AI for logistics in the UK: where it saves time and money, and what it costs to start

AI pays fastest in a logistics business where your customers feel it. That means delivery updates, quotes and booking changes answered instantly, in the portal, email or messaging app they already use. You measure it in fewer “where’s my delivery?” calls, more quotes won and customers who stay. Back-office savings, such as reading orders out of emails, come second but still count. A narrow first job can start at about £500, and a well-run first project at about £5,000. The state of your data decides most of what follows.

Where AI pays in a logistics business

Here’s the order we’d look at it in, starting with what your customers see.

The first three rows make you more competitive. The middle rows save money. The last row decides whether any of it gets used.

Start with your customers

Our view is that customer-facing service is where AI earns its keep right now. Large language models, the technology behind tools like ChatGPT, now handle plain-English conversation well. AI agents go a step further. They’re software that can look something up and then act on it, such as rebooking a slot.

That puts real service inside the software your customers already use, at any hour. A quicker, better experience wins and keeps more work than tidier paperwork does. Your customers never see your back office. They see how fast you answer.

The money shows up in two places. There are jobs you win because you replied first, and accounts you keep because nobody had to chase you.

Delivery updates and “where’s my order?”

If your team spends hours a day answering status questions, start here. An agent reads your tracking data and replies in plain English, by email, chat or WhatsApp. It can take a safe-place instruction or offer a new delivery slot. Anything it isn’t sure about goes to a person, with the conversation so far attached.

The catch is the data underneath. If driver updates arrive hours late, the agent will confidently share old news. That’s worse than no answer, because it sounds certain.

For costs and a worked example, see AI customer support for UK small businesses. If your customers prefer WhatsApp, read WhatsApp AI agents for UK businesses.

Quotes and bookings

If a quote waits for someone to get back to their desk, your customer has time to ask someone else. An agent can collect the job details, price standard work from your rate card and reply in minutes. Unusual loads, awkward collections and big accounts still go to a person.

Bookings work the same way. Letting customers book, change or cancel a collection themselves takes calls off your team. It also puts the details into your system in the customer’s own words, so nobody retypes them.

Matching jobs to drivers on the move

This is where AI changes how a logistics business runs, not just how it answers. Ultra Goldfield Logistics, which we built, matches parcels to drivers already heading the right way. It works like Uber for parcels. A driver says where they’re starting and where they’re going, while planning the trip or already on the road. The platform offers them the jobs along that route, each with its reward and how far off the route it sits.

Senders get a price up front from the pick-up, drop-off and parcel size, pay by card and follow the parcel to the door. The last mile is the most expensive part of delivery, and drivers are already making those journeys with space to spare. Matching the two turns empty space into paid work. See how we built it.

What to measure from day one

Agree the numbers before anything is built, so you can tell whether it worked.

• Status calls and emails per week, before and after
• Time from quote request to quote sent
• Share of quotes that turn into jobs
• Repeat customers and accounts lost
• How often the agent hands over to a person, and why

A high handover rate usually means the agent is missing data. Fix that before you blame the AI.

Then the back office

Back-office work is where most businesses start, and it’s a perfectly good second step. Your customers won’t notice it, so judge it on hours saved and errors avoided.

Orders that arrive as emails, PDFs and spreadsheets

If someone retypes customer orders into your system, AI can read them and fill in the booking. A person checks anything it’s unsure about before the job goes live. AI document processing with a human check covers how that review step works.

Exceptions, damage and proof of delivery

If failed deliveries and damage reports land in one shared inbox, AI can sort them. It summarises each one and sends it to the right person. It can also draft a reply or a claim from a driver’s photo and note, for someone to approve. Measure the time to resolve and the credit notes issued.

Billing and payroll

If invoices depend on rates, waiting time and extras, and someone builds them by hand, that’s a strong candidate. Payroll for drivers on variable hours is another. For The Home Help Company, we automated billing and payroll. That gave the CEO 30 hours a month back, which is most of a working week.

Don’t forget the people on the floor

Drivers, pickers and yard staff decide whether any new tool gets used. If it’s slow, fiddly or needs signal they haven’t got, they’ll work around it. Anything for the frontline should be quick to use with gloves on, and it should work offline.

Pristine Condition is the example we know best. Its movement-tracking product is used by about 150,000 warehouse staff, and it works offline. On a warehouse floor, offline is a requirement. Without it, people go back to paper.

We train the people who’ll run a new tool day to day, in plain English. Give your staff an easy way to flag when the AI gets something wrong. They’ll spot problems long before a monthly report does.

Where most UK businesses are with AI right now

You’re not late. The Office for National Statistics reports that AI use among UK businesses with 10 or more employees rose from about 12% to about 35% since late 2023. Use is still shallow. Only 10% of businesses using AI use it extensively, and the most common use, reported by close to 60%, is improving their own operations.

In plain terms, most businesses have dabbled, mostly behind the scenes. That leaves room to compete on the service your customers can see.

Is your data ready?

Where a project lands depends mostly on the state of your data. Run through these before you spend anything.

• Can you see a delivery’s live status in one place, without phoning the driver?
• Are your rate cards written down and current, or in one person’s head?
• Does each customer have one record, or a different one in every system?
• Are exceptions logged with a reason, or with a note saying “see email”?
• Can other software read your transport management system, the software that plans and tracks your jobs? Ask whether it has an API, a door other software can use.
• Do you know who is allowed to see which data, including customer addresses and driver details?

Mostly yes, and a first project can move quickly. Mostly no, and fixing the data is the first project. That money isn’t wasted, because every later project needs the same foundations.

Is your data ready for AI? goes deeper, and the AI readiness scorecard gives you a quick score. Before customer or driver details go near an AI tool, read our UK GDPR checklist for smaller businesses. Then see how we keep your data safe when we use AI.

What it costs to get started

In our experience, an AI agent can cost as little as £500 to set up. The low end suits a narrow job on clean data. Realistically, £5,000 is the lower bound for a well-managed, organised project. Where yours lands depends mostly on your data and what you want the agent to do.

A paid discovery doesn’t have to follow the chat. When there is one, either outcome costs far less than getting it wrong.

Running costs come on top and depend on your volume. What an AI agent costs to build and run puts numbers on that. How much an AI chatbot costs to run breaks down the model charges in pounds.

Buy, configure or build

You have three routes, and you’ll probably use more than one.

• Buy: ask your transport or warehouse system supplier what AI features it already has, and what they cost.
• Configure: set up a ready-made AI tool with your own data and rules. This suits internal jobs, such as summarising a shared inbox.
• Build: when the AI is how customers choose you, such as quoting faster than anyone else, own it.

Standard route planning, load planning and demand forecasting are well served already. Many transport management systems and specialist route planners offer them, so ask your supplier before you build. Build when the intelligence is the business itself, as matching drivers to jobs is for Ultra Goldfield.

A simple rule: buy what everyone has, and build what makes customers pick you. ChatGPT vs custom AI walks through the trade-offs. If you already run a customer portal or app, read whether we can add AI to it.

Hire an AI lead, or bring in a partner?

LLMs and agents are new, and the tools change every month. That makes hiring one person to lead AI a big risk. One hire carries all the knowledge, and a business new to AI can’t easily judge whether they’re good.

Expertise is a real gap. Around 18% of businesses with 100 to 249 employees say insufficient expertise has delayed their AI adoption.

For most haulage, delivery and warehousing businesses, start with a partner who does this all the time. They review the data, set strong foundations and get it working. Then hire someone to own it. Hiring first still makes sense when AI is continuous, core work at the heart of what you sell. Hiring an AI developer? covers that decision.

What to ask your team or supplier

• Which customer question takes the most staff time each week?
• How old is our tracking data by the time a customer asks?
• What can the agent do on its own, and what needs a person to approve?
• Which numbers we already track will show whether it’s working?
• What will it cost to run each month at our volume?
• Who owns the code, the data and the set-up if we change supplier?
• What happens when the AI model underneath changes or is retired?

If a supplier can’t answer the last two plainly, keep looking.

Where Contic fits

We start with a free chat about your business, with guidance on what we’d do. A paid discovery doesn’t have to follow. Our AI work covers the data review, the foundations and getting agents live with a person in the loop.

We’re AI-augmented, and senior engineers review and own everything that ships. We hold Cyber Essentials Plus and we’re registered with the ICO. You own the code and IP we build for you. Our founder was the founding engineer at AI Music, which Apple acquired.

Our work includes Ultra Goldfield Logistics, Pristine Condition and The Home Help Company. If you want to know where AI would pay first in your business, talk to us.