← MarTech Podcast ™ // Marketing + Technology = Business Growth
MarTech Podcast ™ // Marketing + Technology = Business Growth
Adobe SVP's take on Marketing Enterprise AI
00:39:37
Loading summary
Transcript81 lines
- [00:00]
A
The Martech Podcast is a proud member of the I Hear Everything Podcast Network. Looking to launch or scale your podcast, I Hear Everything delivers podcast production, growth and monetization solutions that transform your words into profit. Ready to give your brand a voice? Then visit iheareverything.com.
- [00:26]
B
From advertising to software as a service to data across all of our programs
- [00:32]
A
and clients, we've seen a 55 to 65% open rate. Getting brands authentically integrated into content performs better than TV advertising.
- [00:42]
B
Typical lifespan of an article is about 24 to 36 hours.
- [00:47]
A
We're reaching out to the right person
- [00:48]
B
with the right message and a clear call to action. Then it's just a matter of timing.
- [00:54]
A
Welcome to the Martech Podcast, a member
- [00:56]
B
of the I Hear Everything Podcast Network.
- [01:00]
A
In this podcast, you'll hear the stories
- [01:02]
B
of world class marketers that you use
- [01:04]
A
technology to drive business results and achieve career success. Here's the host of the Martech podcast
- [01:11]
B
Benjamin Shapiro
- [01:16]
A
71% 71% of marketers believe demand for content will grow 5x by 2027, according to a study by Adobe, consumers demand personalized experiences not based on what they clicked yesterday or last week, but based on what they are doing right now. In the last two years we've gone from using our fingers to type to a world where marketers can generate infinite variations, campaigns and experiences on demand. Now the challenge isn't production, it's coordination. So how do you maintain brand consistency, attribution and governance across experiences when your teams have unlimited creative capacity? I'm Benjamin Shapiro and today we're talking to Patrick Brown, SVP of Global Marketing at Adobe, about what enterprise AI adoption actually looks like when you move beyond experimentation into operational scale. Today's interview is brought to you by Shift Paradigm. Marketing today is buried in complexity. You've got the tech, you've got the tools, but moving the needle feels harder than ever. And the last thing us marketers need is another consultant pitching digital transformation. Enter Shift Paradigm Shift is an integrated team of experts who help enterprise brands turn complexity into traction. Their work is insight led and strategically grounded, designed not to sell you a service or a piece of tech, but to actually solve real business challenges. What makes them different? Well, they're AI enabled but not AI dependent. They're human first, but plugged into the latest tools and models in the moments those models need to go through to prove themselves. They get techy without losing sight of the real person behind every click. And they don't just hand you a deck, they build the blueprints and state of Develop, deploy, and run the engine. Growth isn't one size fits all. So stop settling for strategies that collect dust and start working with a team that actually builds for you. Visit ShiftParadigm.com to see how they can help you connect meaningfully with your audience. That's ShiftParadigm.com Patrick, welcome to the Martech podcast.
- [03:17]
B
Hi, Ben. Happy to be here.
- [03:18]
A
Excited to have you here. Look, we live actually in the same town, but fundamentally we are worlds apart when it comes to the adoption and usage of AI. So I'm excited to talk to you a little bit about what the difference is between how we're using this groundbreaking technology. I come from the solopreneur background where I am pretending to have an army of operators to create a ton of stuff, and it's amazing. I can be in places I never thought I would be. You actually have an army of people that are working for you and Adobe's customers to build all of your content, and you have opposite problems which relies with government. So, first off, just give me a lay of the land of the world for Adobe and how you think about integrating AI when you have such an expansive team.
- [04:15]
B
Yeah, Ben, that is the core question. And again, I'm really, really happy to be here. And in some ways, I'm envious of the rate at which you're able to move. And we talk to a lot of companies that are either starting off or building their brands, and the decisions that they can make with no sunk cost historically allow them to just move in a really different way. And it's actually an interesting area to study for, for those of us that are running, you know, a large organization that have kind of entrenched ways of working. And so, you know, it was interesting. There was a study not long ago where it was like, what was the. I think the question that was asked was like, what? What percent efficiency gains have you gotten off the backs of AI? And they interviewed somebody like yourself running a small business, and then the numbers were staggering. It was like multiples of productivity. And then they asked somebody, I think at Google, and they said 10%, but if I can get 10% on, you know, 10,000 people, that's pretty amazing. And so it's an interesting way. It's a little bit of a way that we have to reframe how we think about the adoption of these AI tools. And I would say, you know, a lot of folks, as we've seen it, and I talked to these other brands, we're kind of in. We have been in this proliferation of tools game for a little while. And it started with you basically have two jobs as a leader. It's make sure that there's access to these AI tools and so people are aware of them and provide access and then encourage usage. And now we're shifting into this, trying to figure out those couple big opportunities from all that usage data that you have that you think you really want to focus on and scale. And so that's, that's kind of the stage we're in and we're trying to build a lot of tools to help companies do that.
- [05:57]
A
I think there's something to be said for I as a solopreneur can be 10x more effective and maybe the employees at Adobe might be 10% more effective, but obviously there is more scale there. Fundamentally they're relatively the same tools that we're using. Is the reason why adoption for smaller companies is more effective because of the rollout, because of the decision making process process because of the training. Like why does Claude help me more than it might someone at Google?
- [06:32]
B
Yeah, it's a, it that it's a great question. I think it's twofold. I think it's like when you have trains that you have to get to places on time, you've got a lot of systems that you've built over the years to get them there and you have this option of like I have to disrupt these trains and these schedules and these things that I'm running using these potentially new trains tools. And this is like classic change adoption or change management within organizations. And I think what you start to quickly see is pockets of really advanced and exciting adoption that then you can try to scale out, but you really have to help the organization like move beyond just exploration to like a real defined approach to like say, okay, this is how we're going to really disrupt how we even think about getting trained from A to B. Whereas not having some of that or being able to like make the call on your own I think is really an empowering way to go for smaller organizations. But I think, you know, larger companies are going to have to look at that and say there's no reason that we can't disrupt ourselves at the same rate that a smaller company is doing. It's just going to take a little more work and a little more coordination.
- [07:36]
A
Yeah, coordination seems to be the word that sticks out to me, I think about how my work has become more effective because I, as you know, the, let's call me the marketer now also can be the engineer and the product person. And the designer, but you actually have an engineer and a product person designer. And so I'm imagining that the lines are blurred between multiple teams, which probably creates some friction or people aren't able to use the tools to their fullest effect because somebody else's job is to do the things that they now can do. You mentioned when we met at Adobe Summit that your team is really customer zero for some of the things that Adobe has launched. Talk to me about some of the ways that you've used AI internally and how that turned into actually public facing features.
- [08:25]
B
Yeah, those are. And they're two related kind of conversations. And I would say we ran into a situation just like you're mentioning and it would have been when, when Adobe released a product called Adobe Firefly. And it was the, this was a couple years ago in 2023 and it was the first commercially safe, and still is the only commercially safe model that you can use in your organization that's not going to produce a likeness that then Disney's going to come sue you for or something like that. It is genuinely commercially safe. The challenge internally was we as marketers and I run a media organization and an email organization and we send a lot globally. We've been historically constrained by content, as you, as you mentioned in your opening and suddenly you had this capability to not be constrained by content, but it did require a different way of working. And what we did was we essentially took a media buyer, an LCM strategist, and we put them together with Platform Engineer as well as one of our AI solutions folks that was behind Firefly and said, we're no longer gated by technology, but we're going to have to work differently and we probably are going to need a new solution built on that technology. And so this team, it was funny because the project name was called Project Platypus and it was part of a joke because we were like, well, is it a duck or is it a beaver? And it was somewhat intentional because we had to keep it lighthearted. But also, you know, we weren't sure where it was going to go.
- [09:53]
A
And Project Jackass didn't have the same connotation, did it?
- [09:57]
B
It doesn't show up well in a board deck, you know, but, but anyway, so the team really rallied behind this challenge and what it meant was, at the end of the day, we ended up building all of these sort of countermeasures that organizationally have been built into the tool. A great example is we had a creative production person, one of our creative directors, as a Part of this program. There's an enormous amount of value that they bring just knowing the brand and the design systems and how we want to show up. That maybe is in their head and often not written down to the rigor at which they know it, but it forced them to partner with the teams and say, okay, I'm going to really document this. So the tool can like I can instantiate all the things that I know into a tool so the marketer can move faster. And this tool ultimately came, became a product called Gen Studio for Performance Marketing, which is a tool that a marketer can use a media buyer or email marketer to develop content on strategy, on brand, on a message with a creative professional kind of working along with them. And it just, it kind of flipped on its head the traditional kind of brief driven, you know, campaign flow and moved to something much more nimble.
- [11:04]
A
It seems like the content constraints went away as you started to adopt AI internally. What surprised you about the process and what happens when those content constraints go away?
- [11:16]
B
Yeah, it goes back to people was one of the first surprises that we had. We, as we got this first core team together, we, we, we asked for volunteers across our creative teams and our internal studios as well as our technologists and our media teams. And we got this group of hand raisers that were incredibly interested in trying to kind of disrupt the way we worked. And what this meant was they all worked in a little bit of a different capacity. What we found is that first group was so incredibly successful. I think it created a little bit of. We were very confident in the ability to scale really quickly because of this group. What we didn't realize is those people that self selected had a bias on kind of what they were, how they were wired. The studio and creatives were really technology and media forward. And then we found all the media folks had creative side gigs. We had photographers and artists and they just were really good at knowing how to get good things and what good things look like coming out of. AI had great taste that was really hard to replicate in kind of subsequent processes. We had to build more infrastructure for the tool to help people that like, hey, I might be a great technical marketer, but I'm not quite as good at generating my own assets or understanding what I want to do, but I can tell a story. And so that's where we learned that helping folks through this transition and working differently is going to require more training and actually support from the tool.
- [12:44]
A
Some of the times you can do something once with AI and you get magic. I was Just building our website and rebuilding the. I hear everything. Our production company's website and the first draft came out beautiful. And then once I started to iterate, it got worse and worse and worse. How do you think about using AI? Not just, you know, for me when I'm iterating, sometimes the output tends to be, you know, a copy of a copy, but also then you have thousands of people that are working on these sort of foundational or fundamental assets. How are you able to replicate and build consistency using AI across large teams?
- [13:27]
B
Yeah, that is, you're right that you're able to scale really quickly. And I think it's interesting the, the comment that you made on like, the more that I work on something or the more complicated my prompt gets, sometimes the worse the outcome gets or the what comes out the other side. And we did see some of that too. And one of the things or another learning that we had early on was particularly for the content flow, we started generating, generating all of these assets. Huge proliferation in assets. And I think the numbers were, we grew like the number of email assets that we were running grew like 600% quarter on quarter just because we had so many different variants that we could run. Now the issue was did we have the right person there to help us make sure we were maintaining a story across our segments or like, how are we telling a story across all those new assets that we're putting into the world? And that required us, you know, we, you need to still have the, the kind of core principles of marketing of like, what is the story I'm trying to tell? How do I want to message? Like, what do I really want to land? Regardless of my ability, if I'm no longer gated by the production workflow of creative of creative assets. And so we really, you know, have like almost a, like a framework that says, this is the messaging, here's the story that we go along that we want to pull through and we really check it against each one of the assets that we're creating and that that's allowed us to make sure that everybody's really aligned with the story we're trying to tell, regardless of what we're generating. I think that that has been a great way for us to say, you know what, this is really headed down a wrong path. We need to pull back and like start to create a new, a new storyline.
- [14:58]
A
I want to double click on that because when I think about this concept of like unlimited creative, it's hard for me to wrap my head around actually telling a coherent story right Understanding the beats of what is going out. How do you figure out how to match Endless Creative to. Here's the beginning, middle and end of the story we're trying to tell across multiple different channels.
- [15:25]
B
Yeah, there's a role that we found to be ever more important, which is this kind of customer marketing focused person. And in the past, I'd say this function is gone by a lot of different names. Campaign marketer, integrated marketers, all these different things. And what this has really become is it's not as much of a coordination function. It's really the resident kind of voice of who the customer is and how the product is serving that customer. And they kind of are the one that is the constant foil to make sure that they're kind of helping to guide the ongoing structure and the way that we're communicating. And it's not like this group is really in a consultative role where they're helping to kind of define even the messaging hierarchy the way that we want to, like, feed all of the different tools downstream. And then increasingly those folks are creating these Personas that we actually can load into some of the agents that then say, okay, so you know what, we actually want to change the tone that we want to speak to this audience because they want to be much more casual or accessible. And so I want to build that into something that the agent then can react to or the tool can react to that then I'm getting something better on the first pass. And that, I think, is an important role that has become increasingly important. And the teams are just naturally seeking out that guidance because ultimately that is starting to be what performs for the assets that they're putting in market as well.
- [16:44]
A
There's a word that I kind of chuckle at because of how my organization functions, where the concept of governance is. Do I think it looks pretty and is it going to offend anyone? And if it is, yes, it looks pretty and no, it's not going to be offensive. It gets shipped. I'm imagining that's a little different for you. And what I could see is somebody who's, you know, your integrated marketer, your campaign manager, I forgot what you called them. Is sitting there essentially with like a Tinder type screen being like, good, good, bad, good, bad. And like, how do you go through and actually think about governance with all the different tools that Adobe does, all the different campaigns now we have all the variants and there's. Everybody can create everything all the time. Time. How do you think about governance for what actually gets pushed out to the customer?
- [17:33]
B
Yeah, the way it's interesting. You know, I think that's where we started was we, we. We very much had these folks in this role where, where they were in a Caesar, thumbs up, thumbs down sort of moment in the.
- [17:45]
A
I was thinking more like a monkey
- [17:47]
B
slapping left or right, but yeah, or that. Or that maybe a little less morbid, but they, they would literally try to do that. And what was happening was there was frustration on both sides. The producers that were now producing all of this huge amount of content, and then this individual that was like, you guys are just not getting the brief on who we built the product for. And I think the way that they're working now is they, they. They're literally working as a part of this squad where folks on my side, the analysts or whether they be the, the media folks, are bringing in, like, hey, these are the things that seem to be performing or resonating with the customers. Let's check it against the messaging and hierarchy. And it's a much more inclusive conversation of like, what's working. It's not about the channel or the spend. It's increasingly about the actual assets. Like, are people engaging with this asset and how does this connect to what we thought they would do? And I think that has been a. It has allowed the team still the license to move really quickly because they understand the shaping, changing game of who they're communicating to. But then this kind of ongoing discussion where that person doesn't have to be in the thumbs up, thumbs down, monkey slapping or Caesar's approach to saying what's good or not.
- [18:54]
A
I like the Caesar's approach too. It seems like there is a sort of supply chain metaphor for your creative, I think of using AI, it's kind of like growth hacking. I can put content everywhere, all of the time and have a much bigger footprint. For you, it is about control and filtering. Are you using AI to, to help with that effort?
- [19:22]
B
Yeah, we are. And I think this is where in a couple different areas. One is, you know, we have from a supply chain perspective, how do we make sure that we're producing these, these real clear documents that we can synthesize all of the different ways that we've shown out. And I'll give you a very specific example where historically we would have a brief that defines how we want to communicate to a given segment. And let's say one of them for us is of course, professional creatives. We built a lot of tools for the amazing folks out there that make amazing art with our creative tools like Photoshop or Illustrator or these sorts of things. But we have a legacy definition of who those folks are. And if we start to bring back some of the way that we're putting either assets or experiences into the world, whether they be social first or ads, and we're finding that people actually responding better to different ways, either the different copy or the different assets, how are we then updating even the way that we think about the communication with those? That's an enormous, just synthesizing problem of all the different ways that we're communicating and the way that we think that we should communicate. And so we actually have this brand agent that we essentially say, okay, this is what we think are, this is how we think we're showing up. But how are we actually showing up on our website? Or how are we actually showing up in our media that we're running into the world? It's this product we call Brand Brain. I think it goes by another name now. But it's a really cool way for us to say actually, you know what, you actually are showing up slightly differently and these are some takeaways that you should bring back into your brand standards. And do you like those or not? And those are capabilities that historically we would not have been able to do.
- [20:58]
A
I'll preface this with don't fire anybody on a podcast, but we've heard a ton about large enterprises like Adobe saying, you know what, AI can do most of these jobs now. We're going to make our teams smaller, flatter, reduce the middle management. You're using AI for governance, AI for creation. Right. AI for distribution. What effect do you think this has on organizations like yours? You don't have to specifically tell me Adobe's plans, but do you agree with organizations get flatter and smaller? Talk to me about the impact on people.
- [21:38]
B
Yeah, there's been a lot of that, of course, and that drives, I mean there's been lots of conversations, lots of press on this.
- [21:43]
A
Nobody ever wants to come out and says, I over hired. I'm just going to start firing people. They blame AI.
- [21:48]
B
It's a failure of vision. It's kind of a, right now it's a crutch. We see some of these massive layoffs that are on the backs. It's probably Covid over hiring. There was a bunch of other issues. But to put it on the, at the feet of AI for where it is today, it feels lazy. I think any organization, any organization has more work, more problems than people, more work than hands, like all of these sorts of things. And I think any manager or strong leader can redeploy and help folks like either expand into new segments or cover new categories or do better in certain countries with the marketing that you're running. And I think that is the name of the game for us. The way we think about it is we actually. Your supply chain metaphor previously was apropos too, because we've actually adopted a mechanism from. I think it's from Six Sigma, but it's dmaic, which is this define measure, analyze, inspect and control. And it comes from supply chain. But really it was when I started my career, I was actually in an operations practice in consulting. And I remember going to an oil refinery and I watched how supply chain professionals in particular analyze any sort of opportunity for scale or improvement and then just roll it out at scale. And so I remember this process of like this giant cooling tower for petroleum. And they found that if they just put these specific wrenches closer to these folks that needed to do things, they could save like 15 minutes in a day. But when they did the math across all of their, it was just a huge amount of savings in terms of the people. And I think we've employed a similar structure just to give our organization two things. One, really feel empowered about where we can potentially leverage the AI, but then identify what it means to really take a success and roll it out globally. And so if we've all aligned, like, you know what, reporting is really important, but actually we should be able to allow agents to do a lot of those kind of very manual reports that we did previously. So if we did this one and it saved us 90%, what if we did it across the 300 other reports and we mobilize a team around to really define the problem, make sure that we analyze the upside and like really start to roll it out. And what we find is the people that are involved in that just start to evolve how they work. And so they're no longer specking out or designing a dashboard, but they may be then providing the visual standards for an agent, for example. And that's, I think, where you have to. What we've done is we've really tried to focus around a rallying objective that's got a really clear outcome and we've got a history of some success. And then once the organization sees something that it likes or that went well, I think organizations are really good at repeating things and then scaling it out.
- [24:32]
A
You're. You're in a unique perspective, or you have a unique perspective because you're using artificial intelligence with a large team, but you're also communicating to marketers and creative about their workflows. How do you think about what you're communicating and what the problems are that marketers face now because of AI that is different than what was happening before.
- [24:54]
B
I think a lot of. Because we're marketers and we're in all of the, you know, many of the organizational kind of communities, like whether it be media or email or marketing analytics, MMA or marketing science, we're still colleagues that are like, hearing problems that everyone has. And I think it's fascinating when you talk to folks in different verticals, whether it be retail or travel or picket, there's interesting problems, but there's some similarities across all of these, where you can understand and kind of hear and empathize with the different flavors of these problems, but all of us are kind of categorizing them into kind of big buckets. Like, there's a creative workflow opportunity, there's analytics, there's data. And I think that kind of empathy, being marketers has been a big piece of what we take into the products that we're trying to build. And we may even say, hey, look, I have friends in consumer packaged goods and they deal with a very different set of problems that I do. But, you know, maybe there's some flavors and we'll work closely with product to say, you know what, while this may not solve a problem for me, it certainly may solve a problem for someone at General Mills or maybe solve a problem for someone at P and G. And then it allows us to kind of make sure that we're scoping the problem in the right way and then we're empathetic to the problems that everybody's dealing with by vertical.
- [26:05]
A
Yeah, the world gets a little bit more complex. I can't imagine what this is like for. For you or Adobe. It's the Creative Suite and it's the analytics and it's the email and like, the product suite is so wide, but now there's this whole other side of entities that you need to market to, where you have all of the consumers, but we also have to market to the agents, to the bots. How do you think about when you're creating your marketing programs? Not just communicating what Adobe is doing to your customers through its regular channels, but also making sure that you're feeding the LLMs and the agents the information they need to make the suggestions. Suggestions that then get to the end customers?
- [26:47]
B
Yeah, that's a. It's a. This early days on a lot of this as we're all looking at our traffic and we're seeing the, the, the growth in the agent driven traffic or
- [26:56]
A
the death of the click as I've been shouting from the rooftop.
- [26:58]
B
But yeah, there is the zero. Yeah, definitely. And, but we certainly see that like we, this is why maybe six months ago, eight months ago, we started a product development cycle for something that we called LLM LLM Optimizer, which is a bit of a mouthful, but it basically means you're, you're no longer. And, and when we started this, what we were noticing is the, the first groups of traffic that we were no longer seeing was the informational search. Because early days on LLMs, remember our experience in ChatGPT 3 or 35 it was like help me find this information, okay, now I no longer need to go to the website. And we certainly saw that. So suddenly we saw this decline in people looking for maybe how to use a mask in Photoshop and it was notable. We're like, huh. So that was the first thing where we were able to say we know that this search is happening, it is no longer coming to us and how do we think about that? What do we do about that? And so quickly this product we developed was really designed to make sure that the answer that someone gets for that question, whether it be in informational now and increasingly it's intent based, is actually accurate. Because if someone is suffering and not finding what they need to do because, because they didn't come to our site, they don't know, they just know that they couldn't get their problem solved in Photoshop. I couldn't figure out the mask. So we quickly. This product is designed to make sure that we're the sources of data that are being cited by the LLM. If it's Reddit, if it's YouTube, if it's off our site, we know at least what those are and we can go correct them or we can make sure that the right content is on them. And the applications for this of course are like informational, but increasingly marketing related too.
- [28:40]
A
So everybody says a different answer for this, but what sources are you finding actually matter?
- [28:47]
B
It's. Well, I think it changes so frequently. That's probably why everybody's giving a different answer. For a while it was like Reddit, Reddit, Reddit. And then I think OpenAI came out publicly and said, well, it's a little less Reddit now. And so, but it's frankly still Reddit. Wikipedia, it's your own site, informational site. It's increasingly the commentary that you see in even conversations, even on some subreddits. And other things. So it changes pretty frequently. There are a couple core ones that we're really kind of doubling down on.
- [29:16]
A
Yeah, I've heard YouTube transcripts are great, said the podcast host. And LinkedIn articles apparently are another hot topic. Not the posts, but the articles.
- [29:26]
B
For some reason, LinkedIn did come on strong. That is true.
- [29:29]
A
There you go.
- [29:29]
B
All right.
- [29:30]
A
Hey, I want to move on to our lightning round where I'm going to ask you some Martech and AI growth related questions.
- [29:37]
B
Are you ready? I am ready.
- [29:39]
A
Okay, let's start off at the top. Adobe is a massive company. How do you define what you do?
- [29:49]
B
That's a great question. I think at the end of the day, we're all about creating the digital experience and that is what we're trying to do. And we really think about like, how are we helping organizations either create and understand the digital experiences they're putting into the world, create new assets, create new art. And we really are focused on helping customers and accounts and brands better understand and create the best customer experience they can.
- [30:18]
A
You are an SVP of marketing at a global enterprise. What do you do on a daily basis?
- [30:26]
B
I think it's. My kids ask the same question and I don't get two sentences in. I think you do a lot of listening and I think you do ultimately, if you get really reductive down to two different things. My job is to try to create structure where often there isn't any meaning. There's a reason we're going after this thing, or defining a problem space to allow the organization to start to really get its head around it. Because there's almost so many opportunities, it can be a little bit disorienting and then helping to manage the change that you've established with that new structure and between those two things, you're kind of vacillating between those two things all the time.
- [31:04]
A
Is there anything that you do where you're still in an operational role?
- [31:08]
B
A lot. I think there are areas where we deep dive collectively. Just because my background is engineering and computer science and I just love the details. I can't help myself. I don't know if my team agrees, but honestly understanding the details. And our current CEO, he Shantan Orion, he always says you have to have your feet in the ground and your head in the clouds, which I think is an interesting thing. The first time I heard that, I'm like, not sure what he means.
- [31:33]
A
Makes me feel like you're going to get stretched.
- [31:36]
B
Well, I think that's probably the takeaway in hindsight, but Being able to go down when you need to to understand and ask the right questions. I don't know what my team knows. I am the least like they know every detail. But being able to ask the right questions and then follow folks down to like as they explain where the opportunity is, I, that's really important.
- [31:54]
A
So how far down do you go? Are you actually like hands in code? I know you have an engineering background, but are you looking evaluating writing code or you have people that are telling you the details of what's actually happening in the baseline.
- [32:07]
B
Thankfully for them, I'm no longer writing code and I don't think anybody is in our organization. My head of AI Solutions famously a couple years ago got in front of a whole bunch of data scientists and said if you're still writing code in six months, you need to come and see me and let's help you get off writing code because of how good things have gotten. But I do like to get down to like the like the architecture level and how do things actually work and I, and the team is gracious enough to spend time with me on these things.
- [32:35]
A
All right, I want to ask you an AI question. What's the most overrated use of AI right now?
- [32:42]
B
I think it is forward looking projection. I think that one of the things that we've seen historically is this and it's this, this, this tension that exists right now on these platforms between the historical context that you've provided it which we, we've loaded as much as we possibly can of all the context and everything that we know and we ask them to ask it to predict the future. And I think oftentimes what you see when you start to do this over time is it only knows the context you provided and it's trying to tell you things that you like. So it is great at summarization, it is great at synthesizing, but I think when the question starts of show shift into things that are more forward looking. It really requires a human judgment on how to think about it.
- [33:25]
A
It seems like every time I watch any sort of video or written work from anybody at a platform company, they always say that you need to be building for the next iteration of the model. And that's great because they know what the next model is and maybe they're just trying to train us to build for the future, but there's no way for us to understand the. I struggle with understanding the capabilities of what's coming down the road other than in six months you won't be coding anymore. Right. Like that made Sense to me. I wasn't coding back then and apparently I am now. So actually the opposite of what they said was going to happen. In six months, no one will be coding. I don't know. That's all I do now. I used to be a podcast host. How do you think about the, the projections when you're looking at what the, you know, the future of AI and the way that everybody's job is changing?
- [34:17]
B
I, you know, I, I think that you have, this is where there's so much happening and there's like you, you have to almost bring it back to your organization and what makes sense. Like at the end of the day there's some, there are some, there's some core bedrock on like what our jobs are. And I think basically we've got three different pillars within our organization. We're delivering great experiences into the world. Like whether they be through like social content that's interesting or any, even advertising or emails. We're measuring and trying to understand what works and then we're building some of these foundational tools and that's all in the service of like helping folks connect with our products. At the end of the day, like, that's how we think about it and how we employ AI to like do those things. What is coming next I think will just accelerate in certain areas that I don't know that I can even forecast.
- [35:02]
A
What's the one marketing job that you think became increasingly more valuable because of AI?
- [35:07]
B
I think it's in our, in our analytics space where you are, we call it an applied analyst. And there are these people that really understand and how, what is happening in a business and they're able to explain it in really, really simple ways. They make clear recommendations, they articulate what's happened. And with the proliferation of everybody having all of these capabilities and the ability to summarize and everybody can write code and everybody can analyze anything. That group that has some core principles around statistics and how things work and what is incremental and what is truth, they have become incredibly important because now everybody has a perspective that they've run through.
- [35:46]
A
Claude, last question for you. What is the one most slept on product at Adobe that everyone in marketing should be using?
- [35:57]
B
Interesting. There's so many. Where do I pick?
- [36:01]
A
That's my problem with Adobe in general is there's so much, there's so many. How do you figure out a vertical? How do you, how do you apply Adobe? It's so broad.
- [36:11]
B
There is a. So I'm, I'm going to, I'm going To cheat. I'm going to give you two. So we have a free product and so one of the things that you're. We're always struggling right now is like how do I make sure that I'm leveraging AI? Like anytime we have a problem is like how could I use AI for this? It's kind of an open question that I think we're all pontificating. One of those is like grabbing context so I can quickly load and build the best prompt possible. We have a product called Adobe Scan and what it does, it's on your mobile phone, it's free and you can basically take a picture of anything and it'll turn it into a basically an OCR recognizable PDF. Like it's, it is the best capture device for context on the planet and you can use it to drop into anything to explain like questions that I've got. Think of it if you're at a conference, think if you're like, you see something interesting and you want or take a physical file that you see, you can use that to, to ask questions or like load it in as context. And that is something that we're even using now like to take pictures of my notepad and putting it in as context. That's one another one that we've got that is, that is more on the scaled side. We have a product called Firefly for creative production and think of it as basically the engine that sits underneath Firefly that you can access programmatically to drive enormous scale in your business. So if you're now sending 15 billion emails a year and you can programmatically in real time using data, go and create assets or assemble assets programmatically through this tool. It is an incredibly, it's an unbelievable way to get scaled production really quickly and work really differently through some of the stuff that you know, all the evergreen assets that you're putting into the world and that's something where we're seeing brands really lean into it.
- [37:53]
A
I said last question and then I realized there's something I desperately have to ask you. A lot of attention was given to Salesforce changing their model and essentially allowing the entire Salesforce ecosystem to be called from a command line prompt. And they're changing their billing around it as well. How do you and Adobe think about the change in SaaS business models when it comes to billing or the usage of coding tools?
- [38:26]
B
This is the, I'll say first that the science isn't really settled on kind of where this goes. I think it's. We're at the stage now where you have to be able to offer your products in multiple ways, including whether it be through an MCP type engagement where the MCP can access and connect. At the end of the day you have tools and you've got ways that you can access them through mcps to do things. And I think we're at the stage too where we're trying to figure out what do brands actually want in terms of being able to either access our systems and tools through those interfaces versus actually using the interfaces themselves. And I think companies are going to be at many, many different places. I also think that it'll be interesting to see how the monetization works down the road where we see toll gating through some of those MCPs or tool usage or what that looks like. And I think we are trying everything but we are mostly partnering with our to figure out how do they want to operate and some of them are in different places on these things.
- [39:22]
A
Yeah, I fundamentally believe that there will be an incredible amount of shift towards people generating their own software and creating personalized experience. But I also don't believe that the entire notion of user interface and the platform is going away. And it feels like everyone is very dramatically saying we're only going to be operating in Claude code or in Codex or hey, look, everybody's just going to go back to the back to the basics and start using the platforms. There's going to be some equilibrium and some shift in between those two back and forth.
- [39:56]
B
Yep, I'm totally aligned with that.
- [39:58]
A
All right, Patrick, I threw a ton at you. We bounced all over the place. I appreciate you coming on the podcast and being my guest and hope to see you around the neighborhood sometime soon.
- [40:07]
B
It was a pleasure. Thanks, Ben.
- [40:08]
A
All right, that wraps up this episode of the MarTech podcast. Thanks to Patrick Brown, the SVP of Global Marketing at Adobe, for joining us. A special thanks to Shift Paradigm for sponsoring this podcast. Shift is an integrated team of experts who help enterprise brands bridge the gap between strategy data and customers. Human first, AI enabled and execution led. They build the blueprints, then stay to develop, deploy and run the engine you need. So stop settling for decks that collect dust and start working with a team that actually builds for you. Visit ShiftParadigm.com to see how they can help you connect meaningfully with your audience. If you'd like to get in touch with Patrick, you could find a link to his LinkedIn profile in our show notes or on martechpod.com or you could visit his company's website, which is adobe.com. and if you haven't subscribed yet and you want a daily stream of marketing and technology knowledge in your podcast feed, hit the subscribe button in your podcast app or on YouTube and we'll be back in your feed next week. All right, that's it for today, but until next time, my advice is to just focus on keeping your customers happy.
- [41:28]
B
Foreign.
- [41:38]
A
Thanks for listening to the Martech podcast and I hear everything. Production Looking to launch or scale a podcast like this one for your brand? Then visit iheareverything.com.