DAM in 2025: From storage to intelligent activation

Session transcript

Melanie Duffy:

Hello everyone, welcome. Thank you all for joining today. We’ll give it just a couple of minutes for everyone to join. I hope everyone’s got a coffee, nice and comfortable. Very excited for this session we’ve got today.

For those of you here as well, before we get started, just a quick note, we’d love for this to be interactive. So please drop your questions into the chat as we go. We’ll pick them up along the way and hopefully have some time for a Q&A at the end of the session.

Okay, wonderful. Let’s jump off, we’ll start with some introductions while the last few people are joining.

So today we’re here to talk about DAM. It plays in the tech ecosystem and how that is all changing in 2025 and beyond. So no longer are DAMs just a place to store assets, but they’re something smarter. You activate assets, you’re connecting it into other systems and ultimately proving its value back to the business.

So today we have got two people with us who have been deep in this space for many years. First up, we have Anil, Managing Partner of TKM Consultants and Friends here at Papirfly. Anil’s worked with marketing leaders across the globe on DAM strategy, AI and change management. He’s seen where things go right, but… Well, have we lost Mel, Fred? We might have lost Mel there. Yeah, sometimes… Maybe I’ll carry on my introduction while we wait for this.

Anil Noorani:

Yeah, maybe you can start, yes. Wonderful. Yeah, hi everyone. My name’s Anil Noorani, as Mel said, I’m the Managing Partner of TKM Consultants. We specialize in a whole host of areas, marketing operations, marketing technology, creative operations, and we understand how it all fits together.

In terms of digital asset management, I’ve been involved in the industry since 99 and I’ve been lucky enough to work with some incredible clients, Johnson & Johnson, Unilever, McDonald’s, Reckitt, Mercedes-Benz, a whole host. And we work primarily with brands, with agencies and technology vendors. So we sort of have a good oversight of how it all sort of sits together and some of the challenges that organizations are having to deal with today and some of the complexities that they’re having to navigate, especially around optimizing their technologies and getting their maximum investment and ROI. So that’s me. Sorry, Mel, I just took over because we lost you for a moment.

Melanie Duffy:

Yes, thank you. There’s always going to be some tech problems, right? So thank you so much for Anil. And joining him today, we have Fred Sanuy, CEO of Activo and owner of DAM News. If you know Fred, you know he’s not afraid to cut through some of the hype and really tell us straight, especially when it comes to things like AI and DAM. So Fredrick, welcome. Is there anything that you would like to add to your intro there?

Fred Sanuy:

Yeah, first of all, thank you for this organization of this new DAM webinar. We are very exciting subjects. So yes, I’m the CEO and co-founder of Activo. Since the last five, six years, we are an independent consulting company here. I’m also the owner of DAM News. Maybe you’re aware about this most well-known website. And also we are trying to organize events in Europe and especially in Paris, we even DAM Paris. So a lot of things around for the DAM community to bring some awareness, best practices and knowledge.

Melanie Duffy:

Thank you so much. So between our amazing speakers today, we’re going to cover how DAMs are evolving, what’s real versus what’s buzz and where organizations should really focus on to get their ROI. And lastly, before we jump in, a quick intro from me. I’m Melanie Duffy. I work product here at Papirfly looking after both our DAM and our brand portal solutions. My role is all about working with our team and our customers to really help evolve these products.

So for anyone who doesn’t know as well, Papirfly, we are a DAM and on-brand content creation suite helping brands manage, activate and distribute assets at scale. So they can stay consistent and move a lot faster. I’ll be guiding today’s session and making sure that we dig into the topics that matter most.

As I mentioned at the top of the call as well, this is quite interactive. If you have any questions, please feel free to pop them in the chat. I’ll be monitoring that throughout the conversation.

So with that, let’s dive in. Today, we’re going to be discussing the industry as well as so DAM where we are. The industry as well as the latest Forrester DAM landscape report that was released last week. There’s lots of talk about this idea of intelligent activation. So moving from a system of record into a system of action.

So this is where I really wanted to start. Historically, DAMs have always been quite static libraries and now they’re expected to really activate content. So Anil, I’m going to throw to you first, from a buyer and a CMO perspective, what does activating assets actually mean? And can you outline for us that spectrum or different sides of what activation does?

Anil Noorani:

Yeah, it’s a great opening sort of statement and an area to explore. And as you said, Forrester talk about moving from a system of record, which I still don’t think we’ve completely nailed down effectively by the way, to a system of action. And when I saw that line actually in the Forrester report, I started to think actually about the sort of journey that one goes on and sort of the spectrum really of digital asset management and how you can maximise it.

So on the left hand side, at the start of that journey, the early part of the spectrum is all about storage. It’s all about finding assets. It’s all about making sure that you are starting to lay the foundations for brand equity globally. So your content is obviously managed consistently. The customer experience is consistent and you can sort of get a return on your investment around reuse and repurposing of assets. So storage is still something I think that we are wrestling with in terms of search and AI is going to play a huge part in that. And I’m sure I’ll come back to that in a moment.

And as you sort of go down that DAM journey and you start moving towards action, I think where the market currently sits is really around this world of sort of composable technology, DAM as a composable solution and interacting and connecting with other solutions in the market space or in the brand ecosystem that CMOs and market directors are heavily investing in. So PIM, which I know is an area that Fred and his team have got huge expertise in, CMS platforms, DXPs. So this composable environment where everything is connected. So you are making the most of a single asset across all those different touch points of the customer journey.

And I think that’s where the market sort of is really investing currently. And we’re seeing a lot of development work going into that particular area and education, I would say. And then on this side of the spectrum, to really move to action, I think is where we start looking at personalisation and scale. And again, AI is going to be the catalyst to driving this forward. So personalisation across all your assets, across all your channels, as long as your data is AI ready, that’s where digital asset management ultimately will sort of move towards. And I think we already have some of that in play today, but it’s not quite as mature perhaps as we thought it might have been maybe five years ago.

So I think that’s the journey we’re at. And I think that being connected to this digital asset management system in order to sort of deliver greater return on investment for marketing teams is where the market is currently sitting as we move towards action.

Melanie Duffy:

Yeah, I find that really interesting, that real three distinct places. The first, you spoke about their taxonomy, then making it quite composable, and then interpersonalisation. Fred, I wanted to ask you, you’ve seen quite a lot of enterprise companies really sort of battle with this at the moment. Have you got any good real world examples of companies that are successfully doing this in any stage of activation?

Fred Sanuy:

Yeah, for sure. So thanks for this introduction. We are very insightful. So to be honest, I think one of the things we have to think about is what incredible benefits we can bring to the customer impact beyond the technology. As we used to say by active or the success of this digital transformation is 5% of technology and 95% of people and processes. Everything starts finally between the my chair and the keyboard.

So how technology can improve such an experience? So regarding what we said, yes, for sure. To be honest, we’re already at the early stage of everything. Just when you are looking at what’s cooking from Nvidia, et cetera, this is, it’s super difficult to work. Just two years ago that Chair GPT was right for the market to get 100 million subscribers in about two months. So it’s super difficult. I think nobody in this world can get an idea of what can be done in the next year.

But something we can say, and as we said, in fact, we are really at the early stage regarding the down. I would say up to now that was a little bit static. And the reason why it was a super challenge and I see so many customers using SharePoint as a dam. Okay, you have folders, you have things like that because it’s close to your PC and laptop and et cetera. But it’s not super enterprise as soon as you want to drive permission, share content, et cetera.

So it’s a super challenge for a dam finally to achieve this goal. How I can make a dam with AI and metadata much more productive than SharePoint. And finally, something we see since a couple of months, I would not say two years, but it’s very early. We see some couple of AI integration that starts to think in some more. I will not say they are thinking, maybe one day, but for sure they are trying to make the assets great again.

It’s always a challenge. Something we’re always explaining to the customers, in such a project, you need a dam manager, librarians, et cetera, because they know the vocabulary of the brand, et cetera. But for sure, and especially for international brands, when you have to move from one English to the other, from French to English, et cetera, it’s sort of about the personalization at the top, as we said. And so for sure, AI starts to bring some services. But we need to keep in mind that it’s a very early stage. And reason why of this idea of composable AI, the idea is more or less to how can make something even greater and smarter in dam systems. And finally, to make the link between the AI capabilities and the control vocabulary of the taxonomy.

Melanie Duffy:

No, it’s really interesting, and you’re completely right with AI is really in its infancy at the moment. And it’s helping really activate a lot of assets. And people are using that in a lot of ways. You mentioned some there about different regions and different languages. And Neil, do you have any other unique examples of how people are really utilizing this for that, sort of going towards that personalization, I guess?

Anil Noorani:

Well, I think in terms of agentic AI and actually utilizing AI for meta-tagging content around facial recognition, people detection, object detection, descriptions, that sort of world, I think has actually existed for some time. We’re seeing a huge acceleration in that capability, naturally. So I think that’ll be the first area where we’re delivering real efficiency around how we search and select content.

In terms of the content at scale element, I think, you know, I sort of sense that we are moving beyond automation. You know, we’re jumping over automation into much more AI-based personalization at scale. So image generation, for example, for e-commerce platforms, transcreation, using templates for assets, using AI to sort of drive that. Digital twin technology is something, you know, that’s really been sort of coming up behind on the radar for some time now, especially around packaging.

You know, that is a form of automation that AI has basically taken it to a whole nother dimension. And we’re seeing a lot of that sort of capability, especially around the retail and consumer goods where actually photography in the true sense of the word is sort of, is now not being utilized quite as much. And AI is driving 10,000, 12,000 variations of the same asset in a digital twin environment.

So I think for localization, more than personalization at this stage, I’d say AI is actually delivering some significant value. Personalization will come in a much more effective way when the data governance is nailed down in organizations. You know, when the data lakes, the data pools are all sort of defined well, and we have certain structures around that data to deliver personalization that is ethically sound, structurally sound, and actually has none of the concerns around bias, et cetera, that I still think, you know, we have some issues with, we certainly have issues with around AI.

So I think that’s sort of the journey that we’re on. So agentic AI to drive efficiency, number one, then we’ll move into localization and transcreation and template-based solutions on math. And then we’ll get to very deep personalization above and beyond what we have today.

And I just wanna just quickly add as well, you know, I’m a firm believer that digital asset management, again, I wanna really reinforce this point, is a key foundation for any marketing team, brand asset team, brand management team, CMO out there. And if you can get that element right, it will feed everything else really effectively.

And so that’s a really important area. And I think because DAM’s been around for a long time, sometimes, and you know, we’ve had a lot of false starts. I think I mentioned when we last spoke, actually, Mel, you know, a CMO I work with once said marketing departments were a graveyard of failed technology implementations. And because digital asset management is not the new kid on the block, it’s been around for a while, there’s a bit of like, you know, tiredness around the change management, but we’ve gotta keep going with it because it’s absolutely crucial to driving all the other applications that sit around that brand ecosystem in order for you to be able to personalize at scale for your consumers around those different touch points.

Melanie Duffy:

I think you’ve touched on something there as well. There’s obviously a lot of things that AI can do. We’ve mentioned quite a few already. For all the CMOs or the marketing executives, they’re on this call listening. What should they be looking at to make sure that they’re choosing the right AI in the right places? How are they measuring ROI? What is important for them to be looking at? Is that for Fred?

Fred Sanuy:

Yeah, for sure. I think to be, I was there because by then I was also working with Chip Bartik and Scott Brinker. And so we have a couple of our conferences with our CMOs in this world. Of course, I think they already started the jobs in the last two years, especially around chatbots, et cetera, which when you are looking at final year, what really matters for all of these guys, it’s all about their customer journey on the website. So it’s super important to personalize, to localize, et cetera.

And to be honest, a lot of things have been done at different stage from CRM, from PIM, et cetera, especially on my side. You know, most retailers today, websites are driven by PIM systems because the PIM is just like as a glue software to organize this information. I’m working for a couple of branches like, of course, Vitality machine, et cetera. And for your information, in about less than one year, AI was able to improve final year product sheet completion by more or less 20%.

So, yes, it works. And for CMOs at the end of the day, it’s all about, as I was saying, finally, it’s to get the right content at the right time to the right people. Okay. And for sure, and especially what you are doing on your side, it’s a clear representation of that. So from the contents that can be your text, informations, analytics, or images, et cetera, you have to produce in the same time, and especially on digital channels, a lot of content, different sizes, formats, et cetera.

And we see that, especially here, I would say sometimes competition by vendors is tough, but when you see some people just like the Canva guys, et cetera, you can ask them some questions, but they are not done in the meantime. So by the way, it’s super important by nature to get this integration as soon as we can in a proper way.

I would like sometime also to say that, and this is also something coming from the customer side, most brands in this world, they have some agencies and they have some graphic chart, et cetera. So it’s super difficult for GNI, for example, to think about, I was thinking about Michelin, my Michelin customer. You have a tire, you have some shadows, et cetera. So AI can do a lot of things. It can put the tire with any type of wallpaper, but this is not the graphic chart of a brand. So at one time, this is a reason why I was saying that AI needs to think, and the only way to think for AI is to rely on some data that has been approved, certified by the customer. Reason why we see more and more integration with custom AI, and more and more people today, especially I’m part of three main projects in Europe. So where customers say, okay, you have to GPT, you have Azure, you have all of these guys, but we need to get our proper AI because we need to control the vocabulary of that. And then AI should be able to think on the right way.

Melanie Duffy:

I think that’s a really good point there where we’re moving from out-of-the-box sort of AI solutions to really now testing that personalization and getting it to really learn your brand, your terminology, and being able to activate it in that way. Anil, do you have any examples of people using this really well, or are we still at the real testing phase of this?

Anil Noorani:

Yeah, actually, I was going to say, I don’t have that many examples of people using it really well because I don’t think there are that many examples of people using it really well. I think the big challenge actually, and it’s just something that struck me when Fred was talking then, one of the big challenges is the trust factor of AI. And therefore, AI strategy has been defined at an enterprise level more than at the marketing level and certainly more than at the content level.

And as a result of that, a lot of the decisions that are made around how we engage with AI in a brand are being made a couple of departments away from where the actual activity happens. Now, that’s actually quite a challenge because then when you’re basically making selection decisions around digital asset management or even when you’re bringing resources in to produce content for you, you have a slight challenge about okay how do we utilize AI in this way? Can we use AI in this way? Because the decisions are actually being made by the CIO who works in a completely different part of the business and damn vendors and damn selection programs and I know Fred and his team are real experts here but they are also having to really educate what the parameters are around actually what’s acceptable.

So every organization’s under incredible pressure, especially technology vendors. What are we doing with AI? How are we going to deliver AI? And actually the customers aren’t actually ready to embrace it in that way. You know, we have to take them on that journey and we need to make sure that they have complete and utter trust in those large language models or you know in terms of the agentic AI, the processes that are being driven to make sure that they are suitable or in whatever format that AI is actually delivering utility. We have to make sure that the data that sits behind it is solid and acceptable and ticks all the boxes from a governance standpoint and I think that’s why there’s going to be, you know, people talk about hope and hype but we are getting to a point where there will just be a reset now. You know, we’re in exploration mode aren’t we? Once we’ve explored it all then we’ll reset and rebuild and we’re just coming into that phase and it’s taking a little bit longer because we don’t necessarily have the skill sets.

A lot of the brands don’t have the skill sets in-house to be able to make those decisions and the same applies whether using, you know, that GPT at home or whether using a digital asset management system at work, you have to be absolutely convinced that what you’re getting from that system has the right levels of governance associated with it. So that’s something.

Melanie Duffy:

So what I’m hearing here is AI is not taking all of our jobs just yet. There still is a place for us and what does that look like? Fred, I might pass over to you now. If we humans still need to be in the loop, what is that doing to our positions? How is our job shifting and where is our focus going now?

Fred Sanuy:

I think maybe one day we can be replaced or maybe you saw that just two weeks ago Gartner was launching ASCO to Gartner. So everything can happen by the way. So I think that if you are looking at this study from Gartner it was super interesting because finally customers say yes, we’d like for 78% to get AI and more and more deep dive in the technology regarding our marketing stacks. But what they are also seeing is that 56% you need to get to some human being in fact.

And you know what Johnson, the CEO of NVIDIA was saying, you’ll not be fired by AI, you’ll be fired by somebody using AI in fact at the end of the day. But as I knew also was saying, maybe you saw all of it just two weeks ago. In fact, I like where we’re starting from the chart from JPMorgan showing that in the next 10 years we improve alongside text, images and different capabilities of AI and JDI. So that’s cool but it’s in the next 10 years and nobody has any idea when it comes.

On the other side, when you see you need to process this information, you need even more calculation. And so when you saw that just last week NVIDIA put 100 billion inside JDBD, you can say, oh my goodness, what’s cooking? So for sure, by the way, I’m also convinced that it’s still a long way to go. Just like when you are doing some dam onboarding, I’m always talking about this AI curve, et cetera. And more or less now we have AI for everything. So you have for AI, et cetera, for JNI. So it’s a little bit up and down as of today, but for sure I see something shrinking and especially on the vendor. I think this is the very first year we saw by many vendors talking about authentic AI, et cetera. So for sure, of course we have marketing buzz around this, but we are not so close to do this job.

But something by where I’d like to keep in mind that we have to bring something to the customer that’s something you can use today and not in the next years, et cetera. And we can really improve this user experience just like you take an image just to provide the count of the people to get a good description of the image and facing these things that are super important for me as, for example, what we did also to talk about the language model, which are super important at that stage. And it’s going super fast. The idea also to get some nice translation of documents, but we are not so far. The ability to run some images for some actions. A couple of things that we see more and more on the Google and Apple things. And by the way, these guys regarding here, the cash of these companies, they are putting a lot of innovation inside.

That’s something we see that maybe we would like to have. I’ve got some customers say, Hey guys, I’d like to have this feature that I’ve got on my iPhone inside and out. Is it possible? That’s one of the things that vendors, it’s super challenging for them because you are facing this. Everybody’s finally can use AI at any time of the journey with your Google. I was testing your latest Google 10 Pro Excel, et cetera, with integration of C2PA, switch C2PA, which is very important by where to track the assets and the creator. Just imagine they are the only device who has a dynamic key chain for each asset. It’s Google, it’s any of them vendor or any camera supplier. So it’s going fast on the customer side and to be honest, it’s a super challenge for you.

So anything you can do to improve and to reach a gap is super welcome.

Melanie Duffy:

Mel, sorry, can I just add one more point?

Anil Noorani:

Because I’ve made a note of this. We talk about composability and that, as I said, that for me is where we’re sitting at the moment to move into this activate an action-based system. And yeah, Fred mentioned Gartner and I’ve made a note about, so for anyone who’s listening to this today, who is more in that marketing world or more in that sort of change management world, there’s composability, which is a technology design structure, but there’s also composability when you’re managing change.

And I just wanted to call this out because it’s really important as businesses now and as brands, we have to change the way in which we are thinking about marketing tech. And the composable thinking design structure is based on five areas. One is everything is changeable and that’s really super important. Number two is you need to change often and change to grow.

This is a big one, design to change rather than design to last. So the world of beer moths, sort of technology vendors, in the same way with agencies, that’s being disrupted beyond all recognition now, because they do find it hard to design to change because of the number of people they generally are carrying as organizations. Think and build modular is extremely important. And the final thing is treat change as a known tool, not as an unknown risk.

So, you know, if you plan in this way and you change the mindset of your teams to think in this way, you’ll have greater success around pivoting naturally in terms of what’s happening and making sure everything is connected. And not saying throw stuff away that you’ve already invested in, but just get more utility from it by basically bringing in other solutions around.

Melanie Duffy:

I really like that, especially the design to change. That’s something that you’ve mentioned that before, and that really resonates with me. Frederick, you work a lot with composability, connecting dams, how they should flow. You’ve then got AI going across these different platforms. How can, how does that all connect and work together?

Fred Sanuy:

Oh my gosh, it’s, I think, by the way, we’re in a period of time where, of course, it’s easier to connect everything as soon as you have some, as we are putting some API capabilities. In the meantime, it’s also weakness, because I was looking again, one of the latest reports of Microsoft, explained that 90% of weakness of the system is coming from the API, because most of prompts, et cetera, are done with the API. And to be honest, we know that because we’re also doing it’s a custom development, it’s just a nightmare to check everything as soon as you have an update.

But by the way, something I see here, by the way, regarding these AI things is, I’d like really to repeat again, and I’m working a proof of concept for a large problem. I cannot tell you at that moment, but in fact, we are really working of a social data, in fact, because at the enterprise level, the dam is a foundation of the asset, which is super important, by the way.

And again, I repeat, a dam is an engine for the assets and the metadata. It’s nothing else around, it’s just some custom things, et cetera. And we don’t have to confuse anything else. It’s all about the data itself. So on my side, it’s always a PIM system. You have some, of course, in between or before, after CRM, CDP, and et cetera.

But I would say alongside this information, that’s something which is more and more easier to synchronize, to syndicate, because API was just a piece of cake. But something it’s important, by the way, for whatever the piece of text you are, is all about this structured information that you have because social data is one of the most important keys to making AI analysis useful. Instead of a black box of unspecified keywords, et cetera, composable errors, you’d create structure and semi-structured data information.

Just like I’ve here told the data that specifies what the data is to control the value feeds, to add to standard feeds, to integrate with your taxonomy. Again, it’s super important in order to get a very top level data.

And something we can say, by the way, in this large ecosystem, the current state of the art, finally, in this current state of awareness, is a process which is called Retrieval Augmented Generation, RAG. And RAG processing can take your structured information and read its own knowledge base.

And finally, what I see on the market side, PIM vendors started two years ago, but they just have to manage this type of information. But it’s super important to structure this information. And at the end of the day, it doesn’t matter. We’re talking always about brand management, about a user experience. Okay, it’s really important for the global onboarding. But as soon as you don’t have this data lake up and running, a structure, nothing you can do.

It’s all about finally, these incredible benefits are always talking to the customer. I’m also working with some retailers in the US. When you have hundreds of channels of syndication, I can tell you it’s a nightmare. Amazon sometimes is changing the rules. They are not sending you an email to say, hey, we changed the world. So you have to put a lot of mechanism between the dam, etc.

Of course, today, the dam is really able to leverage your assets alongside these platforms, because we have Dynamic Accentual Transformation, we have SEO, we have GEOR, etc. And just with a simple URL, very optimized with WebP ID, etc., you can really streamline your content with performance.

Melanie Duffy:

Yeah, I think it’s so interesting, because over the last 10-20 years, it always comes back to a very core principle that you have to have good data to be able to get good insights, to be able to get good personalization, and it always seems to come back to that. So it’s good to know that the marketing executives, everyone listening to this, that really focusing on that clean data is so important, because AI is not going to be able to fix that, right? It will enhance problems with your data if there is issues at that core.

Neil, is there anything you wanted to add on that data perspective?

Anil Noorani:

I mean, just to reinforce the point, really, I mean, even at the weekend, I was watching a fairly large golf tournament that I’m sure some people also were watching alongside me. And Capgemini were advertising in between every shot, and it was all about being data AI ready. It’s such a big issue, this, for organizations, because without the data being effective, being governed, having the right levels of due diligence as they come in and aggregated and collated effectively and cleansed, none of these solutions are going to really work in an effective way.

And I think there’s some great studies around how companies are investing in their MarTech at the moment. And actually, for a lot of organizations, the solutions are very, very sound. I mean, PaperPly is a great product, right? It’s got huge capability, utility, and I know it quite well. It’s, you know, a lot of my clients have utilized it as well. But to take it to the next level, yeah, the data is going to be absolutely crucial. So you can get that next level of ROI from it.

And I think a lot of organizations struggle a little bit with turn on investment, because they’ll think that these assets aren’t being reused or they’re not being localized effectively. Well, actually, you just sort of need to take one step back from that. It’s not the technology that’s the issue. It’s not the user experience. It’s just the way in which that information is either coming in or being managed externally to the actual product itself.

And so data, yeah, that is, it’s becoming, it’s more important now because of AI than it even was, you know, three or four years ago. So absolutely crucial that those, it’s interesting, you know, I agree with what Fred said as well, you know, we’re not going to lose our jobs to AI, we’ll lose our jobs to people who know how to use AI more effectively. That’s a really important point. You know, we need to embrace this world and actually ensure that we have a very strong strategic AI guidelines in our businesses around data and the impact of that data on our Martech solution, our Martech stack.

Melanie Duffy:

Yeah, I think that’s a really good point. I think we’re all on the same page with that. We’ve got a really interesting question from Charles in the chat here. So I’ll throw it out to both of you. With all these integrations and add-ons, how do you stop the dam from becoming complicated for everyday users?

Fred Sanuy:

Great challenge. Yeah, I would say, yes, it’s a very good question, by the way, because, you know, on our side, we shouldn’t do that, but we have some services, which is dam health check, okay. So we’re more or less just when you are sick, you’re asking to your doctor what’s going wrong. And I think many times during the last five years, we see some big issues regarding sort of the management of the people and et cetera. So it’s really a challenge to be honest.

And especially in this world, this world is a bit crazy because we’re asking to people who do everything yesterday. It’s all about the KPIs. It’s all about some investments. Sometimes some brands, they are spending tons of money for nothing. And as soon as you’re asking for some budget, just for your dam system, it’s just like as a big pain.

So I think as usual, it’s all about mindset, strategy, and vision. Hopefully, I would say in this world, when you have the right people, the right CMOs and see something, you are the winner. And you are the winner. I’m used to say, if you pay peanuts, you get monkeys. So it’s important to get the right people. And as soon as you are confident with the people and the skills, soft skills, technical skills, you are the winner.

And that’s the reason that you have the gap of this world. We are the number one because we have the best guys. That’s all. And for brands, for sure, it’s a challenge. And especially, I can tell you in France, we are in a period of time which is a little bit complicated. So we’re more or less, we want to stop everything. We want to stop license. We want to stop, et cetera. We see some bad things coming from re-transfer, drawbacks, et cetera. It’s really a pain.

So the reason why AI can solve a lot of issues, by the way, you need to get some human on the daily business to make it successful.

Anil Noorani:

I’d also, just to add to that, I mean, I think there has to be a real focus on trying to automate what you can because that’s the bottom 20, 25% of like the drudge work that individuals have to go through to make things operate effectively. That really can, a lot of that can be automated. And I’m really excited actually about Gen2KI and the impact that can have on ensuring that the assets themselves, the way in which they can be found will be much more effective moving forward.

So I think if we can really hone in on, automate what we can just to get the efficiency levels driven in, and also it’s all about user experience. I would say that’s the first thing and AI will really add to that because obviously it can make the content more effective.

And I’d also suggest we need to, with every technology implementation I’ve done or been part of, and there’s been many, we have seen a lot of great stuff and a lot of terrible stuff. We’re still extremely poor at communicating objectives, right? And so we need to absolutely, I think actually Fred mentioned talking about vision and purpose, these technologies have an objective and that can sometimes get lost for the end users when we’re sort of rolling this stuff out.

So there is a technical complexity, which I think can be alleviated through greater automation, but we should treat these technology projects at a very human level and ensure that the, you know, we’re not trying to like boil the ocean, there is iterative change that’s developed to ensure that we are making, you know, we’re not going to suddenly get 99% ROI on every asset, it’s just not going to happen. But we just need to ensure that we are making steady progress and, you know, alleviating some of that complexity for our end users where possible.

Melanie Duffy:

I completely agree. And I was going to add on to that as well, that there are so many things that you can do with AI. I think a big part of it is focusing on the one, two, three things that you can do really, really well. And knowing what those outcomes are that you want to get from it rather than trying to try everything perhaps. So I think that’s really good advice. Have the right people. UX is going to become even more important. Automate what you can and really have a focus on what problems you’re trying to solve and do them well.

I think this is a really good place to pause. We’d love to hear from you all now. If you’ve got any questions, thoughts, even challenges that you’re facing with your DAM and your own organisations, please feel to drop them in the chat. We’ll try and tackle as many as we can.

But I think it’s been a really interesting conversation here. We’re talking about how AI is really changing the way that we’re activating assets. It’s no longer a place to just store assets. It’s where you sort of used a great word the other day when we had a chat, Anil, where a DAM is orchestrating the assets, orchestrating change. It’s connecting in with things and it’s bringing that data back so you can really understand how all your assets are performing.

I think it’s a really interesting space. We’re only at the start of it. People are still really important. We still need them in the loop, especially when it comes to governance. We’re not at a point yet where we can just sort of let AI go forth and trust all of the results. There’s so much involvement that we still need to have, which I think is really important.

We haven’t had any questions come through, but Fred, was there any final closing thoughts or advice for the audience that you had today?

Fred Sanuy:

I would like to say to stay young and foolish, as Anil was saying. I think it’s important to be disruptive, to challenge, to stomp, to test. Most of the customers today that we’re working with are seen as an MVP or proof of concept of everything.

Something I would like to dream is, of course, for vendors to achieve their dreams, because finally, everything is on your side. We’re just trying to help the people and customers to find the right path to take. It’s super important. 25 years ago, when Steve was back to the business, he said one thing, one thing we miss is finally to understand how people are working. We need to sit close to the customer to see how they are working. Then back also to the engineers and not do something on the other side to get some bullet points of teachers and try to sell it. It doesn’t work.

So both advice for the customer to be here to test and learn and on the other side for the vendors to be very disruptive, to provide us with the best experience they can do.

Melanie Duffy:

I completely agree. What about yourself, Anil?

Anil Noorani:

Yeah, I think when I consult with clients, one thing I always lean in on is just really define your metrics really well, because without any metrics, there’s no success. I mean, I worked on a fantastic project with a very large life sciences company until just until recently, actually. The asset reuse of that organization was getting globally, both on-pack and off-pack because of that digital asset management systems they have to, was quite phenomenal, actually. They work towards that. The cost savings was exceptional.

But actually, what was most important to them was brand equity globally. They have that metric in mind, and they started at a low base and they moved all the way through the motions over a three year period to get to where they wanted to be. And it was a phenomenal project. And it was they really thought out of the box, actually, and with AI now going further.

So, yeah, always define your metrics really well, stick to them and ensure you’ve just got really strong communication programs in place for your entire team. So they keep reinforcing the value of solutions like these digital asset management systems. So they understand, actually, this is a long game. It’s not just about this one part of the business. There’s a much bigger thing at play here that we want to deliver that will ensure that the CMO gets what they need, which is basically, you know, really strong brand equity on the balance sheet. And that’s actually the bottom line for a lot of these solutions. But that can sometimes get lost in the technology challenges that surface.

Melanie Duffy:

Yeah, that’s a good point. That touches on something that Fred said at the start of the call as well. 95% of change is change management of people, 5% technology. And that’s what makes the success of it. So thank you so much both Neil and Fred for sharing your insights. And thank you everyone for joining.

We’ll be sharing the recording of today’s session along with links to connect with our speakers on LinkedIn. You’ll also be getting free access to the latest Forested Dam landscape report that we mentioned a few times throughout this chat. So keep the conversation going. We really hope to see you in a future session and have a great rest of your day. Thank you. Bye.