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00:00So, my name is Jay Tucker. I run the Center for Media, Entertainment, and Sports at UCLA's Business School.
00:05I also have the pleasure and honor of being able to host conversations like this at Variety Summits from time to time.
00:12I will tell you that my passion has always really been innovation at this intersection of technology and entertainment.
00:19And I'm thrilled to be able to have a conversation about one of the areas of innovation that's been on everybody's mind, it seems like, for the last two years.
00:28So, strap yourselves in. We're going to have a conversation about AI and specifically what it means for you marketing types.
00:36How many of you, just out of curiosity, how many of you are using AI in some way right now?
00:43Okay. Keep your hands up if you are using AI in a strategic way in your job role now, like it's baked into your work functions.
00:53A few. Okay. Okay.
00:56So, with that, I'm going to jump right into it by introducing Angie Barrick, who's over at Google.
01:03Hi, Angie. Thank you for joining us.
01:04Hi, Jay.
01:06So, we've talked about this many times, but when I first met you years ago, you would talk about using technology specifically to improve business outcomes.
01:18That it wasn't just about having the tech or, you know, completing a task, but thinking from, you know, what are the desired results and how are we going to incorporate technology both to achieve those results, but also to measure whether or not we're getting where we're supposed to go.
01:33So, it seems now in this age of incorporating artificial intelligence, there's a lot more that we can measure, a lot more that we can do.
01:41From where you sit, what do you see in terms of how AI can help get us to better outcomes?
01:50Yeah, it's been a really fun journey.
01:53We've been playing in that space for a long time.
01:55We spent a couple years building predictive AI into our tools so that we could start to, to your point, work towards outcomes.
02:04And today, every single one of my entertainment partners is playing in that space.
02:09When they need awareness or reach, we have a video tool that they can use that drives specifically that.
02:16If they need views, longer view time and more consideration, we have a tool that will drive specifically towards that.
02:23And if a studio needs to sell a movie ticket, we have a video tool that will focus specifically on hitting a video sale or a movie ticket sale.
02:33And that's been really wonderful, but kind of in the last year, we had a few partners testing in this space where we started deconstructing all of the traditional targeting parameters that we put on campaigns and just let the AI find the people that we wanted and let it go to town.
02:52And we've seen a lot of success with that to the point where it's an area that we're really focusing on in 2025.
02:58So, that's the predictive side.
02:59And then on the generative side, I'll give you, we built a toolkit called AI for marketing, and we're really trying to solve for some of the use cases we see most often in the marketing space.
03:14And I know Dom is going to talk about something really custom that they did, but I'll give you an example.
03:19I had a conversation with a CMO this week who said they had a show on a streaming platform.
03:25They thought that it wasn't living up to its potential.
03:28It was a better show.
03:29It wasn't getting the audience it wanted.
03:31So, they went into a large language model, and they pulled out, like, what are people saying about this show?
03:37And what should I know?
03:38That's really the chatter here.
03:39And what they found out was people that, it was kind of a professional genre show.
03:44The people that worked in that profession thought it was very realistic and very, very, one of the most realistic shows in that space they'd ever seen.
03:52So, they put a whole campaign around that and landed that press in the New York Times, and all of a sudden they really started to see the viewership tick up for that show.
04:02So, one of the ways Google will take that insight that we hear from someone is we'll put together something called TopicsMine, which allows us to understand all the insights we have from Google's search volume and match it to every single piece of IP in their catalog.
04:18So, that, you know, they're not going to go and look at everything that's going on within their catalog out in conversation today, but we can help identify trends and marketing moments that they can capitalize on across the entire portfolio.
04:31So, that's where things get really exciting for us.
04:33Wow. Okay. So, allowing people to better navigate these new environments where there's so much more that we can know and see, and being able to kind of harness that information and those insights in ways that allowed them to drill down, even though normally they'd have to boil the ocean in order to get those insights, right?
04:58Yeah, absolutely.
04:59All right. So, I'm going to pivot to Josh, if we're going to be on this topic. Josh, over at Disney Advertising.
05:05I was going to volunteer myself for this topic, too.
05:08Nice. Nice. Okay. So, then jump right in. I mean, your clients, partners, and your team are, again, massive environment with everything that's on streaming and all this other stuff that's happening with you.
05:23Similar questions. So, how does AI help you, as well as your partners, you know, ad sellers, et cetera, navigate this environment that's so noisy?
05:34I'll give some context here for a second, but I love the topic of outcomes, and I think it's exactly right.
05:40And a quote that my boss, Rita Farrow, says a lot is, advertising has gone from a world of one-to-many, think, you know, traditional linear advertising, to one-to-one, all of us see a slightly different ad based on who we are, to one-to outcomes, right?
05:56And the data models are there to actually get to a place that what a marketer is trying to achieve can be helped solve through not just all who we are, but the things that we're interested.
06:05Are we in market for a home loan? Are we planning a travel and vacation? Those things can start to come together.
06:12Now, whether it's Google or whether it's Disney, that has to happen at very large scale.
06:16I just happened to look at this yesterday.
06:18We have, at any given time, we have tens of thousands of campaigns running from advertisers.
06:24On any given week, there are four to five billion ad impressions running across Hulu, Disney+, and ESPN.
06:34Total or just yours?
06:36Just ours.
06:37Like, so that is what is happening every, and I get a report every single morning that shows hundreds of millions of commercial spots being delivered.
06:45Now, there's a couple of trends that are going on here.
06:47So, talking about a world that is going to outcomes, you want to be able to connect your outcome signals,
06:52which, historically, you're talking about last-click attribution, very deterministic kind of models,
06:58to getting into much more probabilistic, large data sets that you need to connect into planning teams.
07:03And these planning systems and also your measurement systems need to talk to each other.
07:08This is really easy to say, really hard to do, right?
07:11So, you've got to have really advanced technology stacks to do that.
07:14We have hundreds and hundreds of people in planning roles and account management roles.
07:19And I think over time, those people become analysts and data science on behalf of marketers,
07:24providing insights and recommendations, using ultimately kind of assistance,
07:30and then to help get to recommendations that kind of bring those things together.
07:34And that's in a world where, on any given month, we're seeing 50,000 pieces of ad creative come in.
07:39Marketers want to make more real-time decisions.
07:41We need to be able to process those creatives, and we're using AI today to actually look at those creatives,
07:47make sure they're up to the specs that they need to, make sure there aren't brand issues in that creative,
07:51and then flagging for teams of people what we might need to take an extra look at.
07:55So, I think you've got a convergence of a number of trends going on here that AI is just foundationally,
08:01I think, going to evolve what the selling and operating of advertising teams look like for marketers.
08:06Okay. So, tremendous volume.
08:13That's a lot.
08:15I want to pivot to Heika because now I'm also thinking about the social landscape.
08:23You know, Josh is talking about all these spots, all these impressions, right?
08:26But we don't exist in a monolithic media environment anymore.
08:30You know, people are spending increasingly plenty of time on their mobile devices on platforms that aren't necessarily kind of premium entertainment platforms.
08:41And it's a very noisy environment where there are a lot of different voices.
08:46Can you talk a little bit about how you can use AI to help folks cut through some of that noise?
08:52Yeah, thank you so much.
08:54And, you know, I'm a marketer through and through.
08:57I manage our content and social media and integrated marketing for Microsoft Advertising.
09:02And as such, I spend a lot of my time thinking about and studying trends in consumer behavior, social, all of these things that you mentioned.
09:10And what I am deeply struck by at this moment in time is just how quickly audience engagement is transforming
09:18and how fast that transformation is taking place.
09:21And at the heart of that transformation, one of the major ways we see that transforming at Microsoft is through CoPilot, which we see as the UI of AI.
09:32And it's still emerging.
09:33We're still growing.
09:34But how many have used Microsoft CoPilot?
09:36Yeah, many of you today.
09:38I know I use it a lot professionally and personally.
09:41I'll give you a couple examples.
09:43One, professionally.
09:45So last week I was on spring break, probably like many of you in the local school districts.
09:49And when I came back from vacation, I asked CoPilot right away to go through my Outlook and my Microsoft Teams and summarize anything urgent from my boss.
10:00And it took a second to do that and saved me a lot of time.
10:04That's really smart.
10:04Yes.
10:06Note to self.
10:07Yes.
10:08And in my personal life, as part of that spring break, I also went to Disneyland last week with my toddler.
10:14I'm next to Josh from Disney right now.
10:16And I had a lot of conversations with CoPilot, whether they were in the wee hours or in the early morning, whenever I had time as a busy mom, just asking, what are the best snacks for toddlers at Disneyland?
10:28What are the best rides?
10:29What's the height requirement for Space Mountain?
10:31All of these things.
10:32And just had this really rich, meaningful conversation on my own terms as a consumer.
10:38And so as marketers and as brands, I think this just opens up so many opportunities for engagement.
10:45You know, in CoPilot, we're already seeing that we're beginning to integrate sponsored and organic conversations within CoPilot and clearly delineating what is paid and what is organic, but really giving brands that chance to be part of those conversations.
11:00And so really seeing that the future of marketing is so conversational and so personal.
11:06I love that.
11:07And it just seems that right now, with all of the information that people have available, it's more about directing attention.
11:16Certainly, yeah.
11:17Okay.
11:18So, Dominic?
11:19Yes, sir?
11:20You had a long trip here, didn't you?
11:22Cross country.
11:23Yeah.
11:24Okay.
11:24No Wi-Fi?
11:26No Wi-Fi.
11:26First of all, thank you for being here.
11:30And also, you know, we've talked a little bit about the volume of information that's out there, the variety of entertainment platforms and choices.
11:41You also are deep up to your knees in the streaming economy.
11:46Can you talk a little bit more about how you use AI to drive the most value from new originals, blockbuster films, you know, live sports, et cetera?
11:58I mean, I think in general, we are trying to deploy AI at every sort of step of the campaign itself, all the way from development through execution.
12:07You know, think about things like helping our copywriters with copy for all the CRM messaging and social and things like that.
12:14You know, research, synthetic focus groups, those types of things.
12:18Also, our data team is also, you know, coming to the table with insights through their work.
12:23So, we're trying to put all that in up front and then working our way, you know, throughout the process, we're trying to find ways to be both more productive and more innovative.
12:32And on the innovative front, the example that Angie was talking about is we've been doing a lot with visual AI.
12:38And basically, we co-developed Google Sports AI Engine, I think it's called.
12:44And so, we trained models on football and soccer and then basically created custom creative that our teams, our video editors basically created with the AI tool, sort of made sure they were cool.
12:55And then we put them in trafficking in our lower funnel.
12:58Really fantastic, creative, looks really, really good.
13:01Our video editors will be able to create, you know, 3x the amount of creative volume, which is important because we talked about the predictive engines out there.
13:09Creative has kind of turned into the new targeting and something that we're doing.
13:13And then ultimately, going back to results, we delivered.
13:17Most recently, we did it for the Champions League quarterfinals and we delivered very attractive cost per acquisition for new signups.
13:23So, it's both working well creatively, it's helping with productivity, and then it's influencing business results.
13:28Okay.
13:29And that, what you just said made me think of Jen, this idea of using AI tools to help actually generate creative is going to lead to an explosion of brand messages all over the place.
13:45Jen, could you talk about how you can use AI to add some precision to some of that?
13:51Yeah, at Teads, you know, our positioning really is around being like an omni-channel outcomes platform for the open web.
14:00And a big piece of that is creative optimization, how we leverage AI and data from a creative optimization standpoint.
14:07And not from the sense of creating creative, again, but of amplifying our brand's creative to reach the right consumer in the right environment at the right time to understand more about their consumer journey across all of these very fragmented places where we're consuming content.
14:25And be able to connect that messaging in a really cohesive way that evokes something like, you know, we talk a lot about outcomes here, but outcomes across the funnel.
14:34So, it can be engagement, attention, right, and all the way down to conversions.
14:39And also, how do we tie those quality metrics like attention into conversion?
14:43So, that's a lot of what we're leveraging AI for from a predictive landscape.
14:48On the generative side of things, it's really we're still at the, like, infancy of kind of, like, how we're leveraging generative for creative.
14:56But, again, like, brand assets are very precious, and we want to make sure that they're working as hard as they can in the environments that are most appropriate to get the results and the outcomes that our partners want.
15:08Okay.
15:08All right.
15:09So, we've just given you, I think, between our panelists here, about 12 or 15 different potential use cases for marketers in ways that you can use AI to both generate content, direct content to the right place, and also measure outcomes, audience responses, et cetera.
15:33So, now I'm just going to start asking questions to the whole panel so that we can get into some of the hows and the what's and so on.
15:41First off, Dominic started it, so I'm going to stay on this topic.
15:46You talked about using AI to actually generate creative.
15:50For the panel, is that something that is happening in your teams?
15:56Is that something that you see as useful?
15:58Is that something that you've worked with partners on?
16:00Yeah, for sure.
16:01I mean, I think our creative teams have embraced AI tools.
16:05I think a good example of something we did last year that we were very proud of for the movie If, we worked with Adobe and Firefly and Gen Studio and basically did a social stunt where we had fans on social sort of give us what they would like to see as their if, their imaginary friend.
16:24And basically, we had a team of designers with six designers, two social media managers, and we took those inbound.
16:31We basically, the design team set a sort of a framework reference file and sort of design template for Firefly.
16:38We took what we heard from the fans on social, we sort of edited that to a prompt, we got an image back, and then basically from there, if necessary, we threw it in the Photoshop for tweaks, and then the social media managers posted it.
16:52And over the course of two hours, we were turning these out every two minutes basically, and it was incredible.
16:58And, you know, one fun, not fun, but more heartwarming example was somebody asked to see their dearly departed father as an owl.
17:06And so the team huddled on Slack, what was the best way to prompt the AI, and we came back with a sketch of an owl holding a heart, and the person loved it.
17:14And so that was, like, a really nice moment for us to create a brand connection, you know, with a fan through the project.
17:21And I would add on to that, like, we've seen a few folks test this, especially for a streamer, where you have, like, vast volumes of content in different genres.
17:31So we, I ran a test with someone recently that was, like, let's take your entire movie catalog, you're doing your end-of-year holiday campaign, and the creatives can just prompt it, like, find the ten best things that will be most likely, and they match, they train the model on some of their best subscription-driving assets.
17:50And then they let the AI go, the AI is still not taking away the creative's job.
17:56The part of the job that the AI is taking away is sifting through a volume of catalog content so that the creative can spend more time fine-touching and nuancing.
18:06And we think of it as, like, AI-informed creative or getting you 80% of the way there and throw all kinds of prompts in there.
18:13Do you want five movies in that?
18:15Do you want ten movies in that?
18:16So that's kind of the way that you can think about it.
18:19There's a bill there you're talking about.
18:21You heard me mention the volume of creative that we see today, roughly 50,000 creatives that we then use AI to look at what's happening.
18:28I'll give a real quick example.
18:29If a kid's not wearing a helmet in a commercial, we're not running it, right?
18:33So you can train the model to be able to do that.
18:36The other thing is we were talking earlier about, so there's a creative itself, and then who are you going to run it against?
18:42And I love Dominic's background, and he's also ran the data practice, right?
18:46So he has a data background, he has a finance background, and he has a creative background.
18:50And on the data background, to figure out who you're looking to target, I'll give an example where you take an advertiser's first-party data set.
18:58You combine it with Disney Advertising's first-party data set.
19:01You do that in a privacy-compliant way in a clean room.
19:03You identify the most valuable people to target, and then you go ask the model to go find more people like that.
19:10And then you A-B test that against the advertiser's data, which they can run by themselves, and what the AI and ML models came back with.
19:18They find more people.
19:20They find performance that's totally in line with the first-party audience segments.
19:25And that was a new concept probably two years ago or so.
19:27That's where many of the conversations that we're having right now is how do you take the data models, apply those with lots more creative to different audiences, and then you go test those things.
19:38And then you need to be able to move really quickly and respond.
19:41I love the example of going right to Slack and being able to respond to something in real time.
19:46The speed at which modern marketing works at takes all those skill sets, right?
19:50And so it's great to see when those things are all kind of coming together.
19:54I just love that you brought up the brand safety component about the helmet.
19:58Like, it's true across all of that.
20:00Like, anyone who's working in publishing today, AI is a critical component of how we navigate the content that's getting uploaded and that's appropriate for our audiences and also the ads.
20:10I have some horror marketers in this room today who are very disappointed about the AI's ability to screen through things that we don't think are appropriate in an ad content.
20:18But it's huge in the way that we manage the volume of content coming at us.
20:24One other nod.
20:25So we do this for the commercials that are coming in, but we also do this at a scene level for our content library.
20:32So think about every scene for every show, every movie, every sports watch.
20:36There's metadata.
20:37This isn't a new concept here of what images, what sounds, what's moving.
20:42That can all be tagged, right?
20:43So that's been around for a while.
20:45But what hasn't been around for a while is connect that information into the commercial you see next.
20:51So when you're watching a show like The Bear on Hulu, okay, it's based on restaurants and it's a comedy slash drama.
20:58Well, that's great.
20:59And some advertisers want to be around that with contextual advertising that is addressable.
21:03Well, the next step of that is what's happening at an individual scene.
21:06Are they actually in the kitchen?
21:08Are there appliances in there?
21:09What's the mood or tone that's happening in that?
21:11And what's the next commercial spot you see at the next break and does it match to that?
21:16So that, it's connecting a concept of metadata to actually surface advertising that matters most.
21:23That couldn't be done a couple years ago until you had these large models that can actually look at this and that you can make sense of and serve advertising against.
21:31Again, to the tune of ultimately this will get to how most advertising is delivered.
21:35It's going to take some time, but the concepts are there.
21:37Yeah, and that personalization at scale I think is incredibly interesting because as you're extracting all of those data points and you're able to understand the user's behavior,
21:47you're also able to understand maybe moments where they're less receptive and how do I bring them back in.
21:53And so as a, you know, not you're in the sales side of things, but as the publisher of content, how do you keep them engaged in your content?
21:59And leveraging AI and all of those intense signals to keep them engaged in really customized and personalized ways, I think is growing more than ever before.
22:08So that's stuff I'm really interested in.
22:11No, I mean, I couldn't agree more just in terms of the personalization.
22:14And to your metadata point, one of the things we're doing on the data side is using AI tools to basically hydrate our metadata,
22:19which then has many use cases downstream, both, you know, from creative and aiding visual search AI to, you know,
22:28basically our personalization engines and then also sort of, you know, overall creating, you know,
22:33new sort of marketing assets by basically understanding more detail around every scene and every piece of content,
22:39whether it's at a franchise level or genre level,
22:41and then being able to use that quickly to sort of accumulate options for your creative team to then construct, you know,
22:48a trailer or any other piece of creative,
22:51but really assisted in that sort of search process to find the best, you know,
22:56scenes and the light to use in the process.
22:58And even thinking of speed to market with things too.
23:01So being able to like,
23:02if you have an asset pack that's based on something really culturally relevant that's happening in real time,
23:07to be able to leverage AI and kind of intense signals to, you know,
23:12optimize those based on like what those signals are and be able to, again,
23:16like be able to distribute those in contextual environments to react in real time is,
23:21it's stronger than ever before.
23:23So Jen, you just gave a great example of a use case,
23:30but all of the examples I just heard you all mention seem new and fresh.
23:37And one of the biggest challenges, I think,
23:39especially for marketers who aren't yet using any of these tools is how to integrate them into a workflow, right?
23:47Because you already have existing workflows for everything that you typically do.
23:51And now you see these opportunities,
23:52but how do you actually harness them with, you know,
23:56products that you haven't even incorporated into the organization?
24:00So could you talk a little bit about that,
24:02either how you do it or how you help others do it?
24:07I mean, for us, we're,
24:08the first thing is just trying to get people to understand what tools are available to them.
24:12We just, I've did a whole round of,
24:14no, don't make it sound bigger than it was,
24:16but like survey work with my, with our team,
24:18our data and marketing organization,
24:19try to understand what people,
24:20how people are using AI sort of, you know,
24:22the why, the how's and the why's and the why's not.
24:25And one of the things we found was already over a third of the team was using AI
24:29in their professional work.
24:31But another 25% of the team was using AI personally,
24:35but they hadn't yet migrated it to their professional work.
24:37And the biggest reason that they cited was a lack of awareness, right?
24:41So the company,
24:41we've done a lot of good jobs,
24:43a lot of good work in terms of driving pilots,
24:46working with our tech and our legal teams to unlock enterprise access to certain things
24:51like copilot,
24:52like chat GPT.
24:54But we're still in the process of making sure it's getting into people's hands,
24:57that they know it's available,
24:59how they may use it.
25:00And then I think the use cases will sort of start to accelerate from there.
25:05Do you want to go ahead?
25:06Go ahead.
25:06No, yeah, thank you.
25:07I, yeah,
25:08I think it's just allowing it to be an educational iterative process and also inspiring people
25:15with the vision that using generative AI doesn't have to be this feeding frenzy.
25:20It can actually lead to a place of greater calm and bringing clarity out of chaos.
25:25I think all of us as marketers are in this kind of do more with less.
25:29We've got to be scrappy kind of boat, you know,
25:32regardless of where exactly you sit in the organization.
25:35And where I found a lot of success integrating these types of tools into my team's workflows
25:39and the functional areas that I manage is just incentivizing people around that innovation.
25:45You know,
25:45we have a spotlight in some of our team meetings where people bring their co-pilot prompt of the week
25:50and they share that with others.
25:52You can copy and paste it from the team chat and just show it to others.
25:56It can be something fun.
25:57It can be recipes or travel tips or whatever it is.
25:59But then I also think inspiring people with that idea of bringing that calm.
26:05You know,
26:05when we talk about generative AI,
26:07let's be honest,
26:08there could be an environment of fear,
26:10of, you know,
26:10anxiety.
26:11What kind of changes is this going to bring?
26:14But I believe that once more teams begin to actually implement these technologies
26:18and they see greater productivity and creative gains,
26:22better performance results and impact,
26:24this will ultimately a few years from now actually lead to a lot more calm on our teams
26:30and we'll actually be in a much better place with regards to productivity and efficiency.
26:35Yeah,
26:35I was going to add to that.
26:36And the way that I really started to integrate AI more into my everyday was a bunch of our like account managers,
26:44the like 28 to 32 year olds on our team,
26:47put together their own task force and started giving the entire entertainment team presentations
26:52on how they were using AI.
26:54So like helping us understand where trailers were working and not working for our clients
26:59and really just getting people who are interested in it together and giving them a place to talk to your organization
27:05was like tremendous help for me and the whole team that we work with.
27:08And I think the first place to adopt it is with the leaders as well because I do think we have to demystify it a little bit, right?
27:15Like it's sat for, I've been with TEEDS for six years and our engineering team always talked about it.
27:19It's like, oh yeah, AI, cool, like predictive technology.
27:22But, you know, I think like it's become so commonplace and maybe we've used it to like rewrite emails or things like that.
27:29But I do think like this panel helped me prepare a lot.
27:33And I did listen to a few podcasts that were really interesting about how when leaders adopt it and start iterating on it
27:40and like really open up what they've learned with it to their teams, it helps inspire everybody.
27:45Because even similar in our culture, like I do think some of the younger folks have come to us with really creative ideas
27:51around even sales contests and things like that of a leveraged AI.
27:54But I'm like, I need to adopt it in my every day and I need a sticky note that tells me to adopt this in certain ways
28:00that help me stick to the strategy and find more efficiency.
28:04And then I can bring those to the team.
28:06So I do think it starts with us.
28:08I almost think like there's AI at a product level, at a very large systems level,
28:13and that's what I've talked about so far.
28:14This conversation is how do you use it as functional teams?
28:18And yes, and to everything that's been said so far.
28:21I have an account management team of several hundred account managers, a planning team of several hundred.
28:27It's exactly right, both demographically, who's natural to use things.
28:30And you just create a culture of, hey, we have these enterprise agreements.
28:34Go use these tools and tell us what you learned.
28:36And let's create the space and time to have those conversations.
28:40And then I completely agree with the point as leaders.
28:42Our best work is always done with others.
28:45It's almost never done alone.
28:46And imagine you have a third or fourth seat at the table for an AI assistant to work with you.
28:53We're doing a lot of market analysis.
28:55We're doing a lot of comparison.
28:56We can ask a lot of questions.
28:58And before walking into this room, I had a conversation with someone who was talking about
29:02how it helps him go from a blank white page to get something down.
29:06And then he starts asking the AI what questions should he be asking himself and make sure he can answer those questions.
29:13So, you know, and I'm just seeing the reaction, right?
29:15I think having these conversations, whether it's what prompts are you using, how are you using it as a virtual team member
29:21and an assistant that is truly additive and organic in the process and give it time and space to breathe,
29:26and then embrace your large teams to say, hey, go use these things and tell us what you learned.
29:32And it's kind of that is a very different use case in my mind than what it means at a systems level of, you know,
29:39creation, ad review, ad decisioning at the billions.
29:42Those are like enterprise use cases that have long cycles and you've got to, you know,
29:47that's a different thing than doing as a virtual teams.
29:49But those things happening together just creates this kind of snowball where it becomes part of your culture
29:55and going back to the adoption part.
29:57Yeah, and I think you probably all see this as well, but the more we have people evangelizing and sharing their work,
30:02it's inspiring other teams and team members.
30:04So it does sort of like snowball in a good way in terms of like driving that adoption
30:09and more use cases we hadn't thought of yet.
30:11It's pretty cool to see.
30:13So you talked about AI as your partner,
30:16but I know that thanks wherever Suzanne is,
30:20I've been blessed enough to have presenters here who represent the whole food chain
30:25when it comes to entertainment marketing.
30:27Maybe a couple of you could talk about examples of collaboration
30:30where you've been able to use AI in partnership with another organization
30:35to get to a successful outcome for a brand.
30:39I kind of gave mine already.
30:43Yeah, I'll defer.
30:44Yeah, I think, well, often at YouTube, people come to us and say,
30:51what was working about our trailer?
30:53What should we do differently?
30:54And so like just the easiest thing we can do is say,
30:57well, we have this ABC playbook of how to create content in the entertainment space.
31:02We can pop that into Gemini and pop in the YouTube URL of their trailer
31:06and get really good insights for them about what was working and what wasn't working
31:11in a way that like we don't have to generally, you know,
31:15we could maybe get creative feedback from somebody somewhere,
31:18but it's going to take a couple of days.
31:20If they need that right now for a creative meeting they have in a couple of hours,
31:23we can turn that around in seconds.
31:24And it takes so much pressure off of our teams who are like basically hands on keyboard
31:29trying to make campaigns work.
31:30They're not creative geniuses,
31:32but they can get an answer to a client in the time that they need.
31:35And so we see that as, you know,
31:38helping fill some of the gaps of our competencies in a quick, easy way.
31:42If we have all the information,
31:45we could pump it all into the tool and let the tool do the analysis for us.
31:48Yeah. And right now I think I've been really inspired to see just how the search journey
31:56is evolving and how that is having really measurable outcomes for brands that we work with.
32:02You know, I've, I've read a lot of people on LinkedIn opining that SEO is dead
32:07or something along those lines.
32:09Search is definitely not dead.
32:10The search journey is certainly evolving.
32:12And if I think about it, you know, a few years ago, even as a consumer,
32:16if I were searching for a topic, maybe it's a busy weeknight.
32:19I'm thinking about what show should I watch right now?
32:21I have no idea what to watch and maybe I,
32:23Powerpuff Girls, but go ahead.
32:25Maybe I, maybe I open up a tab and Bing,
32:29and I try to search for shows to watch.
32:30And suddenly I've got all these different open tabs, 50 open tabs.
32:34You know, I've got Instagram notifications pinging me.
32:36It's very overwhelming.
32:37It's the splinter net.
32:38Whereas now, you know,
32:39thinking about that co-pilot UI and how it's all streamlined in one conversation,
32:43those results, that search journey, you know, you could simply ask,
32:47hey, what shows, knowing what you know about me, co-pilot,
32:50what shows would you recommend to me?
32:51How long are the episodes?
32:53Because I only have 25 minutes before I need to go to bed
32:56and just have that rich conversation.
32:58And what we are seeing in terms of those outcomes
33:00is that the ad relevance is rated way higher by users
33:04of that type of streamlined sponsored content experience
33:06and that the click-through is about two times higher.
33:09So really seeing those results.
33:10And on the publisher side, I would say just to that use case,
33:14our SEO team is working really hard to basically help us improve our ability
33:20to sort of show up in the best way in the sort of AI-driven search results
33:24because it's not the sort of typical SEO optimization that you've seen in the past.
33:28And we're really trying to think that through in terms of how do we show up best,
33:31what do we need to do, not just in our site structures
33:33and those types of things that get crawled,
33:35but also around additional editorial, you know,
33:37those types of things that we can help those AI search engines
33:41be able to yield better results
33:43and then hopefully, you know, a good outcome
33:45where they find a show that they love to watch with us.
33:47And a much better consumer experience in that way.
33:50Yeah, I think that's like quality is a big piece, I think,
33:53that we're tapping into there
33:54because in the media landscape, it's very gamified, right?
33:58Like we're all driving to media KPIs,
34:00but I think if we start thinking about how AI can correlate quality metrics
34:04into actual business outcomes and leverage those
34:07to actually have brands connect with consumers
34:10in these quality environments in a different way
34:12that will transform how brands and consumers are connected.
34:16And I think that's a way where you are.
34:19I'll just do a quick build on Angie,
34:21your point about insights and how the speed at which you can get insights.
34:25So it was preparing for this.
34:28So Disney has an audience graph.
34:29That audience graph has hundreds of millions of different identifiers that go in,
34:33and we can see over 100 million households in the U.S.
34:36And what you can see and kind of pull from there is some insights is,
34:39did you know that college football fans also really love Halloween
34:44and also really love chocolate candy?
34:47And so that kind of insight came out of an ML model
34:50on top of that audience graph.
34:52That happens hundreds of times a week
34:55as we're preparing for conversations with marketers
34:57because insights are only as good as who you're providing them to.
35:01If we're having a conversation, I need to talk about your business.
35:04What matters to you?
35:05And so there's a lot of people who are in the chocolate business
35:08who would like to know that there's a good audience there
35:10around college football and around Halloween time
35:12and how do you put those things together.
35:13So I think that type of thing can happen now
35:16at a much different scale and speed
35:18than even just a couple years ago.
35:20How quickly you can get to those insights,
35:22and then you can build audiences around those.
35:24Then you can test those things, and then you can react quickly.
35:26That cycle has sped up so quickly to where years ago
35:30that would have taken several weeks,
35:32you would have teams doing research,
35:34and now you've got a partner to go help get those insights
35:36and then make them actionable.
35:38I love that.
35:39I know we only have about a minute left,
35:41and I don't want to stand between or sit between you and lunch,
35:44but I would love for you all to share any resources
35:49that you think these folks should try
35:51if they're thinking about learning more about using AI
35:55to improve their marketing outcomes.
35:58My team recently put together some original research
36:01on this very topic.
36:03It's called The Marketer's Guide to Chatbots and Agents.
36:06Search for it or just find me on LinkedIn.
36:10Well, okay.
36:11So all I really do is I just try to upload stuff in there.
36:15I drop things in.
36:16I ask it questions.
36:17It does everything for me from personal therapy too.
36:19But you just kind of try.
36:22You just kind of put yourself out there
36:23and see what it gives you back,
36:25and the more you test it
36:26and the more you understand how it works,
36:28you start to get better and better results.
36:30Yeah.
36:31I mean, I feel the same way.
36:32Just get using it,
36:33and then also I guess you could query ChatGPT
36:37or other tools to say what are the best resources,
36:40but in general I think getting your hands on it
36:42and really starting to understand sort of the potential
36:44is the best thing to do.
36:46Yeah, I think the application is key,
36:48and I think where I've been inspired, like I said,
36:50is through listening to podcasts
36:51about how different marketers and brands are leveraging AI.
36:55I think it gets me to think outside the box
36:57of what is like the traditional,
36:58what I see in my own ecosystem.
37:01My nine-year-old daughter.
37:03So my nine-year-old daughter uses Canva
37:06and Canva Plus tools to create presentations
37:09that would knock your socks off,
37:11and those are all AI-assisted prompts that she's used.
37:14She created an entire presentation
37:17with the level of depth and multimedia that's there.
37:21She convinced her whole family to get cats.
37:23My father's allergic to cats.
37:25We now have two cats.
37:26So I think watch kids.
37:29Watch what kids are doing
37:30and see how they naturally are learning this stuff.
37:33It's pretty amazing to see what they're doing
37:36and what's possible.
37:37I love this.
37:38So my two takeaways between the kind of the team
37:42of young people over at Google,
37:45you're a nine-year-old.
37:47One is watch these young folks
37:49and the intergenerational learning that can happen,
37:52and then Angie said it best with,
37:54you just got to try.
37:55So thank you, all of you,
37:57for sharing your insights and your wisdom.