[Music] [Jonathan Whiteside] Thank you all for coming.
First of all, before we get started, I just want to introduce who we are. So my name is Jonathan. I'm Global SVP of Technology of an agency called DEPT®. And I'm joined by Joshua. [Joshua Young] Yes, hello, I'm Joshua Young. I'm with Adobe. I am the Head of the Solution Sales Team in EMEA that focuses on Content and Workfront. I have to say, by the way, I was thinking when we were sitting. Yeah. Like in a movie theater, everybody wants to sit in the middle, but here it seems to be like the complete opposite. Nobody's in the middle. It's just parted ways, like, you're in the middle, but everybody out there. So I'm excited to be here. I live in Denmark in Copenhagen and I support the EMEA business with everything content and Workfront, content supply chain. And I'm very excited to talk about assets here and very pleased that the team at DEPT® invited me to join them today. So thank you. Thank you much for joining. Some of you may have heard of DEPT®, some of you might be less familiar with us. So I just want to very quickly introduce us as a company as well. So DEPT® is a global digital agency who have been built with a unique 50/50 combination of technology and marketing skills. With about 4,000 people across Europe, Americas and APAC, we unlock tomorrow's possibilities for today's most ambitious companies. And we're a platinum Adobe partner and we've been working in Adobe ecosystem for many, many years.
Now because of that 50/50 split between tech and marketing, we've always been very focused on ways to improve marketing performance by using technology. And as the demand for creative assets over the past few years has grown because of personalization because of the increase in different channels, whether that be CRM, on-site, paid media, we've had to come up with a way to find a cost-efficient method for creating lots and lots of content to feed all of those uses of content.
So about five years ago, we decided to set up a dedicated team called the Creative Automation Team. And they were very focused on developing processes, some tools, ways of working about how we could really scale the content production process and solve the assets at scale challenge.
And it worked pretty well. And in the past five years, we've created well over a million assets for brands such as Spotify, Just Eat Takeaway, Zoopla, Smart and many, many more.
And through all of these experiences of creating these million assets, we've learned what works well, what doesn't work well, and really how to make the most impact in doing creative automation.
And as I say, the good news is it really does work.
And what I really want to do over the next 45 minutes is to share with you five lessons that we've learned over doing this to make sure those of you who are just starting your journey in creative automation or looking to scale up your creative automation can do it without making some of the same mistakes that we have made.
Okay, before I get started with the lessons, I think it's really important that we just make sure we're on the same page about what creative automation is. Because when we do demos for clients of creative automation, they go, "Wow, that's magic." And while I would really like to go home to my children and say, "I did magic on stage in Las Vegas." Unfortunately, it isn't magic. So I'm just going to peel back the curtain a little bit and explain what it is. And it's actually two very simple concepts sprinkled with some technology on top. And the first concept is a template, whether it be a static template or a motion template. And the template sets the layout of the asset that we're creating. And in that template there are a number of placeholders. Placeholders for text, for images, for video. And we can also set a number of variables, things like different fonts, different colors, and anything else that we want to be able to vary within the creative assets. So that's the first part, the template. The second part are the data feeds. And the data feeds are where we feed all of the different content, the different variations of content. So in this example, we've got a different food image, a space for the placeholder for Copy 1, a space for placeholder for Copy 2. And we can create as many different variations of different types of content to fill those placeholders as we want. As I say, they can be images, they can be text, they can be video, whatever.
And then the creative automation part is the technology which basically takes all of those different variables, it creates all of the different combinations of all of those different variables together and then it passes it to the template and it renders every single variant. So every single row in that spreadsheet, it will create an individual asset with that unique combination of all of those different pieces of text. And it scales really, really quickly. So if we just have three different columns with 10 different variables, we've got 1,000 assets at the end. So abracadabra, that's the magic.
Yeah, I like analogies as well, but I like rockstar analogies, right? So how many people here have dreamed of being a rockstar at some point in their lives? Come on. Be honest, rockstars, right? I haven't given up on this dream. I still believe one day I'll be on the streets of Copenhagen when I'm old and retired playing Bruce Springsteen songs with my American accent, and I get a niche market in there. But we want you guys to be rockstars. And I think what's interesting, so I'm going to, by the way, sprinkle in a little bit of Adobe's perspective as we go through these five points that Jonathan's going to review. But high level, I want to talk about constant supply chain because I think there's an interesting parallel between rockstars because rockstars need to be an actual rockstar, needs to be very creative. Obviously, they're creating something from nothing. They need to be collaborative. There's a whole team of people that support creating music and touring and all of the stuff behind being a rockstar. They need to be able to protect the assets that they create because that music has value to them, and that's what their business is built on, right? And they need to be able to get insights to know how to improve their story, and they need to be consistent. And my favorite rockstar, I guess, would be maybe Bruce Springsteen, who's been consistent all of these years. And a big difference, though, with a rockstar on Bruce Springsteen's case, I'm a big fan of Born to Run. Do people like the song Born to Run? Yeah. It's best. It's my favorite song. And I probably heard it about 2,000 times, let's say. Only two of those times were live. And the other times were the same recording that he created many years ago. So he doesn't have the ability to tweak and optimize and make it better outside of on tour. But you as marketers have the ability to learn and improve and actually make changes and optimize what you create. So this is what the content supply chain looks like in our world and how we connect all of these pieces together. If you can skip to the next slide. There we go. We didn't work through visual-- - We should have been a-- - Yeah. - We should like-- - A keyword. I'm a baseball fan too. I should have had some baseball signals to alert me to switch the slides. This is how we look at content supply chain. There's a lot of similar things to being a rockstar, and this is how we can help you be a rockstar, right? We want our customers to understand how to collaborate as a team and plan to make sure the entire ecosystem is working together in order to deliver and create and deliver the content end-to-end. And that's what's very interesting around assets, which is why we're going to talk about this around assets because the creative and production piece, I mean, Adobe is the industry leader in creative tools, and it's all about creating assets. And then being able to store them and protect those assets and treat them with value because they're important to your business, being able to deliver that to customers and then gain insights in order to optimize and improve. So this is what we're building and the vision that we have in order to help our customers go from an idea of an asset all the way through producing and creating it and delivering it and understanding how it performs. And this is a growing part of our business, so I'm sure you've heard a lot about this already. It's my favorite topic. And through this presentation, I'm going to jump in and talk more about little pieces of this and how it relates to the lessons that Jonathan's going to walk through.
- Thank you very much. - There you go. Okay.
I'm going to start with lesson one. And this is perhaps the biggest trap of all that we're going to see.
And that's confusing volume with value.
Because it's really, really exciting once you get this technology in your hand. Because you realize you can suddenly create thousands and thousands of assets in minutes at a relatively low cost and you can get very easily carried away. The temptation is to push as many variations, as much content through this technology as possible and assume really that more means better.
And the key lesson is just because you can doesn't mean that you should.
Because more assets doesn't necessarily mean better results. And as we started to generate a high volume of assets we quickly realized something very, very important that we just weren't getting the impact that we thought we're going to do just by creating more and more and more.
Sometimes it meant that we were just creating more noise and we were competing for attention and not necessarily making the impact that we wanted to.
A good example of this is some work that we did for Polaroid. Polaroid always run a campaign towards the end of the year between Thanksgiving and Christmas. It's really the key peak period where they're doing a lot of their sales and a lot of their revenue. And they needed quite a lot of assets for all of the different channels that they were looking to promote their products on for that key sales period.
And with such a wide range of products available, there was a temptation of, okay, we'll just put all of the product images in, all of the benefits and features and we'll just create all of these assets and put them out there. But that's not really what we did. Instead, we started with a very, very clear strategy of actually what a testing framework would be. So starting with a testing framework. What are the key parameters? What are the key areas of the asset which we think would actually make an impact on sales and click-through rates? And this could be messaging, what resonated best, what the creative elements like the color, the photos, the typography, the calls to action, an obvious one, what works, what doesn't work, and different visual styles. The different visual styles work better across different platforms. And we created a really small number of assets to quickly test and validate which ones actually worked and which ones didn't.
And then we used that data. Once we knew what elements were having the biggest impact, that's when we started to create variations based on those key things.
So to do that, we use some AI to look at all of the different test images we put out there. Was there some correlation on over 1,000 assets kind of the key things which were making the click-through rate go? Is it a red background? Is it a green background? Is it the text? Is it the image? And then as I say, that's when we did the scaling. And what did it mean? It meant, actually, we created fewer assets but much better performance. We focused the budget in creating proven winners because we knew with a degree of certainty that actually those are the ones which will scale better.
We had the prediction on the creative effectiveness to improve the ROI. And really crucially, we weren't relying on media spend to fix bad creative. We weren't just throwing budget at media say just push it out everywhere and see what works. We were very, very targeted and strategic with which creative would work on which channel.
So just because automation enables you to produce a million assets, as I say, it doesn't mean that you should. Start small, test, learn, and then scale. Because testing isn't about making more, it's just making smarter.
And I really like the thinking about how value exists within assets you create and making sure you use them in the best way possible. So I like to think of the fact that your assets that you create or pay a lot of money to have created that carry your brand identity, well, they're actually assets as well. So your assets are assets. I like the little spin on the word there. See what I did there? Yeah. So when you look at it, you think about, like I said, you're spending a whole lot of money on assets, going through brand guidelines and all kinds of brand work and creating very important hero assets that get used and are meant to be used. There's a ton of value in that. And they're assets, and that's actual value. They should be considered valuable, and you should treat them as if they're valuable because the money that you invest in creating your assets create value for your company, and you need to make sure you utilize them well and treat them as value and make sure that you don't waste. There shouldn't be any waste in the assets you should create. You should reuse as much as you possibly can and optimize what you've used, and you should allow for quick iterations. And that's what GenAI and automation is what's there to help you do, right? Make the most out of what you've created. Take those assets as value and don't treat them as some commodity, and the asset management system shouldn't be treated that way. It should be treated as the place to really manage and keep track of the value of what you create and the assets that represent your brand and all of the messaging and communications that you want to have with your customers. Couldn't agree more for assets. Like rockstars, by the way. Always rockstars. They have very big assets. They're very important to stuff they create. Okay. Second lesson, quality in, quality out. We learned this the hard way. For a long time, we were focused on the templates and those data feeds, we optimized them, making sure they were creatively as strong as possible, making sure we had lots of different variations. And we said, "Okay, we'll fix the issues afterwards. If there's any issues, we'll QA it, we'll QC it before it goes out." So our mindset was very reactive. It wasn't proactive. It was like, "We'll just fix stuff as it appears and everything will be fine and we'll catch the mistakes later." The result is just a very large volume of assets riddled with errors. So I definitely wouldn't recommend that approach again because a mistake is multiplied thousands of times across thousands of versions. If you get a typo and suddenly it's in 2,000 assets which you then have to go back and fix. So we spent a huge amount of time and QA resources manually checking those things after they've been created.
Combing through each files, trying to find the errors. It became quite a never-ending process of trying to, it's like a whack-a-mole. You think you fix something and then something else pops up in that you've got to fix. And actually more importantly, we calculated, we actually spent 25% of the overall budget on fixing problems which we had created ourselves which isn't ideal. And that's when it really, really clicked. We're doing it wrong. With automation bad inputs don't just stay bad, they multiply exponentially.
And then a few years ago, Zalando came along and they said to us, "Right, guys, we want zero percent defect rates. We don't want final QC checks, quality control checks and we want no manual checking." And we went, "Okay, that's a challenge. How are we going to do this?" And at first it seemed quite impossible but then actually we realized we just need to do the QC check at the start, not at the end. And we were absolutely obsessed with trying to prevent errors in the data feeds and the templates. And that covered a number of different things. Number one, we had to plan for every different scenario upfront. These were things like, okay, when we translate the asset into different languages, how we do line breaks if the text wraps onto two lines? Are we going to try and wrap the text or are we going to shrink the text down? How's that going to work? We're quite obsessive about that. How are product shots shown? A pair of sneakers is very different to a nail polish and how do we crop those images so they look like they've been done in an intentional way and not just, okay, that works and it fits.
And we just spent a lot of time thinking about every single possible thing that could go wrong. We built rules, we built constraints, we built contingency plans, trying to think about every edge case and really future-proofing the templates as much as possible. And what that meant is when we hit the render button to create all of the assets, we knew pretty much exactly what we were going to be.
We had confidence. There was no guesswork, there was no surprises, and we were pretty confident about what we were going to create.
So really the takeaway here is the power of automation isn't just the speed and scale but also the reliability and the predictability that it brings when creating the assets. And the only way to do this is to plan obsessively and eliminate the areas upfront, invest in the right people who actually have knowledge about doing this and so know the things to look out for and build really airtight processes so that everything is checked upfront. We've also recently developed an AI QC checker. So we run our data feeds through this checker and it knows things like text events and how to do things. So we're trying to automate as much as possible of actually the feed creation as much as the rendering of the assets itself.
Yeah, so in this case, I'm going to talk just for a moment, although I could spend an hour and a half on this topic, but I promise I won't talk that long on this. GenStudio for Performance Marketing because this is a new product that we've launched that you've probably obviously seen about it on Keynote and MainStage and stuff over the past couple days. But this takes this idea of quality, and reliability into a very specific product launch that we have. And in this case, this product is a GenAI-first application, to create content quickly, and to be able to take that content and create it for very personalized groups of people, or brands, make sure that everything is on brand guidelines that gets created. So you have the reliability to make sure any piece of content that's created in this tool matches your brand guidelines and is compliant for what your brand needs. And then what's even more important is when you activate the content that gets created, you're able to then get insights back and actually improve and optimize it. So part of the process of having reliable content is also fixing it and tweaking it and improving it and not having content that isn't reliable, assets and content out in space that should be changed and improved, right? So we wanted to have a product that takes a very beginning to end for what a performance marketer needs for paid social ads or for email creation and do this in a very reliable way, but leverage AI in order to create this. So there's this balance of being able to utilize AI in order to create your content, but have some reliability to what gets created. And then to be able to have humans and people involved in order to optimize and change in the future. So this is all part of, if you take this and extrapolate what we're doing across a lot of different products, that's exactly part of the vision. But it's very clearly articulated in how this product works. So we're really excited about what this is able to do in order to bring more reliability and bring more value, to how we can leverage GenAI through the lifecycle of paid media campaigns or email creation.
Okay, third one is really about managing the entire workflow and not just the creation of the assets. So a lot of us, as I said before, we get very excited about automating the content creation stage, the asset creation stage but then we forget what comes next. And if you don't rethink your workflows, automation won't save time. What it is, it just pushes a bottleneck further down the process and it's going to catch you later on.
And that's because existing processes are built really around creating smaller volumes of assets. And when working at scale, you've got questions like how do I get all my stakeholders not to validate and test and feedback on 20 assets or 30 assets but 3,000 assets or 5,000 assets. And it's a very, very different problem.
And we have a client or had a client, have a client who the way that they used to do it was to manage it in a good old Excel spreadsheet.
And that was completely manageable with 30 assets. It was fine. But we did a campaign for them and it created 7,000 assets and they were video assets, 30-second video assets.
And it was across 10 different local markets. So it was 10 different marketing managers who had to approve that. And they had this big spreadsheet, it had 7,000 rows. We called it the rainbow spreadsheet because every market decided to color code it in a different color. And then they added their feedback for every single asset about what was right and which was wrong. And it was absolute chaos. We missed approvals, it had conflicting feedback, the designers who were trying to fix stuff just didn't know where things were. And it was slow, it was stressful, and it completely undermined the reason we were doing the automation in the first place.
And so really the lesson here is the tech that manages the workflow is just as important as the technology that creates the assets themselves.
And we have fixed this in a number of different cases. This is an example for Smart where we used Adobe Workfront to do this particular thing.
Everything is in one place, it's centralized, all of the assets are in a digital asset management system, it's got full version control. And most importantly, particularly for the marketing editors, they have contextual feedback. Instead of leaving their comment in a row in a spreadsheet, they highlight visually what's wrong, they add the comment, they hit the Send button and the designer knows exactly what to fix when they see it.
So automation is about the whole creative lifecycle, not just the asset creation part.
Just like rockstars, right? It's the whole cycle. And this is an example of unifying the creation and production workflow within the context of GenStudio for Performance Marketing again, right? And if you look at all of these different steps from kicking off a campaign to creative to reviewing and approving all of this, it's a number of different teams and stakeholders that are working to deliver this collaboratively for the same goal, trying to go from having a paid media campaign, an idea about what that needs to do that will begin in some brief for kickoff, and then being able to, in the end, actually get it out there, make a difference, see conversions, understand what's working, and then optimize again. So this flow is a perfect example in a very small world of how you need to have workflows and have teams collaborating together, working towards the same goal in a simple and seamless way in order to move quickly because one of the big objectives is to reduce time and move very, very fast. And so I think this is also interesting on this slide because here we talk about-- There's actually three builds. You can go ahead and build the whole thing. You can go to the next two and just put the whole thing up there. So in this case, this is an example of different teams. Too far. Visualize. There we go. I thought there was a-- There we go. So we didn't practice this part.
Non-multiple transactions on one side. No. There's this issue of getting the slides over to each other. It's unfortunately, it's not seamless when collaborating-- - It's not. - On slides. I can tell you that across countries and stuff as well. But so in this case, if we just double-click on the idea of where you're actually dealing with the content production element of this full flow, even this has different people and different teams, and in our case, different products that are delivering. How do you scale asset production as you need to in order to grow very quickly and leverage scale? How do you actually utilize that and make the right decisions when you're creating the performance marketing campaign along with all of the assets that you've already built? And then how do you then actually leverage some of those same assets in a simpler last mile way for a company and empower more people to be able to contribute to this process. So that's a big piece of collaboration and workflows is how do you allow more people in your business to actually be part of the content creation lifecycle. And by creating transparency and easy ways for people to collaborate together, it's easier to then increase those that are contributing to content. And that's part of the vision of what we want to be able to enable.
Okay.
Fourth one, experiment boldly because failure fuels growth.
That's one of the headings I've just thought. Perhaps it should have said it's a marathon, not a sprint, but the same approach. Creative automation is still evolving. I think we've seen that if you were at Summit last year or the year before, the innovations with GenStudio as Joshua was talking about, it's evolving very, very, very quickly. And the companies who are leading in this space aren't waiting for it to be perfect or planning for it to be perfect. They're the ones who are willing to invest, to experiment, to see what works, what doesn't work and take a few risks and learn as they go.
Because the most important thing when implementing a creative automation is not just the tools, it's actually the mindset. It's how you think about things. It's how you think about the experimentation. It's how you think about creating all of the assets which is a very different way than you probably have done in the past.
And this is probably the best example we have of a marathon, not a sprint, is Just Eat Takeaway. Just Eat Takeaway are a food delivery service and we've been working with them for just over three years on what we call Project Sunday. And Project Sunday is their creative automation project. How do we scale all of these different assets? When we first started working with them, we launched in one market, one country market in Europe and we only did CRM assets. It went really, really well the first time we did it. And so we said, "Okay, why don't we scale out to 15 different markets? What if we expand from CRM to paid media as well?" And it really, really exploded. It exploded from a couple of campaigns we're running a month to creating thousands of thousands of assets that we're doing every month.
But the question I always ask myself is why they continue to do it? Now it is very, very cost-effective. We're creating lots and lots of different assets but it's not just the cost effectiveness. It's actually the information that they're learning about what's working and what's not working. I think my favorite anecdotes on this is, or favorite fact is that in the UK where I'm based, photos of burgers on the ads convert much better than pizzas.
And that's not the same for every market. And that's actually very valuable information when you're thinking about the next round of assets that you're going to create. If I want to get a particular type of click-through rate or particular behavior, what actually performs best in what's different market? So it's not just an investment in creating the assets, it's actually an investment in learning what works and what doesn't work. And now we run experiments pretty regularly to make sure that they're keeping on top of trends and making sure that they're investing in the right templates and the right approaches and making the best return on this big investment they've made over the past three years to create all of these different thousands of assets.
And it's because they were in it for the long run and they invested accordingly because it's very easy to get a little bit disheartened when an experiment doesn't work because not every experiment will succeed. But if you learn from each failure, it is a step forward in the right direction.
So looking again at GenStudio for Performance Marketing as a good example, we wanted to build a way to test an experiment with more content variations easily. And so with this tool, the idea is we're able to create a number of variations of content that you can choose from via GenAI that does this creation for you. And then you can very quickly test to understand how things are going and optimize. So Adobe has been using this ourselves, and we've seen a massive improvement in quality of conversions by being able to understand what works all the way down to an attribute of an image. So maybe we can learn that images that are in the daytime are better performing than images that are in the nighttime. Certain colors perform better than other colors. Any kind of attribute of an image, but being able to test new variations of that easily and then very quickly refresh to see how well that works. So this idea of being able to work in a more agile way and test variations and optimize is critical in order to be successful, especially with, in the case of this, things like paid media, which needs to be very fresh and refreshed quickly and optimized. And so this is all meant to look at three things that we're trying to solve, right? How do you automate the creation and create the volume that's quality and of the value as we discussed already? How do you do this by reducing time that it takes to actually create content and how do you manage costs in this way. And if you can control these things while increasing value, reducing time, and helping to manage your costs, you can actually optimize and move and test variations. But if you can't do these things, it's very difficult to go through a testing pattern because if it takes too long or you're not able to create the volume you need to be able to test all of the things you want to test, then it's very difficult to achieve that. So by hitting on these three topics, you're able to open up the window of being able to do so much more and test variations, see what works, and improve conversions. And that's exactly what we want to achieve and how we're looking at GenAI in our products like GenStudio for Performance Marketing.
Okay. This one I think is the most important because for all of the automation, all of the AI, all of the efficiency gains that we've talked about today, there's a thing that machines can't replace and that's human creativity.
A common misconception that we hear when we're presenting demos with creative automation is that automating content is removing creativity altogether. And that couldn't be further from the truth. And we hear that more and more especially as GenAI creeps in that it will just generate the content for us. It will automatically optimize performance. Humans won't be needed anymore at any stage.
But automation doesn't replace creativity. It really does enhance it and actually give us more opportunities to be creative in some cases. And this is probably my favorite example of that. It's for Zoopla. Zoopla is a housing marketplace based in the UK.
And the key to the creative idea isn't the template or just the template, although the template looks really, really nice.
The creativity is actually in the data feed. Probably the thing that people think is the more boring part because Zoopla, because they're selling houses or advertising houses for sale, it's super niche from a location perspective. They want to make sure that every paid ad that they're showing to a potential customer is super relevant to them. And that's because housing prices, housing availability, and supply, different things that are important to different people vary a lot from location to location. And instead of having a generic brand message to put out there, they really want it to be super, super targeted based on the particular location someone is. So we actually used data, not just messaging or creative messaging, we actually use real data. So we got to average house prices. We actually went to public accessibly data like school availability in a particular area or school ratings in a particular area which is publicly available data. And based on the user and where they are when they're looking at the ad or where we think that they are, we actually show them an ad which has been created for their specific zipcode or postcode in the UK with the relevant house price and anything else which we think is really important in the area that they live in. And that means we've generated thousands of super localized assets. So not just from a country perspective but from a very, very localized perspective.
And it's not just-- This isn't about automation for just efficiency sake. It's actually automation for a better creative idea.
It's strategic personalization not just for scale.
And this comes back to the point that smart automation, which I mentioned before, isn't about making more assets. It's about making more relevant, more effective and more strategic assets.
All right. So I'm going to tell a story instead of reading this slide because I like stories. How many people first have experimented with Firefly? At this point, everybody should. All right. Okay. Anybody who hasn't raised their hand in the room tonight play with Firefly. So I'm going to tell a story because I think what it represents is the accessibility to creativity that Firefly and these tools can bring. So at Christmas time, my daughter's learning to be-- She's studying to be a teacher. So we live in Denmark, as mentioned, but we're American, as you probably can tell. And she's learning to be a teacher. She wants to teach English in Danish school. And so she's working with little kids. And so at Christmas, we were with my brother's little kids, my niece and nephew, and my sister trying to get them excited and do something other than play and run around like little kids, said, "Let's write a story together." So they wrote a Christmas story. And they read it, and I thought it was really interesting and very creative. And I said, "Well, why don't we sit down and break this up into sections and go into Firefly and take those sections that you've written and use those as prompts and create images and actually make a little book about a Christmas story to give to your parents when they get they were gone, when they come back as a Christmas present." So then we sat down and spent like two hours with the little kids going through creating all of these images. And when we created each image, it actually unlocked a new layer of creativity in them that started to modify and make the story even better because they started to visualize some of what they'd come up with. So just little kids, that was it. They were able to unlock a new level of creativity by using something like Firefly. It just opened up something new. They were able to think differently and work differently. And in the end, we produced this really cool story with a bunch of pictures and printed it out and gave it to their parents for Christmas. I hope they liked it. I don't know. My brother, he's not as enthusiast. I don't know. I'm not going to complain about it. But anyway, I think he liked it. But it was a ton of fun, and it just to me, really opened the idea that somebody, a little kid that doesn't have any preconceived notion of what creativity should be or what anything should be, started to think differently because this was accessible to them and allowed them to be much more creative. And that's what we see when we work with teams at Adobe, and we think about this not just in a little kids, but how this becomes very enterprise and a business, is more people can contribute to what creativity means via these tools because you start to think differently, you approach problems differently, and you can, in fact, become much more creative. And that's what we want to do is have humans in the middle to be able to launch more creativity and have more people contributing to the process of creating content. And maybe one day these little niece and nephews will do that. I don't know. We'll see. But so that's the way I like to think about what humans sitting at the heart of creativity can mean, right? And using GenAI to unlock a whole bunch of new ideas that maybe otherwise wouldn't have even come to them, right? Okay. That's our five lessons.
I hope you found them valuable in some way especially, if you're just embarking on your creative automation journey or looking to scale up.
I think the final takeaway is back to this automate smarter, not just faster. The best creative automation isn't just about scaling production. It's about solving creative challenges using technology and in more intelligent ways. It's not about removing humans at all. It's really about enhancing and elevating what they can do with the limited resources and time that they have available to them to create these sorts of assets.
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We've done this a lot as hopefully you've seen. We make creative automation smarter. We have the expertise to help. So please, if you have any questions, if you are starting on this journey, if you want some advice, I'm available. I'll be here for the next couple of days. Please link in with me, ask me any questions. I'm very, very happy to help and point you in the right direction.
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