Real-world AI applications in print

In this episode of FESPA Insights, the discussion centers on the critical role of AI, automation, and sustainability in business. The speakers aim to demystify AI by sharing practical applications and case studies, emphasizing the importance of human involvement in the AI process. They highlight how AI can enhance customer service efficiency and maintain brand voice consistency, while also addressing common management fears regarding AI adoption. The session encourages businesses to start with small improvements and engage stakeholders for successful integration. As the conversation shifts to a Q&A format, various AI platforms and their applications are explored, showcasing the growing demand for AI functionality across industries.

Transcript

Welcome everybody to the first episode of Fespa Insights where we’ll be hoping to guide some some of you into your journey into AI adoption.

So initially, welcome to the first episode again. What is Fespa Insights? Well the first of many episodes highlighting three main sectors predominantly AI, automation and sustainability.

I’ll give you a quick rundown of what the agenda actually is today and why we’re doing it. So AI is here now, no longer a trend. It’s something that we’re all going to have to get on board with at some point soon or some point in the near future. We’re gonna plan on cutting through the hype and understanding what’s actually real and usable today.

AI in the real world, we need to learn from case studies and businesses already pioneering the way from fermentation and so that we can learn from them. Practical applications, learn from and utilize the correct tools for your business and of course the ultimate goal building a roadmap for your own implementation journey.

So briefly why does this episode matter?

And this episode matters for a few reasons predominantly the main aim. The hype surrounding AI at the moment has diluted the quality of information for the most part. You don’t know quite exactly what’s right, what you’re looking for, and where to go for it So we’re hoping to offer an understanding of all the actions you could take towards implementation today, setting the time for the future and paving the way. So the outcome for this session we’re hoping to transform knowledge into practical insights and something you can actually work on today, Confidence to enhance your projects with AI applications and enhance the overall experience and get you get yourself scaling as soon as possible.

And of course future looking to explore even further because the things that we’re going over today despite it being quite advanced as it is, is still early stages when it comes to AI. There’s plenty more out there and there’s plenty more in the pipeline, so get excited and get thinking. And of course, the overall theme, we wouldn’t mind building a culture, of experimentation because this is a it’s an experimental time, and there’s a lot to figure out and a lot to find out. So I’m gonna go on to our speakers now and introduce them starting with Rob Hayes.

Hey, Jack. Hi, guys. My name is Rob. Thank you all very much for joining us today.

I’m founder of AirNova. And as Jack politely put it already earlier on, really, you know, was founded with a a a goal to cut you the hype. Right? It’s it’s practicality around AI adoption.

It’s helping whether it’s customers of ours, clients of ours, partners of ours, or or even just the general public, understanding what’s real with AI, what’s not real with AI, and what’s what actually makes it tangible for them. We make sure we bring everything or I make sure we bring everything back to to business value because at the end of the day, even if we’re if we put AI aside for a few minutes and just look at any new process, any transformational project you’re looking to do, it should be rooted in business value, business change. And that’s where we we take AI from the very, very start.

So we bring it back to what’s it actually going to do for your business, where is it going to bring value. There was a recent report out from from MIT where they talked about ninety five percent of of AI projects fail, or or don’t get past proof of value, proof of concept stage, or don’t deliver the value. And I definitely for for myself, Chris, and and Carlo on the call here, for any of the projects that we’ve been involved, our percentage of success has been a lot higher. And a lot of that is because we have have that same ethos, really.

It’s it’s cut you the hype. Make it real. Make it practical. Make it easy to adopt.

Make it relevant for you. That’s me. Sorry. Final piece on me for the introduction. Background is fifteen years in in emerging technology.

And, yeah, I’ve been the last the last two and a half, three years with a big focus on AI AI adoption into into different into different industries across the the Middle East and GCC region.

Thanks, Jacques. Carlo?

Hey, guys. My name is Carlo Pepe. I had twenty almost twenty six years now in tech starting with the first independent ISP in the UK, a company called Demon Internet, who maybe some of you will will remember from the past.

I am an AI business consultant and founder of a company called Kashima.

And, essentially, what we do is help individuals, teams, departments, and organizations as a whole get their head around AI where it can actually help, but in a purposeful way.

As Jack outlined, AI is fairly new. I mean, it’s not. It’s been around for seventy five years as a concept. But in terms of generative AI, which has put it, like, in our hands, it’s, it’s a new concept.

So, Kashima itself does two things a few different ways. Number one is we provide upskilling. So that’s helping individuals learn how to use tools to complete their tasks and workflows. And then number two, we provide consulting so that we can hunt around for those areas that AI can actually add value, to business.

Chris?

Yeah. Thanks, Carlo. Thanks for having us on as well, Jack. Good afternoon, good morning, or good evening depending where you are.

I’ve been very fortunate to work in the print industry for the last sort of fifteen years. Not quite as, experienced as Carlo or Rob with some of those larger numbers that they just referenced. Not sure if that’s an age thing or not, Carlo, but we can we can take that offline. So, basically, I’m all about automation.

Web to print is one of my specialties, personalization, anything that engages the end user for us to use technology. So AI definitely touches that. But as I was saying to the guys when we were behind the scenes preparing for this call, one of the frustrations is the fluff that goes around AI right now. And one of the things I’m really keen and excited about is working with consultants like these guys to try and use it properly so we can automate our systems better and ultimately feed those presses and keeping them running.

So that’s one of my biggest, motivations. I’m very lucky that, I get to head up a very successful and, clever team of marketeers who who understand print automation and workflows.

I’m also very lucky to have been working with Vespa Middle East in January where I met these gentlemen, and they really changed the, the outlook for me on how to look at AI and how we should implement it. I felt so strongly about the lessons I learned from Carlo and Rob in January in Dubai that I spoke about it at Fespa Global in in Berlin, and, I was very, very lucky that I could share that message further. So, yeah, Digital Ink, ultimately, it is what it says. We we’re digital.

We do work with all digital platforms, and we wanna make sure that we keep the ink running. And that can be anything from consultancy to workflow to, asset creation to marketing strategies. So we’re probably predominantly based in the GCC. We do also have customers and teams based in in Europe, mainland Europe, UK, North America.

And, we’re all about driving success at the end of the day. Well, however that looks, could that be a partnership, could that be an integration, or could that be talking to someone like Carlo or Rob?

Fantastic, guys. Well, it’s an absolute pleasure to to have all of you here, and I’m feeling that I’m I’m very lucky right now. So, just quickly before we kick off into the content side of things, I’m just gonna drop a poll in the chat just to sort of gauge where everyone is in their AI implementation. So it’ll last for about a minute thirty, so not too much of a rush, and we’ll go over those results at the end.

So I’m just gonna kick the start of that, and we’ll get into the next sesh next section of content.

So, gentlemen, if you wouldn’t mind letting us know the real world context and who this webinar is actually for.

So I’ll kick this off, guys. So what this is for is this is for people who are not only curious, but kind of overwhelmed with this the vast vast amount of new information that’s coming out, new tools, and claims on LinkedIn, on Instagram around, I’ve developed this tool. It’s it’s killed my sales team. I’ve got rid of all of them.

Or I’ve developed this workflow, comment workflow, and I’ll give you this ability to reduce your marketing team down to one person and perform the job of five hundred. It’s the the the majority of this is a bit of a nonsense, to be honest with you. And so if you want to understand how AI can actually help and how you can get going with that today and how you can improve what you’re currently doing, because my guess so maybe, Jack, this is, actually on the poll. I don’t know.

But my guess is the vast majority of you are using an AI tool at some point every week, maybe every day. On your phone you’re using Gemini in Android, maybe using chat gpt, and you haven’t learned how to use it all. You’re just doing like everyone else is and that’s just using it and trial and error. So if you’re in one of those categories, this is for you to understand exactly what these approaches should be, the best practices.

And what this will do is it will give you, like, a very straightforward view. As Chris said, when we were at FESPA Middle East in January, everyone kind of wanted to park the nonsense and get straight to what can actually be done. And this is the approach of both Rob and myself. So if you’ve taken the first step, if you’re curious, this is perfect for you to learn more.

Well fortunately and I think judging from the poll results we might have the right people in the room and I’m just going to share those results quickly just to give you a bit of a gauger. So only three percent of the audience has been using it for more than five years and sixty one percent of the audience are just in their early stages, whilst thirty six percent have not used AI in the slightest. So I think we might have the right people in the room. Fortunately, I put the right guys in for you. So we’re gonna move on to the next section of content now and just go over some of the what you can expect from AI usage, some of the case studies, and what what results are actually achievable.

I think even just before we go into that, Jack, just on the the poll results, you you talked about was at thirty six percent, I think you said, have never used it at all. Yep. During Carlo’s introduction, he mentioned it mentioned an interesting point where AI has been around for just over seventy years now. But generative AI, which we’re a lot more familiar with, so your ChatChipts, your Gemini, that’s that’s coming up to three years old. But it’s been in our day to day for the last fifteen years for the vast majority of people. And for some other people, it’s been in there for a lot longer.

So when you look at the likes of your CRM systems that you might be using, so your Salesforce, your HubSpot, or you look at some of the tools you might use for your marketing campaigns, or if we even bring it into your home and you look at if you’ve got an Alexa in your home or you’ve got a Siri in your home, they’re all using AI technology underneath the hood. Now it’s not generative AI, which is the the latest, iteration. And as Carlo mentioned, that’s the kind of the new one that’s put up more into our hands that we’re familiar with. But AI is a technology that’s been around for years, and we’ve been using it for years without necessarily realizing or knowing we’ve been using it, per se.

It’s just more now with the recent change, or just recent new new, new iteration of it that we’re like, okay. I can now potentially see a lot more tangible benefits in front of me. Now it can help me plan my holiday. Now it can help me look at a recipe for what I’m gonna cook for dinner tomorrow night based on me putting a picture of what’s in my fridge.

It can now do that for me, but it has been around for a long time. And one of the things that that, that I found very interesting when I’ve done a lot of my workshops and and some of the ones I’ve done with Carlo before is the amount of people who say, never touch it. We don’t use it. No.

I’ve never touched it all. And you’re like, okay. But have you got Siri? Have you used Alexa, for example?

Yes. Okay. Spotify, Netflix, again, they’re all using AI behind the scenes to be able to make their recommendations for us. So from that perspective, and one of the things that we talk a lot about in our in the different, different workshops we do is it’s not new.

Now general AI is new, but but the underlying concepts and technology are not new.

Yeah. Can I have something on that, Rob? Can I just jump in on that and give an example in the print industry? Because I think I think you just hit the nail on the head. Most of the people probably joining this call are using Enfocus and Enfocus applications.

If you’re using Enfocus applications and Enfocus switch, for example, please just give us a thumbs up in the chat. But for example, those guys have been using those kind of technologies under the hood for the last ten years. People that have MIS systems. MIS systems are using that kind of intelligence when they’re working out pricing.

Web to print personalization, XMPI have been using something for some time. So I think Jack could really, support Rob’s point here. Yes. It’s in the home, but it’s also been in the print industry for about ten years.

And, actually, I think we forget how advanced the print industry is with its technical, prowess.

And, actually, we’re too focused on the fluff, and we’re not we’re not we’re missing the point of the function. So, yeah, I just wanted to get some examples there, Rob. Hope you don’t mind me. Yeah.

Yeah. Yeah. No. No. Very good. Now back to your regular broadcast. So so what’s actually kinda in it or or what can you do more?

Let let’s make it more tangible today. So because there is a lot of hype. There’s a lot of excitement. There is a lot of potential.

Like, generative AI has has been a massive development and has really changed the game. So we’ve got kinda three case studies up here in front of you. The first one, although it’s in in industrial real estate, what we like to do a lot of is is take stuff back to concepts.

Right? So the client that I was working on with this one, this is for their customer experience team. Okay? So nearly every organization of some sort, large or small, is going to have a customer experience team.

Now it could be the CEO is still the customer experience person, depending on the the size of your company, but there’s still going to be somewhere someone in there for that. And one of the issues these guys had is they were a massive company that they were a company that leased, physical land, leased offices, leased manufacturing spaces. And they had an issue where if one of their clients had an infraction when it got reported, it took anywhere between forty five to sixty minutes for the customer experience team to be able to figure out what the infraction was done by the client, look through the rule book, figure out what the next step should be, what’s the penalty as a result of this, what’s the process if that penalty or if that if if it isn’t remediated within a certain amount of time, etcetera, and what’s the next steps from that.

Then put that to the relative situation, then put the email together, and then send the email to the client. Alright? And, obviously, when it’s an email like that, you have to be very careful of how you word certain things and your tone and your empathy that you come across with, depending on the issue is key. So it would take them anywhere between forty five to sixty minutes.

They would have twenty plus to thirty of these issues a week. Okay? That would take them this long. So if we call it an hour per issue, you’re looking at thirty hours some weeks that they would take just on this.

And it was a customer experience team with about ten people. So what that also meant was depending on the person who came across the issue, they might pick up a different rule saying, actually, you broke rule five point one instead of seven point two or voice a versa, things like that. So there was also no consistency across the board where everybody had a kinda slightly different view and everybody would word and email slightly differently as well.

By bringing in a GenAI solution, they were able to take this down to a five minute per case. So they were able to feed pictures from the infraction as well as this description of what had happened into the GenAI assistant.

The Gen AI assistant looked through the rule book, came back and said, here’s the three three rules, three infractions that we think they may have broken. This is the one that I would that I think is the highest scoring. So you still got that human element to review and go, I agree or disagree. Actually, it’s number two.

It’s number three. And then based on that selection, then wrote the email out to the client. Now again, the human still reviewed that email. Alright?

So you still have that human in the loop process that is key. The human still reviewed the email, made sure they were happy with us, with the tone, with the the wording used. And then that was all was sent off to the client. But next thing you’re looking at a fifty five minute saving per incident, thirty of those a day thirty of those a week, sorry.

You’re looking at a twenty eight and a half hour saving a week. It’s nearly a full time employee. You start breaking that all over a month, over a year, and that’s a massive, massive saving. But and this is where I think a lot of people also when it comes into AI adoption and speaking about it, It’s not always about the financial element.

So, yes, we can say, okay. They gained efficiency. So, hey. Right. Because I get them time back in their day, maybe they were able to do something else.

As a customer team, maybe they were able to get back to more issues faster. Fantastic. That’s great. But also from the customer experience agents themselves, this was a boring, tedious task that none of them really enjoyed doing.

Doesn’t sound like fun. You have to enforce the rules. No one’s really, really likes that job. Sorry.

There’s a few people that like that job, but the majority of people don’t necessarily like that job. So this was one where they were, as a team, they loved this because the experience that they actually had from improving this process was massive for them because it now turned what was a fifty five, sixty minute process that they didn’t enjoy into a five minute process that was extremely more efficient. And they felt actually that they were adding more value by curating what the AI tool was feeding back to them rather than having to spend a load of time doing the research, read through all the rules, make sure they understood it correctly within the context of the situation.

So for me, I I love this one because it’s not just about the time saving. You also get that experience element improved in it as well. But that can be taken, although this isn’t where you said, that can be taken to anywhere where you have a customer experience team who’s looking to either solve problems or who’s coming across issues from a customer. How can we go through our processes that we have today and make sure we’re identifying the right way to solve this solution to solve this problem from the client?

Your concept is the same, and we talk a lot about concepts in the different workshops. We do.

So, Rob, this is, I really like this.

Actually, if I’m understanding exactly, what you’ve got is almost like a standardized process and standardized response of that notification out. Is that right? Yep. So if you look at the benefits of standardizing the process and getting you still need the human in the loop, which is what you mentioned. Right? Human in the loop being AI AI gets a load of work done and then the human will then edit that email, let’s say, or fact check a few things just to make sure it’s correct before it goes out. What I really like about this is that if you’re let’s say you’re heading up a team of sales people in a printing company and you’ve got fifteen sales people and each of those fifteen sales people are getting an output out, a proposal, or they’re getting a quick quote out, or they’re doing something like very bespoke in terms of maybe design services as well as various different printing on various different assets.

From what you’ve said, one of the massive benefits is the fact that you’ve now got like a standardized tone of voice and standardized persona of the business, which is being received by the markets. Right?

And that then that for me is cool because you’ve now got doesn’t matter if you talk to Bob, Peter, or Paul, you’re going to get your organization persona replying back to you with the human in the loop to give it some personalization.

But what really excites me about this is the fact that once you’ve done that once, you start then improving the process, you’re improving the outcome for the whole organization and you’re no longer trying to improve ten people, ten salespeople.

What you’re doing is you’re improving all of them by making small adjustments, small improvements to that proposal process and then extrapolate that out to everything, right? Imagine delivery services or imagine engaging with primary partners.

It’s not you know, it’s not just in one area. This is a really cool use case. I really like this.

Yeah. I think, Carlo, I see two other things. It’s funny you say that. I see two other things jump out at me. I see first of all brand consistency.

So with the process, you have brand consistency. So, therefore, like you say, you’ve got your ideal customer fit you’re going after. You know you know how you know, who you wanna sell to, but you then got the brand consistency. The brand’s gonna be consistent time and time again.

You can relax. Therefore, you’ve got volume. But, also, this goes back to what you guys were were sharing with us in January. It’s all about finding those I think it was one percent one percent on every task.

Eventually, you get a day back, and therefore, that allows you to scale because now if you’ve got a day back and you can do more and more volume and so on and so on. So, again, I just think it like you say, Carlo, it applies to everything.

Yeah.

And I would say it’s a what you’re saying, I think.

This is what you’re saying, Rob. Right? So this might be real estate use case, a real estate focus, solution or engagement, but actually from a conceptual point of view and Rob and myself, we’re we’re completely in sync on this message in the market.

If you can crack understanding how AI is being used from a conceptual level, wow, you you’ve now opened up the world because you can now apply what Rob’s just spoken about to maybe a legal team or maybe to different facets of the business. Right? Because what you’re doing is you’re you’re taking a process, you’re improving the process that’s used by many. So it’s like it’s from a conceptual level, it’s brilliant. Brilliant.

I would I would touch on on two pieces there just to to add to that, and we’ll move on to the next one is, Carlo, you talked around the kinda like the that incremental gains moving that piece. This one in particular, like, this was this was a some week long engagement to do. Right? So a lot of what we also see online is going, oh, it has to be this big transformational piece.

It has to be it’s a six month, it’s a nine month, it’s a twelve month project. Doesn’t have to be. When you look at those, as Chris said, those one percent gains, those incremental gains that will add up to the bigger piece, they don’t have to be six, nine month long initiatives projects we go before you begin to see value. This was a sub one week engagement to get in, identify the problem, find the solution that works, test the solution, and then put it into production for a moment.

And they’ve been using it ever since very happy, and we’re we’re now looking at the next areas. But the other end the other piece you also mentioned there, Carlo, was around brand consistency, and and, Chris, you touched on that as well. Brings us very nicely onto to the second one. So second one is ecommerce.

Right? And I’m sure a lot of a lot of the the people on this webinar today, they although they might be they they might say they’re printing companies, they would also be ecommerce ecommerce companies very close intertwined, right, with them. And a lot of our customers are potentially e commerce companies as well. And and one issue that that’s one of the ones I worked with had was they were adding they were growing pretty quickly.

And they were adding anywhere between twenty to fifty new skews every single week.

And what they struggled with was getting the branding and the kind of tone of voice across the descriptions and the narrative that they wanted to give for every product. Because there are a couple of different people in the team who are helping to write the descriptions as and when they came in, as and when the products came in and we’re ready to go live. And it every everyone is an individual. And everyone being individual is great, but it also means as a company when you’re trying to say, here’s our brand and tone of voice that we’re aiming for, it’s very, very hard to keep that consistent when you’ve got different people, doing it and and writing those descriptions and putting that information together. So what they used was built we we worked with them to build a very, very simple process where we would take their guidance on the brand voice. So everyone will have a brand voice guide a guide.

We took the images that they had for the new products they were going to put on, so a couple of images per SKU. And then we we gave some sample descriptions.

And we put that into an AI system and got that to give us out drafts. So, again, here’s one. Here’s two. Now interestingly, when we first started off, the client was like, I want five examples.

And I was like, you do, but you don’t really because our goal here is to stay on brand consistency. So you think you want five, but, actually, I’m going to give you two Because we’re also people where we think we like choice, but we don’t want too much choice. So give us too much choice, and then that will delay and delay and delay our decision. So we did a little experiment with them is we took before we did any AI work, we took five of their team who who have written product descriptions before, and we kinda set them at an individual desk where they didn’t talk to each other.

We get them pictures of the same product and they said, here, write us the description. And they had the exact same tools that the AI tool had. Right? They had the brand guideline in front of them.

They had example descriptions in front of them, and they had the pictures.

And the and the the team I was working with, the marketing the head of marketing was working with him and said, okay. Now let’s look at all five. And was like, oh, I like this. I kinda like this.

I kinda like this. It’s okay. But if we only looked at one from Jimmy and this was the one this was her previous process, would that have gone online? Yes.

It’s like, okay. So see where the the the piece of options can kinda take away because now it’s slowing us down. So we said, okay. We we we compromised.

We said two options. So we have the AI tool draft two options, and then, again, you’re human in the loop. The the head of marketing picks option a, option b, and that’s the option that goes live online. Alright?

And that’s that’s it. Very, very simple workflow. One of the things I really liked about this one was we focused very much on what the process is that they have today.

Focus to make sure we understood clearly where the problems are, what the frustrations were with that process today, and what were we actually trying to solve. Because in that scenario, it wasn’t a, hey. We wanted this to be more efficient because it’s gonna save us money. That wasn’t the goal.

The goal was brand voice. That’s what we want. We want consistency in that. So by extension, options is also a bad thing.

But that’s where we went with them and said, okay. Let’s tweak your process today. Let’s break it down. Let’s do an example of how the AI tool could work, but we’ll humanize it first.

So they they understood very clearly, right, this is what it’s going to do, but we’re just gonna automate that process. Again, we ran a a test couple of test cycles that we were happy with to make sure the output and everything was what we expected, and then we we moved it on into production. But we still keep that human in the loop. So the AI tool doesn’t push the description straight out onto the website.

They still go for review, but now it’s a lot quicker, simpler process, for it to then be passed and then to be put online. And this now took that, the highly repetitive task, down to a few minutes because it’s now just the review. Decision about that stuff.

Rob, that that point about the human in the loop, can we come back to that later on challenges? Because I wanna make a really important, marketing lesson we’ve learned from talking to marketing consultants in the AI space on the human in the loop.

Definitely. And and the last piece I’d I’d say about this one, similar to the one above, again, it wasn’t a, hey. Here’s a six month transformational project road map that we need to go on. This was also a a a sub one we can get.

Right? Come in. Let’s identify where we wanna focus. Let’s understand the process as it is today.

Let’s understand the pain points we’re trying to solve for, and that’s what we will aim to to solve and achieve.

Let’s and, yeah, let’s go with that. And that was that was what we did here. It’s it’s interesting.

Everyone’s caught up in their day to day.

Right? Everyone’s really busy.

No one can afford time.

But I think deep down, we will know what we need to do. Right?

If a business defines its needs, AI will define its business value.

You need to take time out to understand what’s going on, what’s working, what’s not working, where do we have inefficiencies so that you can then focus on the right area. And so it looks like, Rob, from that example, you’ve the additional benefit you’ve given is you’ve given them this ability to take a step back and have a look at the business challenges they’ve got and the best way to approach resolving that. And so and I know that when we’ve spoken when we’ve spoken before, a lot of the work that we do during the discovery actually acts as this mirror back to the customer.

And they’re like, woah. That’s really interesting. I haven’t seen my business in this way. So the added outcome you’ve got there is you’ve helped your customer to be able to see not only the business challenge, but different ways of approaching that in in a way that maybe they they wouldn’t have done.

Yeah. Yeah. Yeah.

Clarity. It’s clarity, isn’t it? It’s step back. You know, are we functioning correctly as a business? Are our workflows efficient? Are the people efficient?

We’d really, AI is a trigger to to for that thought process. You know, we you could have done that without AI, really. It’s just when you’re now bringing structure to a a mindset.

So Yeah.

It’s good. It’s good. So I will oh, we got Jack back. Hi, Jack.

Hello, gents.

So I thought I’d invite myself back to the stage briefly just, just waiting for this one to close enough.

Take your time, though. Take your time.

We missed you. We missed you.

Welcome. So, the next one guys is a business to business services company.

Creative actually by its business function. They work in exhibitions, and they have their product is essentially some creative design around, exhibition stands.

And the focus was all around the sales teams there.

Now this organization has many different sub departments with their own sales team, their own creative teams, etcetera.

But in two, they recognized that the proposals going out were just a complete mess. There was no real standardized process.

And as a result, some of the downstream challenges they had were just clogging up their business. Right? And I’m sure everyone will be able to resonate with this. So some of the challenges that they had were that proposals weren’t clear enough, they weren’t concise enough, and two proposals, so a first proposal and a revised proposal, actually can have completely different approaches.

Because it’s almost like the salespeople were just beginning from from scratch.

Now actually going into the business and understanding this, do they have standardized proposals? Yes. Are they being used? No.

Why are they not being used? Because the standardized proposals had been evolved over time and people people found or their sales team found that they weren’t working for them. They were too long. Know, so just a mixed bag of reception.

So the approach that I always take in fairly large organizations, is to put an online survey out to anyone who’s affected in this area.

Anonymous survey, it’s really easy. People can do it, like, in the comfort of their desk or their own home. They don’t think big brother’s watching, and they’re brutally honest.

So getting that across, getting some original or some initial insights, and then having cross functional cross team workshops to really get into the nitty gritty of the problem enabled us to take diverse views across this problem which was affecting everyone. Even though they had standardized proposals which were their solution.

So an important part of what I’m going to say now we’ll touch on a bit later.

But when you’re introducing new process, you’ve got to think about change management. And I don’t mean in like in a real formal way. But you have to think about how an organization or how the workforce is going to accept or get on with with a new process.

Otherwise, you can do all of your due diligence. You can have the best improved process or solution in the world. But if it’s not being adopted, then forget it. So and the value of that is then eroded.

So in order to do that, you need to have as little friction as possible.

So I massively advocate that if you’re looking at new AI solutions and I’ll get on to why I’m explaining this in a second, you should look to the existing technologies or vendors that you currently have.

So the solution that we had here was to use the existing standardized proposals that they had, which were being saved in Microsoft OneDrive, make those available using Microsoft Copilot which is an AI assistant that works specifically in Office three sixty five. And what they were able to do is use Microsoft Copilot in a structured way that would then edit the standardized proposals.

So this gave them the ability to make really quick changes, remove content bulk if they needed to for proposal revisions, And do this all in a way that was aligned with brand guidelines, aligned with messaging, kept those little legal notices that they needed in their proposals, made sure the pricing was structured in exactly the same way.

And what this did was made it quicker, faster, more efficient for the sales team to get proposals out.

But also it gave so much better clarity from a customer receiving them because the proposals were structured in a very clear way.

And what this resulted in was a huge clarification meetings being dropped to ten percent from sixty percent of all proposals that went out. Now just imagine the reduction of the workload there and then the time that these sales people can now put onto other sales activities.

And objections reduced by seventy percent.

Increase or reducing the sales cycle by thirty percent overall. Now these are huge outcomes. Right? And actually when I look at Rob’s two first use cases, two case studies, and I look at this, If we look from a conceptual perspective, what we’re doing is you’re you’re improving a process, standardizing it, getting clarity out so that you can get clarity back, removing friction.

So, like, yeah, they’re they’re very similar from a conceptual perspective, but I think it’s important to highlight that you want to be looking at the existing tools that you have.

A lot of advice I give to customers is invite your existing, technology vendors in and ask, what have you got going on with AI? Because there might be something that they’ve got that you’ve got access to already that you haven’t been made aware of.

Yeah. But I the the other piece I like from this one, Carlo, is is well, I suppose two big elements actually. First is the interaction with the customer point has now just drastically improved. So great. We’ve saved a load of time because we don’t have objections coming back or we don’t have clarification.

But also my service to my customer has now drastically improved as well. So that customer experience element that, you know, mightn’t necessarily have been talked about much in terms of there’s a value here. Actually, that has significantly now improved because they’re not coming back asking me as more questions or as many questions because they are a lot happier, a lot more clear with what we’ve given them. That’s going to give us extra points and bonus points in the tender, which is fantastic.

And to Chris’s points, earlier on around cutting through the hype, that that one percent piece here, in all of these scenarios we showed you so far, we haven’t said, hey. I’m gonna completely transform your sales process.

The AI is transform no. No. If we look at the last one, Carlo, that picked a certain element of your sales process end to end, focus on the proposal part specifically and said, okay. Let’s go and work on this. And that’s where you get that one, that two percent gain in that overall piece, and then you begin to build your momentum from there.

Also to to Carol’s point around the that change management element, bringing your stakeholders in is key. And by also taking this kind of approach and and correct me if I’m wrong with this, Carl, but I make I make an assumption. Don’t like making assumptions on this, but I make an assumption.

Go ahead.

Go ahead. Because this use case was so successful that then the same team is more open to adopting another AI solution in their current workflows, but also, normally in my experience, success breeds success. Right? So next thing, because this sales team is talking about it, the teams that they work with very well, the technical team maybe who sometimes have done build a proposal, they’re going back to them a lot less now.

Maybe the marketing team who they might depend on from some elements, they’re going back to them a lot less now. And part of that will be they’ll be saying something because we’re now using AI in this way to help us here. And that success will then begin to breed around the organization where they want to look at adopting AI tools into their workflows. And that’s what’s going to help your your kinda more company wide adoption, your bigger transformation piece.

Well, can I just jump to just jump on that point real quick? Because I we we discussed this in Berlin at a global, conference. And one of the things we we were talk I was talking about was that point about adoption from management level, getting everybody on board. And I asked a few of the people in the crowd, you know, does your teams have any fear over the use of AI in their day to day?

And everyone said yes, but I was very lucky. I had a very nice audience, and they were very pro AI, and they were I’d I’d say probably business owners. One of the things we shared in Berlin was an example of a very proactive, forward thinking, print shop owner who’s actually got his older generation, fifty plus workers in for extra training. And he’s now not only empowered them and got more than one percent out of it, but they’re back in love with their job again.

They’re now less fearful of tech, and they’ve embraced it because the attitude from the top has been right to embrace it the right way. So I just want you to share that because we are seeing that in the print space where the right leadership with the right mentality is getting even more out of people that society tells us should be on the scrap heap. You know?

Chris, this is really interesting. So we released a white paper today on the print industry, AI adoption in the print industry. And from there, sixty percent of management actually don’t feel confident that they actually understand what AI is.

Despite that, nine ninety percent of sales and marketing were dabbling with the use of generative AI in their businesses. So you’ve got the leaders, majority of them don’t really understand what’s going on. Instead. Yeah. They they they don’t have confidence in their understanding of AI, let alone how it can be used in their business. But while that’s going on, you’ve got their employees beavering away, experimenting with AI without any kind of structure, guidance, any kind of rules.

And so you’ve got this shadow AI, we call it, where people are just doing things of their own accord, which is good because they’re taking the initiative.

But as a business owner Yeah. Not want people to be running around wild like the wild west. Definitely.

Willy nilly.

I lied. I lied to that. It’s interesting. So one of the when we go in and we when I go in to map out a a kind of process and a workflow for the clients, it it’s massive the difference you see between what the management will tell you, here’s how the process and workflow works, and what the people on the ground who are actually executing the process and the workflow works, and and what they will tell you.

And it’s it’s cool when you when you sit in the room. So what I’ll do is is I’ll kick the managers out of the room. I’ll kick the leadership out of the room, and I’ll go, okay. Give me the we’ll have the frontline team in here, and we’ll talk to them.

We’ll get their understanding. Because at times, if you still have management in the room in the room, they can be afraid to speak up. It’s a little bit like Carlo’s anonymous servant. Right?

Everyone will kinda talk when they know it’s okay, but when you’ve got if you’ve got big brother watching, it can be a little bit harder to to share what’s really going on.

And and one of the stats that always comes back, every single client I’ve done this has always come back with. Before I do that, I’ll speak to management. I go, okay, guys. As a company, where is AI?

Are you using AI? And you’re like, most of the time, no. No. We haven’t rolled it out.

We’re not really doing that thing with it. We’re not sure. It’s like, okay.

And then you go to the individuals themselves. And we start talking about process, and they’re like, I’m like, okay. Are you using AI? Yeah.

Yeah. Yeah. I use ChatGPT to help me with this for work. I use Gemini. I use Copilot.

I use MidJourney. I use this. I use this to help me with this for work. Okay?

So you’ve got your frontline team actually using it to help them do something, and you’ve got your management and your leadership with the boss going, no. No. No. We’re not using it at all.

And the thing I find really, really interesting about that is when you speak to the leadership team, one on one so, again, take them out of the room and and have that one on one conversation with them and you go, okay. As a company, are you guys using it? No. No.

We don’t use it all. No problem. You’ve said it to me already. That’s fantastic. As an individual, do you use it?

Yeah. Yeah. I use ChachiPT to help me with this. It’s normally a work related scenario.

I use Gemini. I use this. I use okay. Fantastic. I use Grammarly. Grammarly is an AI too.

I use Grammarly to help me with this. Okay. So you’ve even got where at a at a corporate level, a company level, like, no. We’re not doing it.

We’re not doing nothing with it. We don’t know what we’re doing. Okay. But at individual levels, they’re nearly all using it to do something for work.

So we’ve got that that big kinda gap that that exists to to Carol’s point around that shadow AI piece Yeah.

Where your team and and I’m sorry if there’s anyone on the call who’s like, no. No. No. My team definitely don’t use it a hundred percent.

We don’t use it at all. They do. Sorry. We don’t want to break the news to you now, but they do use it.

But but that big gap that exists, and I think that’s also a piece that’s for me, is is kinda feeding into that hype element as well because you’ve got people talking about maybe kind of what they’re doing with it, but they’re not talking about it from the full concept of here’s what it’s like inside an organization. Here’s how we do it as an organization level. They talk about it going, here’s what I do with it for me, for my particular way that I do my process. But that doesn’t necessarily work inside in the company side of things.

When they come back to brand standards again, you know, if you’re doing it from a central point, we have central process, then everyone can use it the correct way.

Yep. Sorry, gents. Is it alright if I just chime in for a moment? We’re just gonna have to move on to the road map.

I can’t believe how fast the time’s gone. Honestly, forty five minutes already. But, yep, if we wouldn’t mind moving on to the road map just because I feel like that’s what we wanna leave people with, just a real good idea of where to go next. So let’s, let’s crack on with that.

Chris, if you can I’ll take off, guys. So, in your business, there are in every business, there are three ways of looking at how to progress with AI. Number one is the low hanging fruits. This is your workforce, workforce productivity.

This is the people in the business.

Here, you’re looking at tools, really. Honestly, you’re looking at Gemini, you’re looking at Claude, you’re looking at ChatGPT, which incidentally, for me in my view is probably the generative AI tool that everyone has access to which has the most value to an organization because there are so many different ways you can use ChatGPT.

So this is all about people, this is all about their tasks, their activities, their workflows.

The second area to look at are the business processes.

So once you’ve got the employees, the workforce working a bit more efficiently, a bit more effectively using AI, the next roadblock in the business is usually the business process. So yeah I can get my proposal done correctly, I can hold a meeting very well because I’ve done some research about my customer. Next thing is the nightmare process of getting a proposal out. This is a business process.

Or damn, I’ve been really successful and I’ve closed the deal. I now need to place an order internally. Like, you know, these business processes. So business process optimization is the next area to look at.

After that, or in parallel, but maybe as a third priority, are the core business systems.

So Chris will be able to talk about this probably a bit better than I I can for the print industry.

But here, we’re looking at AI inside some of the massively high cost machinery that you use and the, two print services that you have. So these areas, it’s a bit like open heart surgery. Right? You get this wrong. And to Rob’s point earlier, confidence breeds confidence.

So you wanna start with the low hanging fruit, move to the business processes.

Yeah. Only then do you have the confidence for the real open heart surgery. So I don’t know, Rob, would you you agree with this approach?

Yeah. Yeah. It’s it’s start with your workforce. That’s your low hanging fruit. That’s how you begin to build your momentum.

The other thing about that, and we’ve seen in a lot of scenarios, both of us are all of us here are the the this side of the mic have, is they’re also a very good identifier then of where to go next. Because when you begin to speed them up and empower them, the next thing they come to you with is, okay. I can do my part as an individual very well, but now this process is slowing me down. It’s not me how quickly can I build a proposal anymore?

It’s this process, this function, this this workflow is slowing me down now. And that’s a really good place to identify, as Carol said, that kind of business process optimization piece of improving them. And also what what I’ve also found, Chris, to your point around the that kinda the fifty plus group who are really, like, back to enjoying work, back to enjoying what they do. Yeah.

It’s it’s such a topic right now, and there’s there is so much hype around it right now, unfortunately.

But the hype can be a good piece where everybody wants to be involved. Everybody wants to know more. Everybody wants to be doing something with it because it’s also seen as exciting. So you can by by also empowering that workforce piece, you begin to build that excitement, that confidence back in, that they also want to begin improving the business processes. Again, you’ve less of that that kind of roadblock, that challenge. So one of the biggest if we put AI aside for a moment, when you look at any process change, any transformational change, the term digital transformation has been thrown around for years and years and years.

But that kind of change one of the biggest reasons why they struggle or they fail or you don’t get the results you expect is is because you don’t have all of your stakeholders bought in. And one of the key stakeholders in any internal process change is your employees. So, again, by kind of starting at that phase one, that first piece of getting them excited and they begin to see results, they are more bought into when you start bringing in new processes and, involving AI because I I know this will work. I know this will help save me time.

I know this will help improve an experience that I have. Fantastic. Let’s do it. Let’s move.

And you’ll see a lot greater adoption internally, and you have less roadblocks to hit.

Yeah.

And that’s what’s going to lead to your business value.

Sorry, Carlo?

No. Then you move on to identifying like the lean AI use cases. Right? The ones which are not transforming the whole business. What they’re doing is they’re making improvements in in the right areas. And then you need to like pilot these and then scale them.

It’s not about, you know, how do you eat the elephant? You know, section by section. Right? So you need to be looking at identifying those high value areas that can be resolved quite quickly and then proving that and scaling it across the business. So embedding proven solutions into the workflow and then expanding out to the organization.

Fantastic gents. Now I really appreciate you laying out this, roadmap for everybody. In the few last minutes that we’ve got and my lord I still don’t believe that it’s gone this fast. We’re just gonna get onto the q and a and I’ve got a couple questions for you guys. So first off, I’m just gonna start with Carlo. One moment.

Not top’s not having a great time at the moment, but yeah. So to Carlo, what AI platforms do you suggest we use in our business, if any? And I I mean the sort of specific brands, if you will, or or tools.

So the rubbish answer no one wants to hear is it depends what you’re doing.

But the first place for you to look is in your existing technology stack, as they call it. So if you use Microsoft Office, then your go to has to be Microsoft Copilot three six five, which is an assistant inside Microsoft Office. If you’re using Google Workspace, then Google Gemini is the equivalent inside Google Workspace.

If you’re using, tools like Zoho as, ERP, then they have something called Zia, which again is an assistant inside Zoho, which helps, across many different areas.

So go to your existing supply your existing technology and just have a quick look at what they’ve got. For me, the best all rounder without question is OpenAI Chat GPT, and I bet sixty percent at least of people on here would have had some interaction with it. If you’ve been using this every day for two years and you’ve never formally learned how to use a tool, you’re getting, like, five percent value out of it. There’s so much it can do.

Fantastic. Thank you. And I’m not sure if you guys are able to access the q and a page, but Mika has asked a a unique question, one that I believe that we could properly all answer. So, if you wouldn’t mind just taking a little peek at that and letting us know.

So the question is, in the print industry, especially automation of the workflow, this is the same road map. If you’re looking at the objectives, issues, problem areas, and what you’re looking to resolve, what is AI bringing to the table? Rob?

So I think for me, I’m not sure exactly of the the kind of direction where the question wants to go because it can go a couple different places. But what we’re seeing from a I I statue with automation. Right? So what we’re seeing in an automation space is, it’s becoming a lot easier for people now to automate processes internally themselves.

And there’s a lot of what is referred to as low code, no code automation platforms coming out that are very that make it very easy to link different tools that you may be using together to help you pass information through and automate a process like that. And if we go back to the to the second use case I talked about, we use one of those platforms to automate the process of ingesting into the images, ingesting in the brand guidelines, ingesting in the samples, putting it to an AI tool, getting the output, and sending it to the human for review. So we need an automation platform sitting behind for that.

But what I would also say is automation platforms are not for everyone. Right? You’re not it’s not there for everyone to be used. It’s it’s not a tool that anyone can kinda go and pick up tomorrow.

Although they are you don’t have to be a software developer to use them. There’s a kind of technical mindset thought process that is required for a lot of it, especially that that kind of initial learning curve.

But I’ll take that to to the second part of your question. What are we seeing in AI? Well, twenty, twenty five, depending on who you listen to on LinkedIn, Instagram, TikTok, whatever your social media platform of choice is, we’ll talk about twenty twenty five being the year of agentic AI. And agentic AI is AI agents.

So the difference between, let’s say, a chat g p t today, they’re getting there, but at the moment, ChatGPT, I would say, for example, doesn’t really do anything. The Broadwell agent functionality will put that aside for a moment. But it it’s you give it an input, it will give you an output back. Right?

You ask it a question, help me write a proposal. Here’s my guidelines, my context. It will give it back to you. Help me draft an email, help me plan a holiday.

You go to Microsoft Copilot in Outlook, help me draft an email, summarize this email for me, Copilot in Excel, help me build a pivot chart, and it will do that for you. But it won’t kinda take actions based on a decision you wanted to make or based on insights it can get. That’s where the agentic AI element is coming in. So what we’re seeing now is a kind of combination of AI and automation platforms coming together where you’re able to automate the decisions that get made by the insights that the AI tools gather from the information it looks like it looks at and analyzes, but then also begin to maybe personalize and tailor some of the content that it then builds as a result of that automatically.

So that’s where we’re beginning to maybe see the two of them come together a little bit more as well. I said ChatChimpT has just brought out agents. I said I’d put it aside for a second. It is there.

It’s it’s still it’s it’s like your very first mobile phone, right, from my experience of using it. It does stuff. Yeah. Is it the best it’s ever going to be?

No. Does it have a bit of development work to go through? It does. But it’s still something good to to get playing around with, as a starting point.

And and I think that’s where we see AI going as they begin to take more actions autonomously.

Thank you very much, Rob. And, Chris, if I wouldn’t mind asking, where and how do you see AI working with print software in the future?

And this ties into Rob’s answer to the question you just had. It’s already in in place. It’s already happening. So, those of you that may know Electron, for example, who I think were Fesper in in Berlin, they’re they’re a finishing company.

They’re already laying, the blueprint, the foundations for their customers to have, AI as part of servicing support, automatically detecting issues, and then raising tickets and doing stuff. So I see, I see helpful support and intelligence on on the hardware. I believe some of the OEMs already have that on the on the presses. I see things like automated loading coming again.

I know that some of the the finishing tables are using some of the cutting tables are using that now, so they’re looking at they’re quoting anything from twenty to thirty five percent improvement.

And I think I’ve I’ve got the numbers here. One thousand five hundred labor hours saved just by bringing AI into the automation of the mundane task of moving substrates and stuff. We already we already have it now. We’re already seeing it now in in our personalization and our web to print.

I think if you look at direct mailing now, XMPI did a demo recently where, you put your name and you put the town where you’re from. And and straight away, they’ve plugged in some of the the the the brands, the AI brands that the boys have just been been sharing. And it gave a personalized, landing page product and even did some research on the town that you’re from by using a chat GPT esque to then do that research. So I think we’re gonna have I think personalization is gonna be, is gonna be expected.

It’s not gonna be a choice. I think we’re gonna have speed. I think we’re gonna we’re gonna, you know, get time back. We’re all time poor.

You know, it’s a lot harder to do the same job than it was. And I think the amount of intelligence that we’re we’re gonna see very soon in our own industry, because a lot of these companies I’m mentioning and focus again, I come back to them. MISs, they’re now gonna be able to send quotes, instant pricing to the end user on the computer a lot quicker because the calculation speeds quicker. So I think when we’re gonna see it, I think in this year.

Next year, I think we’re gonna see a a large jump in in our in our in our software advances. But I just wanna go back to the the point the guys make. A lot of you on this call will have this software stack already. You will have an electron machine or you will have an Enfocus switch or you’ll you’ll be with a a web to print system or an MIS.

Speak to them. Ask them what’s coming down. Ask them what’s on the road map and ask them how you can get the press operator or the or, you know, or the operator to to learn about it in in preparation.

Thank you very much, gentlemen. I can’t believe again. Oh, sorry.

I was gonna say just as a final point on that to Chris’s piece. And if they tell you they don’t have anything on their own at the at the moment, ask them why. Because they should have. Because every other industry out there is moving along with AI, is bringing in AI functionality because the market’s demanding it. So if you’re a provider of technology isn’t, that’s definitely a flag to to be concerned about.

Thank you very much, guys. And just quickly before we wrap it up, I’m gonna let you guys talk to the audience for a little bit if you wanna get in touch with any of these guys. And I’m just gonna quickly mention Festa Middle East where you can actually catch all three of these guys fortunately for everyone, where we’ll be sharing some more insights. But this time, it’ll be in person.

So I’m just gonna drop a little registration link in there if you wanna check it out. I would encourage you to. It’s a really go really cool event, and it’s in beautiful Dubai so you can’t really go wrong. So, thank you very much guys.

Feel free to share your details, and I’m gonna share the link. Thank you.