DAM 2025 Forecast

CHRIS LACINAK:: 00:00

Welcome back to the DAM Right Podcast. I'm your host, Chris Lacinak, and I'm not gonna lie, it has been a minute. But the good news is there's been a lot of great and exciting things happening both at AVP and on the DAM Right Podcast.

We have an amazing lineup of content coming your way with more awesome, talented guests like the ones you've heard from in the past, but also with some new pivots towards a deep dive into DAM platforms. We'll be hearing from the leadership and the product owners and the sales folks at these organizations so that you can get to know them better and get a better understanding of the landscape.

EO there. And the topic was a: 2025

What are the things you need to know? Because looking out for what's the latest and greatest, where do we think things are going? And I think it's particularly interesting because it comes from insights from a consulting firm, an organization that works with a broad spectrum of companies focused on DAM implementation, and we see all sorts of stuff, as well as a technology provider who also works with a broad spectrum of customers.

So they bring the technology side perspective, I bring the consulting side perspective, and I think it made for a really interesting conversation that you'll enjoy. So without further ado, let's jump in.

MISTI VOGT:: 01:33

Hello. Hello and welcome to today's panel 2025 Executive Forecast on DAM Trends, Tactics and Growth Strategies for a Competitive Edge. Now, let's kick us off with a very important question and feel free to add yours in the comments. Best Super Bowl halftime show of all time, Chris.

CHRIS LACINAK:: 01:56

Well, so I'm a hip hop head and you could tell from my age that I'm someone who thinks that 90s was the golden era of hip hop. So I got to go with Dre, Snoop, 50 Cent, and it's topped off with the Queen of R&B, Mary J. Blige. So that would be my favorite.

MISTI VOGT:: 02:12

That's a pretty good one. Brian.

BRIAN MCLAUGHLIN:: 02:16

Misti, I have to go with the hometown hero here in Minneapolis and say that Prince in the rain singing Purple Rain, there was nothing. It was almost like surreal in terms of the environment and how everything came together. Almost like he could make it rain. So, yeah, I'd go with Prince, one of our favorites here in Minneapolis.

MISTI VOGT:: 02:39

I actually heard that they called Prince before that show and they said, it's gonna be raining, do you wanna cancel. And he said can you make it rain harder?

BRIAN MCLAUGHLIN:: 02:48

I love it.

MISTI VOGT:: 02:49

I love that. Personally, I have to go with Coldplay. I mean, I feel like it doesn't get much better than that. And I'm seeing some comments come in. Michael Jackson, Prince. So lots of great, great ideas and feedback. Oh yeah, Taylor Swift says rain shows are the best.

rging trends that are shaping: 2025

The challenges that organizations face when scaling DAM solutions Three key trends that are shaping the future of DAM, including integration, scalability and business impact and some real world examples of DAM that are being used. How DAM is being used in innovative ways to solve big problems.

So we'll try to answer the audience questions throughout, so please feel free to add them and any comments that you have into the Q and A panel wherever relevant.

MISTI VOGT:: 04:01

Let's get started. State of the Market. I always like to start with a poll. I'm a statistician, so polls are my favorite. And we polled our customers, customers who have made or are making the conversion to Orange Logic and a couple of key trends have emerged about their legacy environments.

1. They were struggling with their legacy systems in terms of adoption. Companies continued to use seven or more discrete content libraries, reporting only around 18% user adoption. So why is this? 88% said they chose Orange Logic as their enterprise. DAM, and low adoption was the catalyst and it was kind of fueled by three key reasons: flexibility, searchability and scalability.

feel will drive innovation in: 2025

It also stresses both the difficulty and need to gain full adoption for DAM after purchase. So we're going to do a quick poll and I already see it up on my screen so I'm sure you see it on yours. What's your biggest challenge when it comes to scaling your DAM system? Oh, got some good feedback that came back.

It looks like what's the top one? Content silos across teams is number one at 41%. Low user adoption comes in and integration with other tools at 37%, budgetary restrictions at 31%. I think we're very much aligned here.

So, Brian, I'm going to kick it over to you. With your experience leading high tech companies across industries, what do these stats reveal to you about the DAM market? Both where it stands today, the direction it's heading, and how do you see this shift aligning with broader trends in enterprise technology.

BRIAN MCLAUGHLIN:: 06:14

Yeah, thank. First of all, thanks Misti. And thanks everybody for taking the time. I know year end is always an incredibly busy time, so thanks for everybody for taking an hour out of your day.

And Chris, you're wrong. Prince was the best. I just want to let you know that to start off, not, not to have a debate here, but. So, you know, candidly, the adoption rates from the research is not completely surprising. Fragmentation leads to a complete lack of efficiency and speed which then drives low adoption.

And the good news is, I think for us as an industry is there are now modern day solutions across the industry to help solve these problems. So this is a solvable problem where it wasn't maybe 10 years ago.

One of our missions here, customer missions here at Orange Logic, is to try to drive and enable 100% adoption across the enterprise. That may seem ambitious, but we don't see why this cannot be attained.

The adoption in DAMS runs parallel with many other enterprise software deployments. The old tech hype curve that has been put forth out there by Gartner years ago is incredibly high with the purchase. So everybody's excited with the purchase. Okay, we've got a DAM, we've got a new DAM, new toys to play with.

But then it leads to this disillusionment and then once the rollout begins, the despair sets in. Okay, how do we really make sure this thing can work? So the good news is it runs its curve. It's not in every situation. But the hype curve does run. It runs through at the individual project level.

This leads to a little bit of a dichotomy as it pertains to having a consolidated DAM approach, which is typically what we hear from those who come on board with us. On one hand, it's never been so important to have a unified platform to harness the power of AI, to manage your risk you've got to have a unified data structure platform.

On the other hand, legacy systems don't allow for this due to their inflexibility and their limitations. So adoption is incredibly hard. Don't get me wrong, across all enterprise software, not Just for DAM. It's something that takes work, effort and certainly the selection of the right technology platform.

Our study, I think reflected this a little more deeply by really seeing there are three primary drivers for lack of adoption across the customers that are coming on board with Orange Logic. So the first is, and we saw this in the survey, but diverse teams have diverse needs across the enterprise, so one size does not fit all.

Secondly, silos are ingrained in their processes and their systems and their ways and they're reluctant to embrace new platform change. Right. We're human, we have pride, we select projects and platforms and that sometimes gets in the way.

And the third and last is sometimes DAM ownership could be somewhat disconnected and even bureaucratic if it's not designed properly from the start. So it's so important right from the beginning to establish the right setup.

The good news, again, all these are solvable problems. We see a very clear path to 100% adoption. We're going to push hard for that going forward and I'd encourage you and urge you, don't try to solve this problem on your own. Engage your tech partner.

You should expect, whether it's us or others out there, expect them to help you through this process and as importantly, work and play with great companies like AVP. Chris and his team do an amazing job of helping with this type of a challenge to overcome the, the adoption curve that's out there.

There are also some things that you can do to avoid this, this gap. Maybe just a couple to think about. One is cater the use cases and the system set up to distinct needs of your diverse users. So and focus on both current and, and future.

You know, I talked to one of my first customer meetings was with Meredith out at LA Phil, and Meredith said to me, she goes, you know, when we started we had this set of use cases and now two, three, four years later, we're looking at a whole different set of use applications.

And I think that's quite common across enterprise technology. Making sure that you are looking at platforms and plans to evolve over time.

I was talking to a leading electronics provider last week who was looking at making a change and they said, quote, unquote, our adoption of our current DAM is incredibly small because it was built to serve the first few teams and then it can't be changed to meet the rest. And I implore you, do not get caught in this trap. It is a trap and once you're there, it's difficult to get back out.

So once you've got this, secondly, once you get this foundation decision made then develop a staged rollout plan be realistic with your scope, involve the users from the different groups so that you get their input and their buy in, ensure that executive buy in and sponsorship so you can align it with the business strategy and the right quantification metrics and other types of things, the budget process, etc.

And lastly we talked a little bit about this, but developing a real strong DAM ownership model, blending the federated elements and the local voices and we can help you with this. I know Chris can help you with this, but really setting up a structure that helps to make sure the DAM can be an enabler as opposed to a disabler.

That's a really important best practice that we've seen across some of our best customers out there. I'm actually really excited about this challenge because with the technology and the processes that are out there, it's more solvable now than ever before.

Ten years ago we used to work around adoption and we just, we'd be happy with 30, 40%. And in the enterprise software space now we hit this problem head on because the technology's very adaptive and the humans behind it I think are empowered to be able to deploy these across the enterprises. So yeah, just some foundation based upon what we've seen out there. Great findings from the research. Thanks for those who helped us to put that together.

MISTI VOGT:: 12:47

And Brian, do you feel the reasons for changing align what you've seen across other enterprise technologies?

BRIAN MCLAUGHLIN:: 12:56

I do. You know, you mentioned flexibility, usability and scale and I think those are pretty common across enterprise software deployments. I guess when you think about flexibility or lack thereof of maybe some of the enterprise systems and those aren't bad systems, they're, they just have run their course.

I think it's important an enterprise DAM is not, I can't say it enough, one size fits all. Somebody who's telling you it's simple and here you go, you can put it in, everybody's going to use it. It's not going to work for any type of enterprise scale.

Whether you're a small enterprise, one of the largest companies in the world. Form fitting one group settings and workflows and portals and templates into others is going to lead to what we call user rebellion or use rebellion. Right. They go back to their old tools or they basically again revolt against the platform.

So I think that is, we see that quite a bit across other paradigms but certainly here in the space usability, it's continued to get marginally better. And I think AI and UX UI tools that are out there are helping but we've got to go beyond, I mean, and we'll talk more about the DAM needs to automatically or autonomously start to perform and help out the user as the onslaught of data continues here.

And last is scale. You know, we're going to see scale challenges like never before, especially with gen AI, transformative technologies, video. I mean we have customers with petabytes of data and ingesting a terabyte a day. So and that'll become the more and more the norm.

So we've got to make sure that the systems can scale up and down with the needs or you'll have a breakpoint, you'll have to make a decision, you'll have to limit your, your scope and use and then again you get back to limited adoption across the enterprise.

MISTI VOGT:: 14:56

Yeah, absolutely. And I remember when I started at Orange Logic six years ago it was, it was pretty common to see 10, 20, 30, sometimes 50 terabytes. And I remember our first petabyte archive felt shocking. And now it's more the norm, it's more that we're seeing archives in the petabyte size, multiple hundreds of terabyte size.

And Chris, I'm sure you're seeing this as well. So as someone, Chris, that's been in the DAM space for over 15 years now, why do you think legacy systems are falling short? And what's driving organizations to prioritize platforms that can scale with their content and operational demands.

CHRIS LACINAK:: 15:37

Yeah, that's a great question. First I'll say Brian, your tech hype into disillusionment scenario reminds me of my digital weight machine in my basement. So I personally touch with that trajectory.

But to your question, Misti, I think that you know, it's almost like meeting this new operation level of operations and content demands is the price of admission these days for organizations that are keeping up looking to be world class at what they do.

Doesn't matter if you're a museum, if you're an apparel company, if you're a higher ed institution, no matter what the case is, if you want to deliver world class user experiences, world class operational efficiencies, faster time to market world class education, you have to be keeping up and leveraging these new technologies that are coming to market.

And I think that in many ways answers the question in the sense that organizations are finding themselves with these new needs. Legacy systems, many legacy systems have not kept up with the rapid advancement in these tech stacks and new technologies and incorporation.

And so I think, you know, as organizations discover what their needs are and as they become the marketplaces, there's smarter DAM users out there these days. Folks have now had their starter DAM. They know what works, what doesn't work, what they like, what they don't like.

And they can articulate their requirements and use cases in ways now they couldn't five years or 10 years ago or before they first had this experience. So I think the combination of this rapid advancement of technologies and this smarter user base that understands what this technology can do for them is creating this disparity that is, that is pushing people towards, you know, a more modern DAM system that can help them achieve their vision and outcomes.

MISTI VOGT:: 17:39

Yeah, absolutely. So understanding the current trends now in the DAM market, it's essential to forecast expectations and guide proactive development, really ensuring your team is well positioned for the future.

tomer's growth strategies for: 2025

We're going to explore these trends a bit more and share how customers are leveraging them today. And then we're going to discuss some exciting possibilities as they unlock drivers of future growth.

So the first is the need for DAMS to play a leading connection role in the enterprise and Martech stack. But more so now, even the enterprise stack, not just the Martech stack, the need for DAMS to be adaptive and the need for DAMS to be autonomous.

So the first trend, DAMS playing a leading connection role in that enterprise stack. Chris, DAM and its relation to the broader ecosystem was a trend that you are super passionate about in our discussions. Can you expand on this and why you think it's important to important one to consider as folks are implementing DAM today.

CHRIS LACINAK:: 19:09

Yeah, thanks. I, I am passionate about this. So I'm going to say full permission to interrupt me because I'm going to do my best not to ramble, but wave at me if I start going on.

There are two things that I think are super fascinating on this topic when we think about the larger ecosystem and what's happening and they're interesting both individually and how they play off of each other.

So the first thing is what I refer to as hyper integration. We have seen a race in the marketplace, I think especially over the past year, it was building, but really have seen this race to integrate and to be as connected as possible to every single system and application that's in an enterprise ecosystem.

So, and we think Here you know about Google Suite or Microsoft or Dropbox or anything that you're using in your day to day basis. We've seen platforms race to create connectors to them. We've seen integration as a service companies come out that that's the sole offering they have.

And for the more tech savvy people, you know, this is like, you know, APIs is a good reference point for what a connector is. But these connectors are in many cases really sophisticated. So they're incorporating in conditional logic, they're incorporating in transformational capabilities, they're incorporating the ability to set rules around things.

So like there is, the capabilities are kind of astounding. But what we see is, the primary vision for this hyper integration is that all of a sudden there's this seamless utopian user experience where a user does not have to be burdened by logging into the DAM to go and find and use assets.

Right? They can be in whatever application they're in and they can create, deposit, search, retrieve, use assets from the DAM without ever having to log into a DAM. Now that's awesome. It's a really beautiful vision.

I will say that I think there's some major concerns about that like governance being a big one. I think there's a big opportunity with this kind of vision to create some real messes both with media and metadata, all sorts of things.

So I think that we will see some of the things we're going to talk about today we see like maybe lessening the amount of human input into systems. This is an area where I think we're going to see an increase in need for folks that are experts, DAM managers, archivists, to create, enforce and leverage governance.

And some of the sophisticated tools and connectors give us some handholds to be able to do that. So I think part of this is going to be, there's going to be some pain, people are going to come to understand it better, they're going to use those tools better.

But there's undoubtedly a human element. So this hyper integration kind of flattens everything out horizontally, right? It gets rid of all these walls. The other thing that is happening at the same time is this vertical narrowing that I call portals.

So portals are, I define as a highly specialized user experience for a specific target audience. And the impact of portals is there's usually more than one. It's for a specific user sitting on top of the same DAM.

So you're giving this really sophisticated user experience to a particular user. You can think about like sports events as a common use case here, where you've got a portal for the press. It's a public facing thing that the press can use and it allows them to log in and find and use vetted and authorized content for publication.

You've got, on the other side of that coin, you've got a portal for videographers and photographers and content creators that are creating and putting content in. You've got a portal maybe for editors that are, that are editing the content for authorizers and approvers.

Or you can think about brand portals, companies that have multiple brands, portals per brand. And we're even starting to talk about this like in the higher ed space, like a portal for researchers, a portal per collection, a portal for alumni, for faculty and staff, right?

And the portal says what can they see or not see? So they don't have to be burdened by things that they don't need to see. What's the exact user interface and user experience that they need? What's the metadata and the media they need to see, what permissions do they have.

So it's really crafted just for them. So I think this is just fascinating because when you put these together, it creates this mesh and we talk about adaptive DAM, we're going to get there. But like that makes it adaptive to so many different use cases that it, it just, it really creates, I think, new capabilities that are really exciting.

So I'll stop there.

MISTI VOGT:: 23:43

Thanks. Yeah, absolutely. I think the integration story is a, is a big one right now and we're seeing new channels emerge, new downstream channels with the opportunity to take the structure of DAM, the governance that has been in DAM for quite some time and now feed that back into the organization, whether it's part of the AI stack or the broader stack, to continue to evolve the business in a really strategic way.

So I think you pretty much hit the nail on the head there. So Brian, how do you see other leading companies in this space helping this transition from a standalone to a more interconnected, broader ecosystem DAM.

BRIAN MCLAUGHLIN:: 24:26

Yeah, Misti. So I think this call is full of DAM enthusiasts, DAM junkies if you will. Those that, that either work in the world of DAM or, or appreciate the value for what it do.

So I think the good news is, is that DAM serving a leadership role in the Martech stack and the broader enterprise stack is, is, is moved to critical. And that's exciting. It's a big responsibility, but it's exciting.

And we listened a lot to the survey, but also just what we're seeing in terms of patterns and trends out there. So why is this? I think there's really kind of three core reasons for it.

The first is around the need for a single source of truth with content. Right? 93% of marketers said a single source of truth provides substantial benefits to organization. If you don't have structured, consistent and clean data and structure around your content, you're gonna lose advantage versus the competitors that are out there.

Leading companies are gonna leverage this to drive their AI models and obviously their analytic tools and their campaigns. Those that don't, aren't, and they're gonna fall behind because there's so much power around having this single source of truth.

If you've got 12 different DAMS and 15 different data sources and the data's inconsistently structured and not clean across the sources, you're not going to be able to harness the power of the very near future.

The second is marketers and other users are drowning in content, right? Much of this content unfortunately goes to waste because it's impossible to find. Forrester came out with a study in a stat which I absolutely love.

I don't love the outcome of it, but I love the fact that it clarified, I think for us what we see is a real problem is 65% of content is unfindable or unusable. Think about that.

That renders 65% of your DAM to be unfindable or unusable if it's not structured the right way. So we're seeing the introduction of new tools like natural language, search and other types of capabilities we've been implementing those others have.

There's some new things that are really going to help I enable this. But you know, there's a long way to go. And just one use case that we've heard from our customers is when customers said, you mean I can take a 60 minute video and look for a logo on a shirt and get the frames back that have that logo and a shirt back in milliseconds? That, that seems impossible.

And we showed them just with, with our capabilities and again, others have some wonderful capability as well. But that, that, that impossible has become possible through, through the, the importance of the technology that's out there.

Lastly, we're all facing it, but this whole notion of content authenticity and control, right, it's more relevant and more important than ever before. But brands and content are being distorted, misused, faked at levels like we've never seen.

And having this consolidated source of truth as well as the right digital rights protection tools will be paramount, I think just to the protection of your brand going forward.

So equally to the I think the DAM itself being central to the stack is the need for the DAM to play well in the broader ecosystem. And I know just speaking on behalf of Orange Logic, we've invested massively in the last 24 months and in particular in this area.

You know, DAM providers will have to increase these capabilities across the board and I think it's paramount that when you're making selections or looking out there determining what is an ecosystem friendly tool and company, I mean there's no magic badge or certification that says hey, you're friendly to the ecosystem.

I think you need to ask questions. And the questions I'd ask if I were in your shoes or you know, have they developed an API first architecture? Many have and that's the good news. I think a lot of the modern systems have. Do they have pre established connectors and partners that complement the DAM and are these offered in a user friendly and self configuring manner? This is an area where we've really spent a lot of our energy in the last even six to nine months here.

Do they have a development portal that allows for the IT teams to get in and begin to run test scripts and test capabilities for the integrations and connectors? Do they have partner friendly pricing? And then I guess lastly, does the company that you're working with offer a solutions design engineering group that can help you kind of design the solution and then and or partners that they've partnered with like like AVP and others that have that help that can help to kind of put these pieces together.

I think these are the thing the questions that I would ask and these will help to ensure that the system that you're using or purchasing is really truly ecosystem friendly. Because without it you will not get anywhere near 100% adoption going forward.

CHRIS LACINAK:: 29:34

Yeah, I'd love to just second real quick, the content authenticity conversation is such an important one. Misti, you and I talked about that at Henry Stewart DAM New York and you are exactly right to put that in the ecosystem conversation.

Brian, I'm really bullish on this as a really critical topic. I think it's not getting enough attention mentioning the DAM space right now. Orange Logic has done a great job of really supporting that, but maybe we can touch on that later. But just to second the importance of that particular conversation.

MISTI VOGT:: 30:00

I really think that could be and probably should be its own webinar on just content authenticity. I spent some time with some of your team members, Kara actually, joined me at DMLA a couple months ago now and we spoke exhaustively about content authenticity.

And I think one really cool takeaway from that was what does it mean to be authentic? You know, is it only if it's straight off the camera, raw footage is it authentic? And we landed on a, a definition that I really appreciate and that is authenticity can only be defined to the context of which that content needs to be delivered and the story that it's trying to tell.

So if you are Save the Children or the U.N. for example, authenticity is your brand. You can't be mingling elements of AI into that content and putting it to market. It's really, it could be really damaging. It would be really damaging to the brand.

On the flip side, if you're a retail company and you are developing a personalized experience for your users and you're swapping out the background, I mean, that's a completely different story. It doesn't mean that that product is inauthentic or that content is inauthentic.

So, a whole other conversation, I'm also seeing some buzzing in the chat around sustainability, which I think could also be its own topic. So, but just to address that really quickly, I'm curious to hear what your thoughts are sustainability and then we'll jump into the adaptive DAM. So Brian, curious to hear what your thoughts are on sustainability. It is a hot topic. It's coming up quite often now in RFPs.

BRIAN MCLAUGHLIN:: 31:41

Yeah. So good question, Misti. And the, to the chat, the chatters out there. I mean, you know, at Orange Logic, we're, we're publishing here, it should come out here in the next couple weeks.

Our sustainability position for our own sustainability position and pledges to future sustainability, but also what we can offer to our customers. I mean, I think we have the obligation to be a sustainable business and continuously improve and drive sustainable capabilities, whether it's energy consumption or others across the board.

And then as importantly, if not more so, offering capabilities that are the most sustainable as possible. And I guess, let me just bring up AI. AI flies in the face in many cases of sustainability, right? Because AI is going to consume massive amounts of power, massive amounts of water, massive amounts of, of capability that you could argue are not the most sustainable.

So how do we work with our customers to implement the right, the most efficient, the most sustainable AI models that are out there? How do we work with our customers to make sure that from a storage perspective, that we're using the right balance of cold storage and other storage, smart storage, intelligent storage capabilities? These are things we take very seriously in our pledge to offering to our customers a sustainable DAM and you'll be, we'll be seeing more on this, but we take it very seriously and we've signed up for specific targets in line with the Paris Accord.

Then you know, from a, from a business standpoint, again those will be published and next step is to make sure that we can help you all with your pledges, which are in many cases are very vast and very, very impressive. Our job is to help you support those.

MISTI VOGT:: 33:37

All about the community. Right, Chris, what are your thoughts on.

CHRIS LACINAK:: 33:42

Thanks, Misti. So I think we need to look at this in a couple ways. One is, and I think this actually bleeds into the adaptive DAM conversation. One is like we see organizations asking the question how can we create more sustainable processes, workflows utilizing DAM? So here we think like we've had the good fortune of working with an amazing apparel company that has sustainability goals and one of the things they're doing is using DAM in their 3D production process.

So they're moving to a virtual 3D product creation process that gets rid of this physical prototyping, shipping things, physical goods all over the world, is a much more, for other reasons, not just that, but in many ways it's much more, it allows for faster time to market, it's better bottom line, those are nice things that go along with the sustainability impact of that.

So that's like one, organizations can look at their workflows and say how can we create more sustainable workflows by using DAM? The other facet is what is our digital footprint as an organization and how are we doing that? So working with like critically examining and evaluating DAMS and their sustainability pledges like you're talking about is one aspect of that.

But Brian, you mentioned AI and I up until several weeks ago thought, you know, I've read in the Times we're opening nuclear plants for, to support AI and things like that. My colleague Kara Van Malssen was, was just doing some research and some work around sustainability and DAM and, and did some analysis and actually, and this is not to say either or I'll, I'll, I'll get to a concluding statement here.

But, but video is by far and away the worst culprit when it comes to sustainability as far as CO2 emissions and water utilization and stuff. Because one, just because of the size, the bandwidth utilizations, how many people globally are using it.

But for organizations, how much video they're creating, if you just look at a given organization and the operations in the course of a year of what they would do, AI is a almost negligible part of the CO2 emissions compared to video transcoding, video storage, video streaming.

And the goal here is not to say this is good or this is bad, it's just to, I think organizations, what can they do? They can use cold storage more conservatively instead of hot storage. That has a big impact. You know, maybe we don't need to create proxies for everything.

Can you do it on demand? Can you do it in a prioritized way? So I think that organizations can start to more critically examine their digital footprint to also themselves in the utilization of a DAM in and of itself create more sustainable practices.

MISTI VOGT:: 37:17

Onto the adaptive DAM, which definitely intersects with the other topics that we've talked about. The second trend we studied was the need for DAM to be adaptive. And we're seeing this, we're seeing bits and pieces of this with the intelligent DAM.

So in essence to form fit its environment, use case. Chris, you brought this up with portals. And so Brian, how, how do you see OL, Orange Logic, evolving our platform to meet the needs for this adaptation?

BRIAN MCLAUGHLIN:: 37:44

So I think the adaptive DAM concept as a trend is really founded in one key premise and that is the DAM should adapt to the user, not the other way around. So DAM users unite, right? Stand up, right? It's time that the DAM actually adapted to the use case, not the other way around.

And I think that's a big, big disabler for adoption is that DAMS haven't adopted to the user. So we're kind of entering this. We're, I think we're in this third generation of DAMSas we look at it, right. Gen 1 was DAM serving as a library.

Gen 2 more connected DAM, right. It started to interface with other subsystems and other pieces of the business and workflows.

Gen 3, which is kind of our current state, there's a lot of talk about intelligent DAMS and so I think that's where we are right now is most of the leading companies are offering some form of an intelligent DAM which has added the secret sauce of AI to enhance the capability.

So I think while these are interesting and I think through the pointed use of AI, they're they're moving the ball forward, they don't holistically address the core issues of speed, scale and adoption like we've talked about. We see the next step for, for DAMS and this is really the key trends I think we're going to see come loud and clear in '25 is this age of adaptation and autonomy.

And we'll talk about both of these, Chris and I will as we, as we kind of go through the journey here with Misti. But this is, you know, it's at the heart of what we see as the next big trend.

So starting with adaptation, right. An adaptive DAM really offers unmatched flexibility with you know, tailored views and tailored data structures and features that are unique to each team in terms of how they work.

Basically teams can construct the DAM to look, feel and function from a rule set, metadata, taxonomy, connectors, how they, what applications they use to their specific use case.

So what does it mean in practice? How do we take all that and say okay, what does this mean in practice? It means that you can now create these experiences if you're a distinct group that are very tailored to your business needs and to your strategies and objectives.

But back to that executive alignment, you don't, it's not one size fits all. You don't have to follow the pattern over here because it's the lowest common denominator or that they were the first in. The first in shouldn't set the rules for everybody else downstream.

It means unmatched agility going forward. It means hyper personalized experiences from again those workflows to templates to portals like Chris is talking about. It means those pre established connectors and that you can build in app within a marketplace within the DAM that can configure themselves going forward.

And it means that you can also begin to bring your own tools in particular AI that there are hundreds of gen AI tools and models out there. We often get asked which one should I use? Well, we've got our recommendations based upon the use case.

But more importantly, a DAM should be able to allow you to bring your own AI types of tools that meet your sustainability goals or your use case goals or whatever. The DAM shouldn't limit your creativity and your ability to leverage modern technology.

So I, I just can't stress enough the, the dam will adapt to the users in this modern age. This next phase of dams, which is really exciting, not, not the other way around.

MISTI VOGT:: 41:26

Yeah, Chris do you have anything to add to that.

CHRIS LACINAK:: 41:28

Well, I'll, I'll go quickly here. I'm just looking. We have so many great questions, so I don't want to take up too much time. I'll say. I, I think my comments earlier kind of spoke to that and Brian did a great job of, of, of laying that out.

I just, you know, I gave maybe just a couple of examples because this can feel a little bit lofty, maybe in abstract. So like, you know, I gave the digital product creation example that's, you know, we're no longer looking at dam being solely in the martech stack, right. Like it's now moving into other parts of the enterprise doing really highly specialized things.

So that's one example like digital product creation I think is a really interesting example of what adaptive DAM looks like. Another one I would give is digital preservation. We see this, I think for years, you know, organizations have been essentially, if they're, if their resource, if they have enough resources, they've been getting two systems, a digital preservation solution system and a DAM.

And we're seeing that change. We're seeing organizations start to adopt, because the sophistication level of DAMS has increased to really be able to support digital preservation use cases and requirements, we're now seeing organizations select a single system. That has a lot of implications because these are not systems, these are operations, right. Both of these things require programs and operations and staff and workflows and all these things.

So to reduce down to one system has huge positive implications for these organizations. So we see just as another example like adaptive DAM, that's another place where DAM historically was not, DAM was kind of a bad word in digital archives and preservation for many years.

There's a history there and now that's becoming less and less true all the time. So I just think that's another interesting example of what does adaptive DAM look like. It starts to play these other roles and organizations in interesting ways.

MISTI VOGT:: 43:05

Yeah, absolutely. And we actually got a great audience question from Juan Montez that tees us right up to autonomy. So Brian, I'm going to throw this one over to you direct from Juan. How are you thinking about workflows and the adaptive autonomous DAM? Because adaptive sounds great, but it does also sound like a lot of work.

BRIAN MCLAUGHLIN:: 43:29

Yeah, so I think in an autonomous DAM, you know, and we'll talk more about that in just a second, workflows become almost self creating based upon the conditions and the data and the need set.

The user can key in a set of parameters and needs. The workflow almost creates itself based upon that basic input, based upon the history and the learning and training that it's done from some of the different permutations that are out there.

Secondly, it's self curing. If there's any type of failure point in the workflow or breakdown the workflow, it'll provide a self curing mechanism.

I think last, the workflows will become much more intelligent. They'll have AI embedded within the workflow to be able to drive very adaptive decisioning.

So it's not just going to be a decision tree workflow, you know, A or B or C, you know, the classic decision tree format and flow. It basically you're going, the workflow itself is going to be able to learn from past responses and begin to predict where it needs to go and head and it'll actually start to drive those decisions.

All under the purview of a very astute DAM manager, DAM administrator. But I think it'll start to do more and more of that work to cure, to solve and even create additional workflows or augmentations of workflows.

So really good question. Some of you are probably thinking, well, what the heck is an autonomous DAM? I think it's a newer concept as I mentioned. Right now we're in this third phase of intelligent DAMS which have AI as a tool. It's a tool in the toolbox. It's not the answer, right.

Recent studies on AI, Gen AI in particular, 28% of organizations have adopted Gen AI technology. But in nearly all the use cases they've failed to meet the business objective because of specific departments or projects are very constrained from the other benefits that may be out there.

So I think we as an industry need to take this to the next level. So an autonomous DAM takes AI and automation to that whole next level. It creates a DAM that's self managing, that's continuously learning to handle the complexity and the scale of the operation and allows the users to focus on creativity and strategy.

It doesn't replace the user for the DAM. It actually enhances how they interact with the DAM. That's an important, really important part is that I think that the smarter the DAM becomes the, the better the interaction they're going to get for admins and users and others.

But this, this, the DAM learns and trains and it does so using, you know, large language models and predictive intelligence and other capabilities that are built within that are out there today, but are, are, you know, ultimately our, our goal with an autonomous DAM is to enhance that human engagement with the DAM and it really feeds into this 100% adoption across the enterprise.

So what are the elements of an autonomous DAM? What do you need to be looking for? Well, first and foremost at the core it's got, it has the ability to learn and train from the data structures and it deploys deep large language model based decisioning at the core.

Second of all it self manages from the auto tagging process to predictive search to campaign recommendations to others. And third, it auto scales up and down based upon the use case, based upon the need again back to sustainability. It can auto scale across different types of environments as you go forward. You don't have to be as concerned about that.

You know, ultimately those core capabilities will lead to a whole new form of usability, right. You could do things like something we're calling Persona DNA mapping. So each of the users or admins that interact will have their own unique DNA. Here's how they interact with that DAM.

The DAM is going to learn how that use happens and begin to set up configurations and tools and outputs based upon that DNA. There'll also be self auditing mechanisms for whether it's again the workflows I talked about or for brand authenticity and compliance.

We can start to look at the metadata and the content structures and we can also create kind of an AI auditor tool that looks at the compliance mechanism. So just a couple of examples.

I mean we project very near term here that at least 25% of the human interaction with a DAM can be conducted by an autonomous DAM, which ultimately enhances that, that, that experience and the interaction point with, with the DAM going forward.

So a lot, a lot there could have our own, I think our own webinar just on that. We're excited to you know, be involved in that effort going forward. And again I think it'll become very much an industry capability in the not too distant future.

MISTI VOGT:: 48:47

Chris, what are your thoughts on that?

CHRIS LACINAK:: 48:49

Yeah, so, well, I'll offer a couple. Brian did a great job laying that out. Let me offer a couple of Kind of practical examples to help people anchor this to like their day to day. What's this look like? So the, the biggest workflow thing we see being addressed is this historic problem that has plagued many organizations for years, which is a broken self service model.

Now it can be broken for a number of reasons, but the experience is user after user logs into the DAM, does a search, quickly becomes frustrated and then picks up the phone, sends them chat message, texts, whatever the DAM manager or the archivist and says can you find this thing for me? Now that's bad because there's a bottleneck on an individual.

It's also bad because then those people go and talk to their colleagues and they say that DAM doesn't really work that well. I can't find the things I'm looking for. So it has created a big problem over the years like the self service model, how well it functions.

So what we've seen is DAM platforms again kind of racing to create the ultimate self service experience. So here we put to use those large language models that Brian was talking about. Let's call it into an AI agent that sits and either replaces or supplements the traditional search box.

And what's it doing? Well it's looking at, Brian talked about DNA, personal DNA. It's using your search history, what have you searched for, what are the things? It gives it context to know how it can better help you find the types of things that you're typically looking for faster.

It's also searching the metadata that's in your metadata model and taxonomy that you have created. But it, it can also in cases be leveraging metadata that's generated typically by AI tools that might not be part of your formal metadata model that give a more natural language search capability.

So, so that again it can help people find things faster. So this, I don't think we're quite there yet, but we're, we're well on our way. It's going to happen very soon where there will be this self service experience that will address that historic problem that I think is, I think it's game changing actually.

I think it's kind of, it feels kind of small but I think it's, it's a really big deal. So I think you think that that's, that's an, that's an example of autonomous. Then you've got like think of all the, and that's pretty complex.

I mean and then think of the hundreds or thousands of decisions that administrators kind of going to the back end here, administrators and managers make on a daily basis and AI's ability to do those things.

And I've got a quick aside this is so interesting. Like George Church might be the name that folks know. He did a lot of work around data storage in DNA, but he's also working on this de extinction project.

And I heard a podcast with his colleague Ben Lamb. They're bringing back the woolly mammoth and the saber toothed tiger. They want to rewild them, but they talked about they have this immense challenge of editing DNA. You've got a suite of tools, you've got a suite of types of edits you have to make.

And if you make the wrong edit, you use the wrong tool to make the edit, you lose weeks or months of work. So they have an AI agent that looks at the scenario that they have the edit they have to make, it looks at the tool suite and it has been able to produce selections that are way more likely to succeed than when humans were doing it.

So that's like a small example and that's really complicated. Think about all the mundane stuff that AI could be doing, either to expedite the process, in that case, that the human's still doing the work, but the AI tool is giving them information.

So to either expedite or replace some more mundane types of things. So those are some examples I'll throw out.

MISTI VOGT:: 52:25

Yeah, absolutely. And I think it's also not an overnight thing. And that's okay. It's not a panic. Rush, my DAM should be autonomous tomorrow. It takes time.

Like you look at autonomous cars, everybody kind of associates the two because that's what we're seeing really emerging. The really important thing is that you're setting up this framework and this governance structure to start training and giving the DAM bits and pieces to Brian's point, 25%.

It's totally reasonable. Give it little bits and pieces with supervision and adaptation ability and training. But build that in today so in the future we can expand, expand that percentage. And I, it's, it's already happening. It's happening today.

CHRIS LACINAK:: 53:08

Well, and it's going to just, I mean it's happening in our day to day lives. Every platform we use is starting to go this route. So at some point, I don't, I don't, I think you could look back in 10 years and go like, oh, we thought that was a thing then, right? Like it's just an everyday part of the systems we use.

MISTI VOGT:: 53:24

Yeah, absolutely. I'm going to take one quick audience question and then we'll kind of do a quick round out and wrap up because I can't believe how fast the time has gone. Already 8:54. David sent over a question. Do you see any trend developing for DAM systems to offer support to maintain the chain of provenance with images that contain C2PA metadata to help in verifying images that have not been tampered with of interest to news organizations and others that are concerned about image truth.

CHRIS LACINAK:: 53:57

Well, I'll say a quick thing is just to say I think that Orange Logic is leading the way on this particular front. So I think, I mean I'd love to hand it over to Misti or Brian to talk about what you all are doing. I think it's really

BRIAN MCLAUGHLIN:: 54:08

Misti, you could jump in here because I know you have a passion for this but yeah, absolutely. I mean I think our vision is to be able to inform our users on the way in if content has been altered by or impacted by Gen AI in particular.

And throughout the course of within the DAM, the transformation process, we're going to track iterations and show you using graphical tools where and how it's been iterated throughout the course in the DAM.

And then as it leaves the DAM, be able to track across different distribution channels how that particular content piece or you know, brand pieces has actually been altered and then report back to you. Hey, you may want to take a look at this because this has been altered in this way.

And Misti, you may want to chime in because I know you've got a real passion for this as well.

MISTI VOGT:: 55:01

I'm biting my tongue as a moderator. It's my job to give you guys. But yes, I'm happy to address this really quick. One, we fully support C2PA today. We extract it just like any other metadata. It's built on top of IPTC fortunately.

And there's the entire Content Authenticity Initiative that have put forth this really awesome community and governance structure for us to follow. The problem with it is it's not a hundred percent, it's not a fail safe. C2PA metadata can be stripped out.

There are some really popular platforms that just strip out C2PA metadata as soon as you, you upload it into that platform. So that's one problem. The other thing is some AI platforms are popping up, up like daisies every other day.

So if they don't have C2PA also built into that creation process, you're going to lose that entire story. So C2PA is very important. We're seeing some news agencies and other organizations that are drawing the line and saying if a content, if content arrives to the DAM and it doesn't have C2PA, it's assumed to be fake.

That is definitely the extreme, but I can respect that, especially in terms of news agencies where authenticity is 100% of their brand. I think a really important thing that we're looking at now is what else should accompany C2PA in order to show that provenance and ability to authenticate an asset and show the story and the journey of that asset? So we're looking at forensic watermarking as one thing that can also have C2PA and metadata and invisible watermarking and then also some blockchain technology.

I know blockchain technology. I'm sure everybody has a strong opinion. It's gone back and forth. But I do think NFTs was kind of a cool phase. But the really cool thing about it is it's a really strong bond to show that authenticity and ownership and provenance of an asset.

So I, I see some emergence of some blockchain technologies and the combination of these three things really give you a full picture of that asset in the journey.

CHRIS LACINAK:: 57:18

Yeah. And the question asker David Riecks is a real expert in the field of embedded metadata, so he knows the ecosystem woes for sure.

MISTI VOGT:: 57:26

Thank you, David. We could talk about that.

BRIAN MCLAUGHLIN:: 57:27

Thank you.

MISTI VOGT:: 57:28

All right, actionable takeaways. So, what's one piece of advice you'd give organizations looking to push boundaries with their DAM and start using it innovative ways that align with the future trends?

BRIAN MCLAUGHLIN:: 57:42

Chris, Chris, go ahead and fire away.

CHRIS LACINAK:: 57:44

Sure. Well, I'll do. I'll make it quick. I would point you to a resource that my colleague Kara Van Malssen created called the DAM Strategy Canvas. It's a really, it's a one page canvas and it's got a guide on how to use it.

But you know, in the same way that a business doesn't just create a strategy when they form, they do like at least annual strategy and planning. This is a great tool and guide to walk you through basically how you can be adapting and innovating on an ongoing basis.

So I would say you can download that at our website. The DAM Strategy Canvas and Guide. I would point people to that and say use it. I think it'll be a really valuable tool for doing that.

BRIAN MCLAUGHLIN:: 58:18

Yeah, my thought is very similar. It's really create a product vision for your DAM. Where do you want to be and what are the objectives? How do these align with your company strategies? What's the scope, plan to get there and look at it in terms of iterations, look across the groups on an annual basis, look at this plan, see how you're doing compared to that original vision doc to make sure that you're aligned.

I would encourage aiming for 100% adoption across the applicable groups. And stress tests, two to three of those future proof use cases. Think of where do we want to be a year from now? Here are two or three use cases.

Can we get there with this deployment? And you know, as part of that, I would encourage you to challenge your partner, your technology partner. Tell them to give you a roadmap review.

If they're not willing or they don't, they're not showing you alignment on a roadmap, then maybe you're not with the right partner because they should be able to provide you with visibility to where they're heading and then ensuring alignment with, with your goals. That's a really key part of, I think, the, the, the partner alignment side of things.

MISTI VOGT:: 59:30

Absolutely. And thank you guys so much. That brings us to the top of the hour. I can't believe it already. This was great. I feel like we definitely could have gone for probably a full day.

So please feel free to send us any follow up. Thank you so much. Lots of participation. Chris, thank you. Thank you. Brian, thank you. Really appreciate it. And to all the participants, much appreciated.

CHRIS LACINAK:: 59:50

Thanks everybody. Thank you.

BRIAN MCLAUGHLIN:: 59:51

Thanks everybody. Thanks, Misti.