messaging with Customers

Your customers will encounter the AI agent primarily via chat, which means that you need to start with a foundation level of two-way messaging capabilities between your customers and your team. Customers should be able to respond to system-generated text messages and receive a response in the same thread, which your team interacts with via a streamlined chat flow in your last mile delivery software interface.

2. Scope Your AI Agent Properly

There’s a lot that you can expect your AI agent to handle, but it’s not magically going to handle every customer interaction. We recommend starting out a deployment with the chat agent set up for these use cases:

• Providing order details and other order information including item descriptions
• Informing customers about delivery schedules and estimated time of arrival (ETA)
• Capturing and processing delivery instructions
• Escalating cases to customer service when the chatbot cannot provide an answer, including requests for cancellations, rescheduling, and address changes

Having this technology already in place will make it much easier to capitalize as LLMs improve time—so this is a strong setup for a future scenario where your agents are handling rescheduling, order updates, and more.

3. Gather the Right Data

You’ve set up your two-way messaging and scoped out what you want your AI agent to actually do. Now it’s time to get your data ready to go.

This is less daunting than it sounds. Whatever AI you’re leveraging will be relying on the capabilities of existing LLMs, so you’ll just need to input the information that’s specific to your business:

• Name and address
• Description
• Customer service hours
• Website

Customer service hours are a particularly important puzzle piece. That information effectively enables your agent to manage customer expectations about when your human customer support reps will be available to handle inquiries that have been escalated.

4. Configure and Brand Your AI Agent

This is where you match your AI agent to your existing brand identity by giving it a name and a distinctive voice. Ask yourself a few questions:

• What’s a name we can give the agent that will resonate with customers and project the right image within the context of your brand?
• Is there anything unique or distinctive about the tone of your overall brand that you’d like to impart to the chat agent?
• Are there any types of queries or customer messages that your chat agent should ignore automatically?

5. Decide How and When to Escalate to a Human

For inquiries that are outside the scope of your AI-powered agent, the agent needs to escalate to a human customer support rep. This means that you need to decide who gets alerted, and how, when a customer has a question or request that the AI can’t handle. We recommend email alerts to stakeholders including the customer support team and managers, to ensure visibility into how these follow-ups are being handled. 

Make sure to train your team on what to expect from the handoff from the AI agent and to clearly define the protocols for dealing with particular customer needs or requests. 

How does this power ROI for fleet managers? There are a few crucial ways:

• Virtually eliminates WISMO calls
• Reduces customer service workload
• Speeds up issue resolution
• Centralizes and streamlines customer interactions

Taken as a whole, these various impacts can add up to significant cost savings and efficiency improvements across your logistics processes. 

AI Is Empowering Drivers as Well

When it comes to AI in driver management, the right driver mobile app is critical. Your app should already be offering turn-by-turn directions, configurable installation and service forms, proof of delivery capture, a digital manifest, and a direct line from the driver to the dispatcher. 

It should be a one-stop-shop for empowering drivers to do their best work. 

Once you’re at this level, AI-powered intelligence is the next evolution. Traditional mobile technology can make a huge difference in the last mile, but AI comes into its own in the last 50 feet. The right solution can offer AI-generated voice guidance as the driver approaches the delivery site with info on parking, loading, site-specific requirements, and much more—all of which improves efficiency and customer satisfaction. 

This kind of enhancement helps drivers overcome common—yet challenging—situations drivers face every day:

• Gated Communities and Complex Residences: Drivers receive gate codes, specific building locations, parking instructions and elevator locations before arrival, eliminating guesswork and reducing time spent trying to locate parking and access.
• Urban Commercial Deliveries: In congested downtown areas, the driver AI provides critical information about parking availability, loading zones, building access times, and potential traffic restrictions, allowing drivers to plan their stop before they arrive.
• High-Volume Retail Deliveries: When making time-sensitive deliveries to retail locations, drivers get advance notice of delivery windows, loading dock availability, and specific receiving procedures.

This helps reduce the time required for each stop, so drivers can complete more deliveries per day, with fewer failed deliveries and costly return trips. It reduces stress as well, so drivers are less likely to burn out. If all this adds up to even one extra delivery per day, you’re looking at a huge increase in profitability over time. 

<< Learn more about DispatchTrack’s Driver AI here >>

Choosing the Right Delivery Fleet Management Software

When it comes to AI in delivery fleet management, logistics organizations aren’t on their own. In the era of SaaS software, the onus is off of organizations to maintain their own software. You don’t need to build out your own AI—the right technology partner can help you implement AI-powered capabilities right out of the box. 

You don’t need a heavy-duty TMS either. The right delivery fleet management software will give you the capabilities you need for delivery fleet tracking, route optimization, customer experience, and driver management—all while laying the groundwork for AI evolution. 

The trick is to find a solution that’s innovating technologically without losing sight of the real day-to-day challenges of running a fleet.