How Gordon Food Service uses LLMs for automation

Deji Adedayo, Head of Intelligent Automation at Gordon Food Service, shares how a traditional food business became an AI champion, one automation at a time.

Accounts payable, product catalogue, supply chain - we take a look at what tools, processes, and people made automation not just possible, but successful.

Watch the full interview

How Gordon Food Service became AI champions | Who's doing what in AI - YouTube

How Gordon Food Service became AI champions | Who's doing what in AI

Featuring

Deji (Intelligent Automation Lead, Gordon Food Service)
Sarthak (CEO, Nanonets AI Agents)

Watch time: 43:00

Highlights

Evangelising Automation:

Deji spearheaded automation at GFS, starting with cataloging, accounts payable, and receipts processing.

From frustration to 93% accurate:

After a disappointing experience with IDP solution, described as "slow and inaccurate", Deji’s team switched to Gemini. Despite initial setbacks with even lower accuracy, they improved to 93% within a few months.

Building the Right Team:

Successful automation requires more than just engineers and product managers, it also depends on data analysts who are necessary for communicating impact.

Advice to automation teams:

The part which teams are likely to underestimate is the importance of evangelising through clear metrics and compelling visual demos.

Transcript

Automation philosophy

Deji

An illustration I often use - I forget where I heard it - is a security guard whose job is to keep a property safe. But he also has to manually turn lights on and off every day. While he’s doing that he’s not actually focused on security. Now imagine replacing those lights with motion sensors or automated timers. The guard is free to do what he was really hired for. We recruit people for their expertise, not the mundane tasks.

I like to explain automation by asking people to think about the tasks they find most frustrating in their day-to-day jobs. Imagine if those tasks could be handled automatically, with the result ready when you need it, and you never had to think about them again.

Deji's projects

Deji

I’m really excited about generative AI. It’s unlocked a bunch of things we couldn’t do before. There was a time when we couldn’t do image classification for our products; we had to wait for vendors to supply us with usable images. Now, we generate those images ourselves, run an automated quality check, and they’re live on our website really quickly.

Another one is invoicing. Our previous process involved manually matching invoices, receipts, and purchase orders to make sure the quantity and amounts match. Invoices were sent to our local offices, and then manually forwarded to our AP inbox. We could never catch up to the volume of documents. It was pretty clear we needed to automate this.

Initially we looked at the IDP tool of our automation vendor. It was so slow and clunky for our scale, ~500 documents daily. That’s when we switched to Gemini, and it’s worked great. We started with single-page docs and then multi-page. Today that automation runs with 93% accuracy. Invoices are paid on time, and there’s no manual intervention.

How long it took to automate

Deji

Oh, to be honest with you, this sounds great right now but it wasn't great when we started off. The initial automation took around 6-8 weeks to build. But accounting for all the nuances in invoices, POs, and the process itself took us many months. I think it took us most of last year to get it done. We'd improve it, look at the data, and repeat. We had a war room with the business team, to check what they were seeing on their side.

With the 93 percent accuracy we have now, there's still room for improvement. It really isn’t a 2-3 month thing.

Dealing with errors

Deji

I don’t believe in building automation and walking away. I believe in continuous improvement. Even at 93% or 96% accuracy, I aim for 100%.

For every automation, we track KPIs on dashboards, especially accuracy. Then we look at the exceptions that lead to inaccuracy. We meet all automation stakeholders monthly, focusing on finding resolutions.

The GFS automation squad

Deji

I like to think of it like a car service centre. When you bring in your car, someone greets you and notes the issue, while a mechanic fixes the car. The automation team works similarly. You need someone who can translate business needs into technical language. I prefer developers to focus on building, so I like having an analyst or business liaison to ensure nothing is lost in translation.

I’m less concerned about what tools someone already knows. There are too many to master them all.

Deji

I get this question a lot. I start by meeting the business stakeholders personally. The key is: don’t bring me a solution, bring me the problem. Once I understand the problem, I start mapping out possible approaches.

ROI is obviously important, but how does the process impact upstream or downstream teams? Does it affect customer satisfaction or revenue?

I’d say employee morale is an area we often overlook. When AI automates repetitive tasks like image classification or invoice processing, people can stop worrying about it.

What's next and advice for automation teams

Deji

I think supply chain will be transformative. We’re just scratching the surface.

Start with finance; it's a great place because people are doing a lot of copy-pasting, downloading reports, exporting to SAP. But it’s not just about where you start, it’s also about how. Evangelise. Show people what’s possible, and small wins like that build credibility fast.

Deji

Don’t be afraid to fail. Try things, break things, learn fast, and adjust. That mindset helps you move quickly and build momentum. A lot of people don’t understand automation, some are afraid of it, and some just don’t see the value. The more you show them what’s possible, the more support and traction you’ll gain. I call myself an “automation evangelist” for that reason.