Unlock the power of agentic AI across Adobe CX Enterprise

Transcript

We’re just going to give everyone a few minutes to get started.

Then we’ll get started.

Just give everyone a couple more minutes to get from their next meeting and we will get started here in a second.

Do you want to roll the video to get started? We think that delivering a relevant experience shouldn’t be a marathon. It should be a conversation. Introducing Adobe Agent Orchestrator, your single pane of glass for customer experience orchestration. Please help me plan a My Card campaign. Use last year’s campaign performance as the baseline. I’d like to target existing customers eligible for credit cards. Please make sure the audience is at least 10,000 people. I’d like to test two new message variants for this campaign geared towards getting credit card signups. Summarize results for me after a month and suggest improvements.

By leveraging multiple agents in a single prompt, you can begin creating your campaign. Enter a prompt and the reasoning engine plans the workflow, assigns the right agents to execute and keeps you updated every step of the way. It all starts with Data Insights Agent instantly retrieving historical performance, giving you a baseline grounded in behavioral truth.

Next, to define your reach, Audience Agent curates high value segments in seconds, ensuring your message finds the right eyes.

To orchestrate, Journey Agent designs an end-to-end flow that reflects who customers are and how they want to be engaged. And to ensure impact, Experimentation Agent validates your creative, optimizing every variant for maximum conversion. When Data-Driven Insights meet human expertise, every step is connected and every outcome is intentional. One seamless journey from idea to impact. This is unified customer experience. What used to take weeks of manual orchestration now happens in a fraction of the time and can be adapted in real time based on how customers are engaging, meaning you spend less time managing execution and more time driving performance across every KPI that matters. Connect with your customers like never before.

Thank you, Vidya. Thanks for sharing that. Hi, everyone. And thanks so much for joining us today for our webinar on how to unlock the power of Agintic AI with Adobe. I’m Betsy Lewis and I lead our Success Advisory team across Asia Pacific and we’re part of the Ultimate Success business. And our team partners closely with many of you on the call to really focus on how you’re getting the most value out of your Adobe solutions over time. Today’s the first session in what we’re calling our Adobe AI Webinar Series brought to you by the Ultimate Success team. And the goal of this series is pretty simple. We know that there’s a huge momentum right now around AI, particularly around agintic capabilities, what they are, how they work, and importantly, what they actually mean for your teams day to day. So rather than trying to cover everything in a single session, we’ve designed this as a series to give you a solid baseline understanding of what’s available for you today. The intent is that by the end of this series, you’re not just more familiar with the features, but you have clarity on how you can start to apply them within your own organization. And basically how the Ultimate Success team can help take you further and scale that. So if you want to pop back quickly to the agenda video, I’ll run through the agenda and what we’re going to cover. We’ll start with a bit of context setting on what AI is and where we’re seeing the biggest opportunities across our customers. And from there, video will walk you through some of the key agintic capabilities within Adobe and what they do and how they’re going to start to be used in practice. And then we’ll head over to Paul and he will bring that to life with more practical examples and perspectives on how the teams are rolling that out across their organizations.

If you go to the next slide, as I mentioned, this is the first of a series of webinars that the team has put together to focus on the agintic capabilities within the Adobe tech stack. And as you can see, this will start to build out today’s more of a foundational baseline to get everybody on the same page. And then from there, we’ll go deeper in upcoming sessions focusing on specific use cases, how to operationalize these capabilities and what it looks like to embed them into your workflows at scale.

So think of this as a series as a starting point of the broader journey rather than a standalone session. So we hope that you are able to join us for all of the sessions that are relevant for you and your roles.

With that, I’m excited to introduce our speakers for today. So if you go to the next slide today, we’re joined by Vidya Sivakumar, who leads our AI practice as part of the Success Advisory team across APAC and is one of our principal field engineers. She has deep expertise in real time CDP, AJO, Campaign, and Pawan Gupta is another principal field engineer on the team as well. And he brings deep expertise on all things AEM and how these AI capabilities are being applied across customers. If you have questions during the session, feel free to put them into the chat pod on the top of the screen. And just wanted to note as well that this session is being recorded and the recording and the slides will be shared after the event. So with that, I’ll hand it over to you Vidya to get us kicked off.

Thank you Betsy. Hello everyone.

Alright, welcome again.

So just quickly drop a hello in the chat and tell us which city where you’re joining us from.

So from the registration, I see that we’ve got a couple of airlines, financial services, and travel brands across Australia and India joining us today. So I’m sure that it’s going to be a lively session. So I’m Vidya and I have Pawan here with me today as well. So the next hour we’re going to unpack exactly what you just saw in the video and what Betsy mentions. So what Adobe AI is all about, how it works, and how close are we to reality from that video that we saw and how relevant it is for your industry right now. So let’s get into it. So to start with, from the screen you’re seeing here, what’s actually happening out there is customer expectations have moved rapidly and it’s evolving at a really rapid pace.

People have experienced what seamless personalized interactions feels like, whether that’s maybe from their bank, their streaming services, or their retail kiosks or shops. And now that they have seen what it feels like, they expect the same from every brand, every touch point, everywhere they interact. So the bar has been set high. So relevance, in other words, what we call personalization, going back, is no longer by itself is a differentiator. So it’s an absolute baseline, yes, for sure, but it’s not a differentiator. So think about something as simple as taking an airline example here. A customer is researching or looking for a flight and they browse it on the website, they start on the website, they start the journey on the website.

And that signal, the intent has been captured and they get a personalized offer on that particular destination path on their mobile phone or mobile application. And they take that and they book the flight through the app. So to them, to the customer, that looks like one seamless experience.

But internally for that airlines, that journey just crossed the website team, the marketing team, and probably the pricing engine, and as well as the CRM. And it’s not uncommon to see that the content could be fragmented across all of these systems. The inconsistent messaging and systems usually don’t really talk or sync very well with each other. So on top of this, what’s happening is there’s this explosion of content demand. So you are required to create more variations, more channels, and at a greater speed at the same time. And all of that with the same number of team and resources you already have right now. So even if you get these two right, even if you get the experiences right, if the brand is not showing up in the moments where your customers are actually looking, so in case like in your AI searches or in social third-party interfaces, so that experience that you have built will never even get a chance to matter. So all of these three things together, which is the rising expectation, exploring content demand, and fragmented discovery, all of this is shaping and basically reshaping how companies are growing in the digital marketing world. So like I said, relevance or personalization is the baseline, but experience is going to be the differentiator for the digital marketing world going forward. And that’s exactly what we are going to tackle today and see how we achieve that experience altogether. So before we dive in there, let’s have a quick pulse check. So how mature is your organization in adopting AI for digital experience? Let us know. Let us hear where do you think you really are today.

All right. I can’t really see the poll, but I’m guessing that there’s quite a bit of a spread.

And that’s exactly what we see across the regions as well. So where you are at, it doesn’t really matter. Today, the session is tailored in such a way that it actually should make sense and it should be your focus as well.

So talking about all of those challenges, so we just saw the scale of challenges as we, you know, customer demanding, personalization, content volumes, exploding and the organic traffic to your websites, which is declining. So the question is, what is a modern solution that could actually look like for all of these problems or the challenges that we see? And this is where Adobe’s answer comes in. So we are calling it customer experience orchestration, CXO. So CXO is all about bringing together the creativity, marketing and agentic AI to deliver personalized experiences in real time and at global scale. So everything we cover today sits under this umbrella. So think of this as the destination and the rest of this session is kind of like, you know, we go towards this how to achieving that CXO. So at the base of it is what we have, enterprise architecture. Now, let’s have a quick look at what that architecture evolution looks like for the enterprises in this evolution.

So we saw the CXO. The CXO is built on these layers. So basically we have four here, starting with data.

You have your data. You have been collecting it for decades. And that’s a no brainer right there. And models on top of it, which is models like the AI models, you’re using it to predict things like churn propensity, next best offer, conversions and so on. So right now, that’s where most of the organizations are today. That’s where they’re comfortable in using the AI up to. Not generalizing, but it’s the most, you know, where we see our art. And the shift really happens at agent orchestration layer. So here what’s happening is instead of a human looking at those predictions and the data and deciding what to do with that, the orchestrator actually is picking up and it’s reasoning with that data, plans and acts on that data automatically. And while the while coordinating with multiple agents, which is available across simultaneously. And then at the top sits the apps and interfaces. So this is where, you know, your customers actually experiences it all. So your app, your website, and also now the net new AI native surfaces.

So customers are increasingly kind of like starting their journey from chat GPTs, co-pilot, public cities. So these are the new front doors for every brand. And if you as an organization or a brand is not showing up here, then your experiences or you’re not even in the conversation. So the difference with all of the underneath all of this, the difference that Adobe is making is the AI is not just bolted to the side. It’s not sitting on top or at the side, but it’s embedded directly into the platform inside the workflows where your teams are already working in. So that’s the architecture shift that we’re kind of like seeing in our Adobe CXO has been built upon. Now, let’s break it down and see how it gets split into this delivery outcomes within CXO. So we have categories in three pillars, customer engagement, content supply chain and brand visibility. So each one of this is addressing a different part of the challenge that we just talked about when we opened. So we have the ability to create a new experience, content at scale and being discoverable in a fragmented world. So what ties all of them together is Adobe’s AI platform, which is the foundation or the underneath, the powering it all. And Adobe AI platform is one of the comprehensive agentic foundation for content, customer intelligence and brand discoverability. So let’s take a look at each of this pillar in a little bit detail and get the core of it to start.

So starting with the customer engagements, so every organization here today, you know, you might be doing personalization to some degree. So we can all confidently say that the gap is definitely not very much on the data or the customer intent, but mostly, most likely the execution at the speed and the scale that we want and our customers are expecting. So all of these solutions that we are seeing, they’re available right now. Adobe Experience Platform, Journey Optimizer, Experimentation Accelerator, Brand Concierge. And on top of all of that is Adobe Experience Platform agents. All of this is connected. So if you have to take an example and see how it works and the capabilities across these applications that we have, the AI capabilities. So let’s take this example on the right side of the slide. Right. So someone is just asking the AI assistant which segment drove the highest conversion lift this quarter. So instantly you get the insights. There’s no cross-team dependency, no waiting, no data pool that you need to wait for to get that insights. And the same insight, it flows straight into the audience activation within RT-CDP. The right segment, right there, ready to go. And then the end result, that goal member gets a personalized offer at 3.15 p.m., probably being identified using our Send Time Optimization within Journey Optimizer on their phone when they are likely to click on that or interact with your message. So one seamless motion from insight to audience to experience. And that’s what it looks like when customer engagement is working.

And now let’s look at the content supply chain.

So now with the CSP pillar, it’s all about more channels, more markets and more personalization, achieving all of this. And for the most teams, you can all say right now the bottleneck is not about coming up with the ideas for the creative. It’s more about getting things out the door. So especially like, you know, if you’re thinking about talking about regulated industries, financial services, airlines, you name it, almost every industry, every asset has a compliance, legal and brand approval that is sitting in the middle of the whole process. So and that’s not going to go away either. So but the time it takes doesn’t have to be what it is today. So that’s where Adobe’s content supply chain connects the entire flow. Creation, governance, activation, approval, all of it together with AI doing the heavy lifting on all of the variations and compliance checks before any of that reaches a human reviewer. So the solutions which are at play here are Gen Studio, Firefly, Creative Cloud and Adobe Experience Manager agents. All of this are working together. So teams like yours spend less time in chasing approvals and more time on the work that actually matters. Again, if you quickly look at the content supply chain capabilities here again with the example, somebody is prompting, hey, create assets for the top three performing segments across carousel, email and social. And it produces a social post, a banner ad and an content design fragment ready for email, which is channel ready, campaign ready and on brand. That’s planning, creation, brand governance and activation all in one motion. There is no briefing chain, no variation chaos, no waiting. And again, that’s again the content supply chain working at its best. And the third pillar is brand visibility. So Pavani here is going to go in detail on this pillar, but at the high level, this is a challenge that is quite new for most enterprises now. Brand visibility is about being found and trusted in the moment that matters. So customers don’t discover your brands in one place anymore. They search, scroll, ask questions and increasingly are relying on AI driven interfaces to help them decide what’s the best thing for them. So if your brand is not showing up or visible and accurate and consistent across in those moments, the experience breaks even before it could land. So think about a customer researching a credit card. They compare it interest rates on a search engine, ask a question on the AI assistant and then land on your product page. So brand visibility is about ensuring what they see is consistent and trustworthy at every step, not at the end of the funnel, not just one final page. So the product that is making all of this possible or happen are going to be LLM optimizer, AEM site optimizer and our brand concierge. And here’s what it looks like in practice. Again, it helps you with your optimize for both traditional and regenerative engine optimization.

And it turns passive browsing into guided personalized interactions and website modernization for AI discovery and performance and also helps with paid media optimization across AI power channels and a lot more. So we can have a deeper dive on this when we have a demo on the LLMOS.

All right. So now that we have seen the big picture and understand that the foundation for Adobe is driving, which is CXO and the three pillars, the architecture. Now, let’s kind of like have a look at the core of the engine, which is kind of like covering all of this and have a quick look at how AI has evolved and where it’s heading and what it means to your teams.

So if you look back, right, every major technology shift has redefined what customer experience means and looks like. So to start with, the Internet basically connected customers. The mobile made the experiences personal and social channels actually put customers in conversation. They gave it a voice. And now we have entered the AI era, which is where the creativity, marketing and intelligence is fusing into these experiences that are connected, contextual and continuously learning. So each wave, if you really see into a look into it, has created a new competitive edge for those who are willing to adopt and new set of challenges for those who don’t. So we are in that moment of change. So and AI itself has evolved in multiple ways throughout the time.

So if we look at the AI evolution itself, not all of the AI is same here. There are three distinct types and they do all different jobs here, starting with predictive AI. This is the oldest of the three, trained on your historical data, tells you what’s likely to happen, like John’s course, propensity models, next best action. It’s reactive to your data. And then comes the generative AI. This is the chat chippity moment, the assistant moment. So you prompt it, it responds. Great for productivity, content creation, summarization, but it still waits to be asked. It’s reactive. And agentic AI, this is the new frontier. So it doesn’t wait. It understands your goals, breaks it into the steps and acts across your systems autonomously. It’s the difference between a tool and a coworker. So each one builds on the last and the most powerful setups, as we call, uses all three of these together.

So this is the basic distinction across what, how AI has evolved and where we are today. You must be wondering what this means to our team. So if you like, this slide actually explains it in really nice three points. So this is about replacing people. Humans, we should be looking forward to shifting our focus as humans into strategic thinking, creative and ethical oversight. That’s something that, you know, is we cannot siphon off to AI or AI can’t do. And teams can expand with specialist agents on the pre-existing repetitive work. Think of it as your teams getting more capacity and not fewer people to do the work. So and the way brands also change how they engage with their customers, customers and also how it improves. So as a result of all of this, it’s driving better business outcomes as well. So AI takes the repetitive and human takes the strategic work. That’s a partnership we should be looking at. And that’s the approach we should take with AI.

OK, so now let’s get into the platform that kind of like makes this all happen.

So, Agent Orchestrator, Adobe Experience Platform Agent Orchestrator. This is what coordinates and runs all of the Adobe AI agent across our experience cloud. This is the starting point for any of our agents to be called upon. So let’s look at what it covers, right? So now this is the full map of what Adobe Experience Platform Agents covers across the customer experience lifecycle. And what I want to notice here is like these agents are not just general purpose assistants. Each one is purpose built for a specific job. So if you’re looking at starting with workflow optimization, audience management, content production, journey orchestration, site optimization, data insights, so on.

So the common theme across all of them is execution. We are focusing on execution. We have the data and then the agents have to take you to the next step. So they’re designed to move work forward inside that live experience workflows that you’re already working on. So it always works alongside your humans. It’s not, you know, there is always a human in the loop for any work that gets done across these agents. We’ll have a look at that in a minute as well, but because of the demos and these are not coming soon. This is already out there. And a lot of global brands are already seeing those results. So talking about the global brands and the results, you know, if you have to pick up one or two here. So AAA Northwest, Northeast have seen about three times membership conversion and about 30 percent faster campaign and record growth in the past seven years. So and then you talk about RMIT, which is our own here within Australian region. So 23 percent of conversion rate on a single AI powered targeted banner and Cisco for the customers here with the B2B licensing and features. So B2B AI agents have accelerated deal closures and have cut the time to identify those key decision makers. And all of this is basically showing the real organizations, how they are leveraging and deploying them to see the value. So now. Before we, you know, to deploy this, like, you know, we need to be able to be confident to be able to use that. So we’ll have a quick look at that. But before that, I want to again ask you all which Adobe AI capabilities are you currently using? 20 seconds to respond.

I’m hoping at least there were a couple of choices there and nobody has picked up none.

But doesn’t matter. Even if you’re not using any of them yet, you have come to the right place and definitely no pressure.

So we are quickly jumping onto the demos. But just before before that is one more thing that we need, which is, of course, all of the, you know, enterprises, if you are going to deploy.

Can we trust? How do we trust AI and be able to deploy at enterprise level? How do we trust that with our data? And that’s where Adobe has built all of these tools and capabilities with trust as the foundation. So, you know, for those of you in financial services and aviation, almost everyone, you already know that governance isn’t optional. So Adobe has built this in from the ground up. So all of our AI capabilities are responsible, explainable, human centered and enterprise secure. And it’s not an afterthought, but it has been built as a foundation because none of this works at scale in a regulated environment, which is most of us here without all of these factors considered. All right. So this is all we had. And I have demo right now on customer engagement pillar that we saw. So let’s quickly jump on there. But before I do that, quick check to the teams. How are we going? All right. So to the demo.

So if you have access to Adobe Experience platform and AI system, this is what something you would land on. This is the home screen looks like. So as you’re seeing, you don’t have to go to any of the solutions as such, not AJA or CJA, just the main screen home page and you land at this experience platform AI assistant. So I’m taking the role of a marketing specialist and I’m working for a company called Luma. I know if any of you have attended any of our Adobe sales sessions, this is one of our favorite brand, fictitious brand, Luma. So we are using that today as well. So let’s say I’m planning a new campaign for yoga apparel and I want to highlight some of my products that customers may not have bought yet. So let’s start with how AI assistant can help me build a personalized promotion campaign.

But before I get started, let’s analyze some data. You know, that’s where we got to start. So I asked the AI assistant, show me the revenue by product subcategory for yoga apparel in October. And I want the top 20. Let’s start there.

Some time. And then as you see, it has quickly pulled the right information from customer journey analytics to show me the purchase information of my top products from the month October there. So it’s a bit of a longer list. So I’ll ask AI assistant to help me kind of like narrow it down so that, you know, I have a better gauge on the data. So what I’m going to do is I’m going to say, hey, based on the table, which product type should we prioritize for the next seasonal campaign to maximize the engagement and conversion? And then if you see the this has narrowed down things for me and I’ll focus on these products as of now. And when we get into the details of my campaign, then we can actually even streamline the data. So let’s get started. Right. So let’s get started with the campaign creation. So I’m going to go ahead and say, hey, please help me plan an email marketing campaign for the fall season. And my focus will be to target weekend yoga sessions. So I want to experiment with two variations of the content. So let’s go ahead and post that.

So as soon as I post that, AI assistant comes back with a full plan on executing that campaign towards the right side here. The first thing I see the AI assistant did was make sure that it’s understanding my question and uses that to come up with a complete plan. So the plan has a goal as well as four different phases to it, including creating audience, setting up the journey and generating new content and setting up some monitoring and scheduling process. So each phase also has certain sub task in here. So if you look at it. Yeah, there you go.

Now, looking at this, I realize that I have not given a lot of information or like, you know, the audience is a bit weak. So let me quickly fix that and we can see how that works out.

So I’m saying, hey, let’s make sure that the audience is at least 10,000 profiles and let’s target people who have viewed yoga leggings and mats but have not purchased recently. So I have clearly explained my intent. As you can see, it’s gone ahead and added a new constraint into the plan here. So under the constraints, it’s also checking for audience should have at least 10,000 profiles. So once it creates the audience, it does the self check.

So, and again, one more last thing before we proceed. I want to remove the monitoring phases of now because I don’t have the right connections to do that. So I’m going to go ahead and say, hey, please remove the monitoring. This is also going to show you how it adjusts the plan based on, you know, our requirement as we go as well.

All right. So once again, you know, we’ve got the assistant has quickly adjusted the plan. The updates looks great and I’m happy to proceed. So I’m going to go ahead and say, yep, I’m happy with the plan. Let’s go ahead and proceed. So this is also one of the critical points that I want you to pay attention to. So every time, yes, it comes up with a plan. It ensures that it is listening and reasoning to what we are saying, but it also waits for us to approve it.

the loop so there is always human oversight onto all of the components that get created.

So once I have that, first thing that AIS is intended was it performed a few steps of this phase including discovering XDM fields here, translating that onto audience definition and gave me the estimate of the audience size as well. So the audience size is right and it’s the same constraints that I had given for about 10,000. So I’ll go ahead with this audience. I say yes please proceed with creating the audience. Also if you see here the first phase has gone now from in progress to complete and I’ve got the audience created. So this you can access it right here or you can also go to the audience UI and make any changes if needed. Now that phase one is complete I’m going to the next step. It’s asking me if I want to go to the next step to configure and create the email journey. So I say yes let’s go ahead. Now as we’re seeing with the specifications of the journey that it recommends, it’s basically recommending a journey plan and it’s pretty complex you know journey including certain branches for the experimentations as well as entry and exit criteria. It also shows me the journey specifications in natural language for my review so that I can understand that better.

And yeah technical details is easy and it’s easy to understand. It’s looking good for me here so what I do is yeah I’m happy to proceed. So once we do that comes back to me with the fully created journey and shows me the name of the unique ID of the journey that’s created. So that’s the key for us to go back to the journey UI and have a look at that and play around where you can even change here or you can go to the UI screen and then change make the changes from there. So the last phase for the plan is to set up the content. So I’m like I’m clueless I don’t know what to use. So what I’m going to do is I ask the AI assistant so what content variations should I use here. Let’s see what it comes back with. So now what AI assistant has done is handle the past performances of my content and picks up the top three themes that it think will do well. So this looks pretty good to me as well so I’m going to ask to generate two content of these variations and let’s see what it comes up with. All right there you go so we’ve got both the variations and look at that they look pretty good to me so I’m going to go ahead and say continue.

So as you can see now all the three phases has been complete and my work here is done. I’ve got my campaign and the variations has been complete. Thank you. So this is how customer engagement and data and insights agents come together to transform from insights to audiences to activation all in one single motion. So with that I’m handing it back to Pawan for his presentation. Some demos on content supply chain. Pawan to you. Thank you and let me share my screen.

Let me know if it’s visible to everybody.

Thank you. Yeah so as we understand from there that Adobe is embedding AI product across all these products which are solving different use cases. I’m going to put a spotlight on the AI which is my favorite word in the content. So in the content, AEM provide an opportunity to create those experiences and those experiences can be managed in the platform pretty well which works on the three principle of generation activation and optimization right that how you can create those experiences much faster that’s why the generation comes in a picture how those expenses are generated can be attributed to multiple channels those can be your Facebook campaigns, your marketing campaigns, your website, portals right so how you can make those acquisition more faster and after that your experience are delivered to the end users you have to basically continue optimize those experiences right so what kind of a platform capability can provide to make sure that those expenses are optimized so that I can getting more conversions more leads and everything right so these are the three pillars where AEM comes in a picture to basically create those platform. Now what Adobe have done a part of this framework these agents which are part of the orchestration layer helping these processes to be more optimized so that customer can basically improve the efficiency put the brand compliance and make sure that these things can be processed more faster so that you are basically more focusing or toward creating more brands more experiences rather than focusing more towards like how we can optimize right so these agents are basically are the individual tasks which are running as part of the orchestra which is basically working like a mind in the mind you are just past the context and the mind will automatically divert to the right agent what niche is supposed to do right and that’s where the AI assistant basically playing a role of the orchestra and these agent will be called over there so I’ll just talk about couple of agents basically like we we have launched one agent called production agent which are helping to basically manage your content cycle in much faster so that think about a use case where you have to update a content across multiple pages within few minutes rather than someone is updating manually you can basically leverage the the expense agent to basically make that things in a quicker few minutes wait we have governance agent which basically helping in terms of suppose you are basically creating a lot of the brands and expenses and those brands and compliance sheet basically is being done manually which taking more time right so one place you’re talking about that I how I can create my content faster which my system is given the capability but those brand experience should be live to the end user and branding compliance play a major role because everything should be governed and compliance and that is taking more of time right how I can leverage the agent capability to basically make those process automatic and that’s why the governance agent come the picture right and we will more deep dive on this more agents on the upcoming web series but these agents are helping in terms of the generation acquisition optimization and what we generally hear when we are creating these experiences and think these are the four uses we generally hear with the customer right most of the customer have those legacy platform which have the lot of the beautiful content right but those content is not visible in terms of the lmm right so your brand presence is not reachable right so how I can basically make my legacy platform to convert to the AI world so that whatever the experience I’m providing through those platform how I can do right so these agents can helpful to basically modernize your discovery it can help you to basically migrate your site content from the legacy word to the air discovery so that you can basically live in the world of the emotions are getting changed people are coming not coming to the your dietly site people are searching through the your elements and coming to a site right so your brand presence play a major role so this is the common use case which we hear from the customer another use case basically as I talk about you are creating good experiences right but how you can make those expenses do faster to the market the brand compliance come the major picture right how I can automate those processes so that one place I’m creating a like a good content on the pace but second place without content needs to be activated and fast in the channel right so how I can put the brand compliance check so that I don’t have to do those matter process third use case we generally hear that okay I created my content right how I can fast launch the multiple channel right or can I use some kind of automatic agent capability to do it yeah those agents basically helpful to basically create your production launch at Wishinger where using the agent you can update a lot of content with a single click and by passing the single command over there and last but not least when I talk about the expenses those expenses is basically your assets play a major role right how those experiences can be delivered in optimized way so that if my campaign is being delivered through Instagram Facebook website right I have to deliver different uh expenses to the in optimized way so that people are able to convert right and for that the my expense should be optimized to the channel how I can use my agent capability to basically optimize the right so the agent basically able to help to basically create those kind of variations for you which are compatible to your campaign and whenever the audience is being targeted to the current channel they are able to reach to you in a shorter time so these are the common use case which basically been covered in terms of the content and supply chain where these are the major pain point where the customer face it and these agent capabilities are helping to basically bring these use case in a real external part to improve the efficiency now what I will do basically I will take a quick demo on about governance agent which is one of my favorite and basically what is helping basically automating my brand and compliance check so that rather than things which are being done by the customer on the manual way they can do the automation over there right so this is one of my cloud manager demo environment and what it do basically that if you have the agent enabled AI capability enabled on the platform on the cloud manager you will see a option called governance context and what I did basically that under this governance think about I have brand called secret rank and whenever I’m making any expense live under this brand I want certain check to be part of that process so that every time whenever releasing any new content I don’t want someone to basically manually review it should automatically give me those brand compliance automatically you so within this brand what I have done I have configured n number of different kind of a branch governance which are basically that without these branch check nothing should be go live to the environment right so think about I’m a manual user I’m doing this check for every page so every page is taking for me 10 minutes I do think about I have 500 pages to reactivate right it is the 5000 minutes right as a manual however can I do some kind of automation on that part yes you can do it and that’s why the brand governance check can help you to over there I have configured this page I told that okay under this particular domain I want to run these branch check which should be done so think about I have a page which is basically hosted on this public domain and this is the page which I have to live it and make sure that this is following the brand compliance check what I have done basically I went to the assistant and what I did basically that I told you that AI assistant is playing a role of a mind you are passing a contact that okay can the system can tell me where this page which I’m publishing to the different channel that’s it following my brand compliance and now what I do basically behind the scene the mind automatically call the brand governance context because that is the way the mind is ultimately converting it you don’t have to worry and what I do it would go through my all the checks and tell me that okay does this base are aligned or not so if my those test cases are not being matched up to 50 it’s failing that your brand compliance is getting failed and any of the task is getting failed it also telling me the suggestion which is basically a discovery part that okay what are the content you’re using that content is not compatible it’s not following those background and this is the suggested so you can use it so that rather than working on manual thing you will automatically update it right so these checks will help you to basically move your content journey to production faster so that you can deliver those experience in a in a positive way now I will hand over to Vidya on the the other innovation which adobe is doing thanks baban we’ll be quick because we are running out of time again so so this is what we call basically about integrations or extensibility so we have identified the audience in our aap we know the gap is in the yoga apparel range the example that we took now the question is how do we get that insight into the hands of the people who need to act on it so as you all know most marketing teams are not using or living inside aap all day so they are in the powerpoint they’re in the teams they are writing briefs so and that’s exactly where adobe has gone to meet them with adobe marketing agent for microsoft 365 co-pilot which is now ga you know as we’re seeing here there are three things it’s basically unlocking insights on demand from aap journey intelligence and faster decisioning all without leaving microsoft 365 so here adobe is bringing the intelligence and microsoft brings the workspace and your team gets both so now let me quickly show you something more interesting and a bit different as well so that’s this is basically adobe marketing agent ama for microsoft 365 co-pilot which is live now feel free to try it out and you should be able to configure and access that if you need help with configuration you know whom to reach out to so now let’s quickly move on to something which is a little different the ones for the technically curious here in the room today so we all love claud here so what if instead of purpose-built integrations like on top of adobe assistant your team wanted to talk to adobe data through their own ai assistant of choice or a different skin and that’s exactly what we are doing with adobe mcp’s here so here i’m in claud and i’ve connected to the uh you know customer journey analytics where adobe mcp server let me quickly show that if i can there you go so this should be available for all of you as well i’ve connected to the cja mcp and i have given all the access and i’ve simply gone and asked uh to give fetch me uh insight from uh on a particular window for auto vision new optimizer campaign that i have launched and adobe data insights agent has brought the uh insights into claud and claud has created this beautiful visualization for all of us within that window and that’s the power of mcp’s that we are uh adobe is building across our adobe capabilities and solutions so now this is where i kind of like i want to pause for a minute and then make a bigger point here right what you just saw is not just one-off trick we have published mcp servers across enterprise entire experience cloud stack here we’re seeing analytics customer journey analytics aem commerce and all of it is available as you’re seeing at the bottom there um at developer.adobe.com a registry now so you can go have a look at that and explore how you can uh integrate with your choice of ai assistant so what this means practically is like your teams don’t have to work exclusively inside adobe interfaces it could be using claud copilot or any other ai assistant we support that with mcp and you can bring adobe’s data and capability directly into that workflow and this is kind of like an adobe’s openness we are kind of like you know not building walls we are not making it a black box but we are building connectors to it because the best of the ai strategy for your organization isn’t about picking one smart ai but it’s all about that making all of your ai tools smarter with the data which is within adobe so i know that there is was supposed to be a demo on the mcp server with aem but given the time i’m gonna skip that but if you are interested in that please drop us a note and we’ll be more than happy to do a deeper dive session on the mcp’s itself what we got so um bhavan do you want to take over yes let me present it uh uh sorry we are running late on time but i’ll just quickly cover so after your experience become live and to the human being right okay but the biggest problem we are seeing in the today’s world that lot of the traffic is now moving to the from the human touch to the lms people are more talking in the conversation way and what we are happening that even your brand experience is good due to the they are not following the certain format unstructured format the expenses slow they have a lot of the outdated content it basically did not give in the visibility to the to the expenses in the lmm right what does that mean that whenever someone is trying to come to those lmm’s and asking for this particular brand your brand is not getting published and not been shown on those lmm sites so your convergence it basically damaging the conversions it basically reducing the revenues and everything even your expenses are much better right so how we can basically do everything right and this is the uh like the survey which we’ve done and we can see that around 3005 traffic has been increased and it’s keep increasing over the years where people are not coming to the typical way of reaching to the site to the right content people are more going the conversion way where the lmm’s are basically playing a major role to basically in the in the reach to over there right and this is a quick summary how the things right now people are asking a question based they are basically not a query based they are basically asking okay oh i am coming to okay which is the best speed of editor basically which i can use right and this is the way the the conversation being done to those agent right and you see how the results are being displayed right and if your brand is not being displayed meaning it’s basically losing the opportunity to the convert right so those moving from the those legacy to the ai world i think is a big drift and which shift which is we are seeing so how you can basically make your brand presents so that whenever the content is being crawled by the llms it can basically provide the visibility in the things right so we have a product called adobe lmm optimizer which is helping the brand to basically bring towards the journey of the ai era so that using the lmm optimizer you can basically tune your content in such a way and you can pass those prompts to the lmm’s so that whenever the lmm comes and someone asks those queries and everything your brand can be mentioned and we have a upcoming webinar on lmo i think 10th of june where we deep dive of how this product works and how the things are but this just give a quick lens that don’t think about seo think about more about geo also because the shape is getting changed the human minds are changing people don’t want to reach on the site they want to believe on the lmm data so make sure that your data is visible more brands experience which will basically it will be a good conversion point to basically lm over there so we are going to cover more on that part in the upcoming session so i’ll hand over to vidya for the remaining part yeah thank you bavan all right so we’re gonna quickly go through the roadmap so to get you all excited for what’s coming so as we’re seeing here we started with ai assistant in 2023 and we have moved on to agents which is now right now where we are and we have recently announced ai co-worker simon i saw your question and i believe ai co-worker is where you know your marketers can really simply put a marketing strategy or a brief campaign brief and and the ai does that job for you from bringing in what attribute makes sense there what attributes would give you a better audience strategy or a campaign conversion rates so the co-work is what we are looking forward for so yeah keep an eye out for that this will be announced in the summit in in every regions in the next couple of months so keep an eye out for that to know more about ai co-worker so this is an architecture definitely you know i would let summit and then the the upcoming sessions talk about it but yeah really excited for this there’s a lot of flexibility here to use whichever ai we and which is all powered by our adobe ai capabilities underneath and the data that we have all within trust and governance and you know ai which is built on response responsible ai ethics again a deeper dive into what’s coming this is our what look uh roadmap looks like otop commerce integration and lmo ai collaborators engagement intelligence and b2b ai this one and cx analytics lm insights conversation insights so so many more things to look forward to so yeah keep an eye out for your summit announcements and this is all the uh agents that we’ve already released so and on a monthly basis we are releasing a lot more and adding a lot of you know more niche capabilities into all of these agents so it’s a really exciting time that we are in so yep i understand it’s gonna be a little feels might feel like a bit overwhelming but you don’t know what you’re doing and you’re doing it all by yourself so with adobe experience uh adobe ultimate success we have a curated accelerator where we help you with um you know a structured accelerator where we kind of like you know help you with um walk away with the clarity on where yeah it fits into your tech stack you know a prioritized roadmap of use cases uh defined kpis on them and not some architecture that clears next steps for your organizations and and and the teams here today we have like you know ones we have today here uh wherever you are in the journey and the adobe journey and this is how you know come talk to us and this is how we can move you from watching demos and a concept to actually deploying the ai so if you still need more help for the help here then we still have three ways into it ultimate success we help you prioritize the use cases and give you the roadmap and with integrated services they can help you actually implement deploy those ai capabilities and premiere learning will help you to self-service diy by knowing more about our ai across adobe and we have released quite a few um training material expanded experience league with hands-on guidance a training community premium learning for leaders and value realization program that is coming soon as well this is a really uh ai training hub is really well built uh so i would highly recommend everyone to have a look at that we’ll share the pack after the session so you can scan that and then it takes you directly to the website a really good place to start if you want to get across adobe ai and also leaving some references for you to take away so the three things you know at the end of this from today is we all have to understand ai is moving fast so lean in don’t wait for the perfect moment and adobe cx enterprise that is the story come know about it you know it’s a data content and engagement brand visibility all of that connected through agentic ai and you saw that today via some of our demos and be ready to adopt this space is evolving so every week and every month so stay curious and keep experimenting not last but not the least again we have just surfacing all the next webinars that we have if you have not registered register for it if you don’t have them talk to your adobe account team and they’ll be able to get this across to you and before you all go really appreciate if you can take the survey it helps us shape the next webinars that we have um uh it’s better for you so please do take the time to take this survey and let us know what you think of the session right that’s all i had and on time and we have some questions in the q a we will definitely get back to them but yeah just bear with us if you have any more questions feel free to drop them there and then we will definitely get back to you with the recording and the pack and the answers to your questions i was just going to put a link to the upcoming webinars as well i’ll put those in the okay thank you guys thanks everyone thanks everyone have a good afternoon