Good morning, and thank you for joining us for our Q2 FY 2027 IR webinar on product adoption and momentum. I am Mark Murphy, EVP of Global Investor Relations, here with Valmik Desai on the far end, representing the IR team for Salesforce. We are very grateful to be joined by Bill Patterson, President and Chief Commercial Officer, sitting next to Valmik, as well as Connor Marsden, President of Sales and Chief Consumption Officer. These are two very dynamic and impactful thought leaders of the industry. Gentlemen, first off, thank you for joining us this morning. Morning. Thank you. Great to be here. Our goal with this is to address investors' most common questions and topics leading both into and out of our earnings report last week. Those are going to include AI monetization, AIforce, and other product and partnership announcements, including the one relating to Claude, infusion of AI across the platform. We are going to give you a couple customer stories to try to demystify what is actually happening on the ground. Before we begin, I want to read you this disclaimer. Some of our comments today may contain forward-looking statements that are subject to risks, uncertainties, and assumptions, which could change. Should any of these risks materialize or should our assumptions prove to be incorrect, actual company results or outcomes could differ materially from these forward-looking statements. A description of these risks, uncertainties, and assumptions and other factors that could affect our financial results or outcomes is included in our SEC filings, including our most recent report on Forms 10-K, 10-Q, and any other SEC filings. Except as required by law, we do not undertake any responsibility to update these forward-looking statements. Our plan is to start with a brief presentation, and then we are going to jump into your questions. Please, at any time, when anything crosses your mind, feel free to submit your questions in the chat. With that, I am going to hand it over to Connor and then Bill. Fantastic. Thanks, Mark, so much. I am so excited to be here today to talk about some of the momentum that we are having in the market today and really helping to turn our customers into agentic enterprises. We have probably shown this slide to you a lot, and I am going to provide some context on what we see with our customers today. First, to ground us, as we have been in this agentic revolution, there is really four key aspects to make any agent successful. It is trust, action, agency, and interface. We have re-architected our entire platform to be able to meet the moment in today's market. Starting with trust, trusted context, and data that is delivered in a secure way with the right user permissions, and of course, with zero data retention as we start to integrate with the LLMs. Our action layer, that is our application layer that our customers have used for years and years, Service, Sales, Marketing, Analytics. This is where we have our standard workflows, business processes, or custom workflows and business processes to meet the unique needs of our customers. For example, Tableau today has 33 million semantic layers built in that we can now extend into our layer of agency. You are probably seeing some new names on the list, Casey and Hunter and Marshall. As we have continued to extend our agentic footprint, we now have out-of-the-box use cases that our customers are leveraging to drive our agentic footprint. For example, Casey. Casey takes advantage of the best of our Service Cloud application and the best of our data footprint underneath to provide great resolution for our customers with no human interaction. But when you do need to pass it over to a human, it is passed with the context of that conversation, so the human can pick up with their own agent to help solve that customer problem. All of this is extended into our headless interfaces. Whether that be our traditional Lightning interface or Coworker, which is our fastest-growing AI product that we have had to date, or Slack, or Teams, or this great announcement that we made with Anthropic with Claudeforce, being able to take the best of Claude to create custom interfaces that combine the best of Salesforce and the best of other applications into dashboards, analytics, and purpose-built views into your data to help people get work done faster. A great example of this is SharkNinja. SharkNinja is a great commerce customer, service customer, Data Cloud customer today on the platform. They launched a service agent together with our shopper agent and saw a 6% increase in conversion. But then they wanted to build their own custom agent, an unboxing agent. This unboxing agent, when you opened up one of their espresso machines, would help walk a customer through how to set up the machine, how to configure it, how to make your first espresso, how to order any consumables for that item. It required each layer. It required the agency layer, it required the service layer, and it required the trust layer with Data Cloud, all uniquely positioned. They saw a 93% resolution rate for the customers who used that agent, and only 7% had to be promoted to a human. So that represented a better customer experience and significant cost savings. What is unique about our platform today is that when we look at the data lakes and the hyperscalers, they may have a data layer and they are building out an agency layer, but they do not have an application layer today. Or if you look at the frontier models, they certainly have an agency layer that they are building, but they do not have an application or a data layer, and really understanding the metadata and the context and the semantics of the data in which they are working out. The traditional application providers, they may be building an agency layer on top, but they do not have the robust data layer that we have underneath. We are uniquely positioned in that we have all four, and all the providers wish that they had Slack today to drive AI together with your employees and the marketplace today. Through this investment, we are seeing our agentic footprint rapidly expand. When I started as a Chief Consumption Officer in February to make sure our customers are getting value off their deployments, it was really about Slackbot, our A4X, which is our internal agents, and Agentforce, which was the foundation for our external agents that we were providing into the marketplace. In H1 through both organic and inorganic innovation, we brought Piper and Marshall, our Momentum acquisition for conversational AI for our salespeople, and then Coworker, which we launched at the tail end of H1. That is going to rapidly expand into H2, with our pending Fin and Contentful acquisitions, our Marshall, Albert, which is going to be taking the best of Slackbot, but extending it to non-Slack environments. Hunter, Casey, Paige, Carter, just to name a few, and then all powered with our headless and Claude applications. What is really interesting is we have 10,000+ customers today that are uniquely using one of our AI products. Now we are seeing significant momentum as we are having more success of people adding a second, third, and fourth AI solution from Salesforce. So we can continue to sell into our base and driving new customer acquisition, which roughly doubled since the beginning of February, the number of customers who had our AI products in production. But now we can start to cross-sell into that base of customers to show more value from an agentic standpoint from Salesforce. What this really has helped us lead to is fantastic financial results. Our Agentforce and data ARR grew by 200+% to $3.9 billion. Our Agentforce ARR is up 200% to $1.5 billion. Most impressively, this is a measure of value and the work being done on the platform, we saw a 97% increase of our AWUs to $7 billion. We get asked the question all the time, who is using our platform and is it old industry, new industries? Nine out of the top 10 AI native companies have chosen Salesforce to be their central nervous system and their brain for running their operations today. What is another thing that has enabled some of the success? One of the things we talk a lot about here at Salesforce is speed to value with our customers. We have made a lot of really smart investments to really unlock the value for our customers. Starting on the right-hand side of the screen are builders. Builders are our version of FTEs. We have roughly 600 today in the market that are all embedded within inside of our sales team, working hands-on board with our keyboard, and we are going to be more than doubling this investment towards the end of the year. We really saw the value in out-of-the-box agents. That is the Casey, Hunter, Piper, because when we have an out-of-the-box agent together with our apps and our data layer, we are really able to drive fast time to value and get our agents up and running in 30 to 45 days. We wanted to unlock the entire developer community. We launched Agent Script, which allows us to plug in Agentforce into Claude or Codex so that they can use the development environment of their choice and drive deployment with inside of Agentforce. That is why we are seeing the time to deploy significantly improve. Just one other aspect I want to talk about. All these, since we have agentified every layer of our platform, for our traditional application, sales and service, we are able to use these coding tools, Claude and Codex, to actually configure our Salesforce environment, and we are seeing a 40% improvement on how quickly we can get our customers onto our platform. One large major global retailer that we are working with needed to do a contact deployment with agents on the front end. Their internal engineering team gave them a quote that it was going to be 35 weeks to deploy a custom build of that solution. They chose Salesforce. We were able to get it live in six weeks. It is phenomenal about how we can use the tools to deploy our platform, to bring agents along for the ride, and really turn them into an agentic enterprise. This is really reflected in the new customer acquisition that we have been able to drive today. I briefly touched on SharkNinja. We have Dell that is using us for supply chain today. 19,000 individuals at Dell use us to route complex supply chain requests, automate the processes, and it is saving roughly 30 hours per week per team. We talk about fast time to value. Live Nation, they just had a great festival, BottleRock up in Napa Valley, and we were able to get an agent up and live in 30 days where they had 37,000 guest interactions, and they are going to be expanding this to all their festivals across the world. Wyndham deployed an agent in their contact center that saw a 25% increase in the average or decrease in the average handle time that they are able to deploy. And that required their application layer with agents and then on the foundation of data that we are able to bring to bear. We are seeing fantastic momentum today with our platform, with our customers. We are seeing expanded usage of our apps, and now we are starting to see customers go back to the well again and add the second, third, and fourth agentic solution from Salesforce. This is going to drive monetization at every layer of our platform. Now I am going to hand it over to Bill to maybe talk about how we are trying to innovate from a pricing perspective. Yeah. Thank you, Connor. Look, I think one of the reasons that I love working at Salesforce, it is the slide that you see here. It is all the customers that we are bringing really into this agentic era of truly transforming their business. But I can guarantee you, if you have the wrong pricing model and the wrong monetization model, they are not going to transform. In fact, they are going to be really confused. One of the things my team has been deeply focused on is really simplifying and streamlining a lot of our pricing and packaging opportunities, really to give customers benefit at this time. Enterprise software has always been complicated. It has always been challenging to sort of price by feature or price by size of an offering or how much scale do you want to put into your solutions. When we had this moment really about helping our customers, we went back to sort of the foundations of Salesforce and said, "What we really need to do at this time is invent a new pricing structure that really aligns to the benefits that customers realize from this new technology that you just went through." That is where, number one, the first area of focus for my organization is ultimately helping with better predictability, but really better value realization for customers. We have invented a whole new model called outcome-based pricing. Our help agents like Casey, like you talked about, are priced by the resolutions that they drive for our customers, and if they do not resolve the issue, you do not pay for the offering. This is truly putting our money where our mouth is around driving better value realization for customers who utilize our technologies. In addition, it is not always the case where you can have price agents on an outcome-based way, because sometimes agents work across multiple disciplines, multiple domains, multiple offerings. What we have also done is really gone back to the drawing board around creating better value-based bundles and Flex Credits to flex and scale and stretch the platform, as needed, to really utilize and deploy the capabilities you need to make your business successful. As Connor started, the architecture is so pervasive now, and it is so impressive, and it is accelerating every day. But really, the Flex Credit manifestation lets you use all of those capabilities to use what is right for your business and just give you more value at scale. What we learned at this moment in time is customers are on different modes and pacing of this journey, and so we need to ultimately be more flexible. We need to offer new ways to activate your business on Salesforce. This is sometimes where you utilize things like pay-as-you-go. I just need to pay for as enough of I'm consuming from the platform and put it into action. Or, thank you, I use deeper contract structures like our Agentic Enterprise Licensing Agreement, which gives you unlimited access to all the technology, utilize what you need, put it into practice, and then scale that across your business like never before. These new structures, more predictability, more customer value, more flexibility, are fundamentally transforming how we serve our customers in this moment. Because at the end of the day, if it's confusing and if we're not serving our customers, it really doesn't matter. Let me build a little bit on behind the scenes about how we're using this new headless 360 monetization structure. We've got a lot of questions about this from developers and a lot of our partners. But essentially, as I mentioned, everything is a compounding model here at Salesforce. Flex Credits serve at the foundation of every sort of consumption utility that we have in our offering. If you just want to get started, use what we call our Salesforce Foundations platform and Flex Credits, and that just runs the meter for what you access on the platform itself. One of the things we're really excited to do, though, is to offer more of that predictability, more of that value for every user. We've created what we call this headless add-on, which packages a lot of work capacity for every user, make it easy. Maybe you and I use the software a little bit differently. You're probably a lot more intense on the software with how much consumption you're driving. But essentially, that headless add-on monetizes just in a simple way for every user to access to the platform, and it gives you enough capacity that you need to get your job done. We take this headless add-on, put a lot of work capacity. This is all the AWUs you need to be productive. Now that becomes a simple way for every organization to start accessing new technologies like Claudeforce, the partnership we just announced with Anthropic. Now we're also going to take that headless add-on and package it into our premium edition. As you move up the value stack for Agentforce for sales or Agentforce for service or one of our Agentforce for industry offerings, this capability nests inside of that productivity suite. This is where we start to see the magic start to occur. All of that AI, centralized and organized by role, optimized for every user, makes our users very productive with the amount of capacity they need, and it's really that focused productivity they require to get their job done. That Agentforce for service or sales add-on also nests in our premium edition. This is where this compounding monetization, simple model, it just embeds into every prior edition, embeds into the top tier. This makes it really simple for our customers to plan, predict, and scale their use of Salesforce in this moment in time. Ultimately, the Agentforce 1 Edition is the best of Salesforce for all roles. It's what includes our traditional applications like Sales and Service. It packages Slack, it packages Tableau. Ultimately, this is where the best of all of our company's offerings come together in that Agentforce 1 Edition. This is really exciting to see the growth of this offering because it means more customers are finding more value with the platform in this moment in time. Ultimately, at the end of the day, it is about transforming their businesses with the technology we serve them with. I know, Bill, when I go and talk with our customers today, there is a lot of concern over the cost of AI. We have heard some of the stories on token maxing, things of that nature. We have the flexibility to provide unlimited agreements, so we can provide a predictable model on what the cost can be. If customers are using multiple solutions from Salesforce, you do not need to precisely predict what the consumption on anything is because you have Flex Credits that are fungible that can be plugged into your data solution if you end up using more of our data products or across your various agents. We can meet the moment for wherever our customer is on the journey to provide them the right contracting and pricing to meet their requirement. That is where our breadth and scale really comes to provide comfort for our customers, that they know they are going to only pay for what they are going to be using in whatever iteration that we decide to package it up in. I was with a customer just recently, and they said their spending is up 30%, and when they actually did the math, their productivity was up by about 3%. Yeah. And so there is just a fundamental mismatch today between what is going on in the spending environment and in the value realization environment. Our mission is to change that. It is to be easier, to be more simple, to be more valuable for every customer. So you are not counting how many tokens, you are counting how many leads that you processed or how many new orders that you managed or how many cases you have resolved on our platform. Then just the last thing that has been eye-opening for me personally is users. What this model is providing, especially with headless, is it has actually given us access to more users internally of people who want to take advantage and consume the application. It may not be the full Salesforce application. It may be a headless application that they are engaging with and consuming, and so it is actually expanding our TAM across the addressable user base inside of our customers. Yeah. I think serving customers is not limited to one department. Yeah. So the opportunity to really use this new platform, this new capability to reach across the organization so that we all can work in service of our business and all work in service of our customers, it is ultimately where we are seeing a lot more value be created. Yeah. And a lot more growth opportunity for our customers to realize on the basis of what this platform can do for them. Yeah. It just really unlocks the system, so if someone in finance needs to address a service or a pricing issue, they can get access to the right screen to get their work done efficiently with AI guiding their journey. Absolutely. Thank you so much, Connor and Bill, for all those comments. We would now like to go ahead and get into the Q&A session, and we have left plenty of time for that. I want to remind the audience that you can go right into your Zoom interface and submit questions through the Q&A chat box. While we queue up those questions, I want to begin with the first question we see, which says, "On Agentforce and Data 360 pricing, you have iterated through several models. Is the pricing approach getting clearer for customers, and are you seeing their preferred way to consume it become clearer, too? Yeah. First off, thank you for the question, for those that submitted online. First off, is the pricing any more clear? God, I hope so. We have actually been iterating along the way around different moments of what the AI can do, and in some cases, like you have seen, where Agentforce started as a platform where we were building a lot of capabilities, and it was about building agents, we had to price in a platform kind of way. That really made it so you were probably maybe too atomic for what you were monetizing in the offering. As we have these new worlds of out-of-box agents or complete agents, finished agents to serve a domain that can get to an outcome, it is a lot more easy to predict and scale those kind of price and monetization moments because the value exchange is clear. As the feedback continues to come in for our ecosystem, it is getting more clear. It is getting easier to deploy. It is getting easier for customers to realize value, and that value exchange is ultimately where, again, as Connor and I were talking, very different from how many tokens do you need to be productive? Yeah. I definitely think this is a much more clear approach. It is not limited to Agentforce. We have also been simplifying our approach with Data Cloud and some of those underlying technologies to serve the agents with. As I mentioned, we sure hope it is getting clearer. Our customer feedback has been quite strong. Again, how that measures and manifests is the more that customers adopt, that is where we see success. It is natural when you have a kind of Cambrian explosion in all of these new technologies, the new surfaces, the new form factors. There has to be experimentation- Yeah. ...in the early innings, right? Well, we always say the inventor of the ship also invented the shipwreck, so we really needed to make sure that we went through these iterations and tested what works, what scales. Ultimately, at the end of the day, our mission is not just put technology in the world and hope you get value from it. No. This is where we go back to our roots of Salesforce and say, "You get value from the offering and get value from the agents, and the value exchange between our customers and our company is clear." So yeah, I definitely appreciate the feedback. It has been a lot of iteration, but I think the signs for customer benefit and growth of usage, as you have seen, Connor, are starting to show those signs of a much more clear approach here. Wonderful. Thank you. Our second question, I should read the names as they are coming in, is coming from Luke Heinen of Madison Investments. Thank you, Luke. This says, "How are you or will you monetize Slackbot? If customers prefer to use Claude within Slack, is there a way to monetize that, or does that limit the Slack revenue opportunity? Yeah, great question. Thank you, Luke, for the question. We are planning to monetize Slackbot as part of your Slack subscription. First off, Slack is a per seat or per user subscription access fee. So everyone who wants to access Slack pays a per user per month offering there. Inside of that per user per month offering, we give you a lot of capacity to use Slackbot to be productive. So if you are asking questions about your customers or asking questions about your suppliers, you can use Slackbot for all kinds of productivity experiences, and every user gets a lot of questions that they can ask. Now, if you have power users, and you go beyond that inherent supply, you can always add more capacity for Slackbot to do more work for you. So again, this is where we load you with enough work to get started. You utilize what we call our Flex Credits to expand that usage capacity as usage grows over time. It really allows our organizations to crawl and walk, then truly run with AI into their offering. The second part of your question about embedding Anthropic inside of Slack, does that limit Slack's revenue appeal? Absolutely not. Anthropic is good at some things. Slackbot is good at some things. Other partner offerings and other AI offerings are good at some things. So what you really should expect from Salesforce, and ultimately what Slack is as a surface and a canvas for us, is expanding the number of opportunities that other productivity systems can integrate. Because what we know is integrating in the tools of choice of the customers that we serve is going to ultimately make them more productive on the platform. We don't see that as a limiter. We actually see it as an amplifier. And we do think that it also drives happier users. By the way, happier users drive more usage, more usage drives more retention. This flywheel of opportunity and growth truly starts to get groundswell and steam. I actually had this question happen with a customer where they were using Claude, and they were evaluating Slackbot. And fundamentally, Slackbot uses Claude as the underpinning of the LLM. Yeah. But we provide practically unlimited use of Claude with inside the Slackbot licensing model today. And so what I told the customer is I said, "Hey, you can use Claude and pay per token, or you can have an unlimited use of the application inside of Slackbot and not worry about your token expense, have the same capabilities, have the same ability to share skills to be productive and drive it." And they found that to be a much more appealing model than using Claude from a token perspective today, and they opted for Slackbot. And so this is, once again, from a pricing and packaging standpoint, what are the scenarios where you're going to uncap the amount of use of the application and spread it across a lot of users. We're going to have power users and light users and have the right model, versus a scenario where you're going to be paying per token that potentially can expand where you're not getting the productivity, and the customer opted for Slackbot, and that's a pattern that I see playing out over and over again. Absolutely. If I could add two more points on the Slack piece, because it's so important to the core strategy. The Slack interface is expanding as we speak. The innovation that the team's driving there, we've talked about Slack Code briefly at earnings. When you come to Dreamforce, you're going to see a full version of what Slack Code looks like for a developer. That interface, that UI, where you're able to get your work done, where previously you might've been switching between four or five different screens just to get that workflow complete, Slack is now becoming that hub for a lot of that work. Two other stats that I think were really impressive from the quarter. First, Slack had its strongest net new AOV performance since we closed the acquisition in Q2. Second, since we launched Slackbot, just in the period from GA to today, we've seen a tripling in upgrades. So when we think about the value of Slack and how we're thinking about this broader interface layer, the more we integrate with more partners, bringing those amazing multiplayer agent experiences into that interface, the more we drive more Slackbot usage, consumption, adoption, the better for Slackbot, Slack's overall business performance, and frankly, the better for how we're actually interacting with Salesforce, right? For me, I do a lot of customer meetings when I get asked to. I love to do it. Previously, someone from Connor's team would come over and be like, "Okay, let me give you the prep. Let me pull stuff from our Salesforce org. Let me give you the full view." I don't have to do that anymore. I just ask Slackbot, "What should I know about X customer? What's their recent products? Are they having any customer success issues? What's the team trying to sell?" It gives me a full prep doc directly within my Slack channel. And within that prep doc, I have Connor's team coming in and telling me, "Hey, here's where we really want you to focus." So this flow of the interface being everything that you would've normally done across multiple different layers showing up in Slack, we think is super exciting. It's a game changer. It's addictive, I can tell you that as a new joiner that never had access to Slack and had never seen it. I said recently, if you take it away from me, you're going to have to pry it out of my cold, dead hands. That is how addictive that product is. Thank you for that. Next question is going to be from Alex Zukin of Wolfe. "How should we think about how much certain agentic workflows cost? Is there a dollar value per lead, or is there a CPQ agent or a marketing agent? How many AWUs will that burn, and how should customers think about fitting this into budgets, particularly with something like Slack and Code channels, et c?" Thank you for the three part question there, Alex. Alex, thank you for the thoroughness of the question. Let me tell you how our team thinks of setting pricing in this moment, because as you've seen and heard earlier, we went through a lot of iterations on this topic. How we think about how much certain agentic workflow costs is really about setting a value, and a value for how valuable is the offering that we're sort of putting into the hands of our customers. For example, we know there is $1 per lead because that's ultimately how organizations size and scale their own performance and their own planning and budgeting activities for how many marketing qualified leads they need to really enlist and fuel their sales funnels, if you will. We do look at this in terms of what organizations today pay, not just in software, but total costs, labor costs, workflow costs, software costs, the integration costs. All of that sort of equates to some degree of utilitary budget that an organization would plan for. What we're doing is we're competing on the basis if we think we can make that easier for organizations to do based when you use our technologies. I don't actually want you to be think. The second part of your question about AWUs that burn, I actually don't want you to think about that at all. I think that's an internal measure of utilization for how we are sort of seeing how much performance happens out of our platform, called the Agentic Work Unit. What I want you to be thinking about, and what I want your customers in the industry to be thinking about, is really the labor and the economic offset of, it used to cost me maybe $5 to do a phone call. Well, now I can actually do it for $1, $2 per resolution here on the Salesforce platform. This is where we want to just think about offsetting expenses for our customers and making it much more economical, much more easy to scale using the benefit of our platform that can now serve that unit of work. Next question is from Kirk Materne of Evercore. "Can you talk about how the horizontal pricing strategy for AI complements your industry cloud pricing in any industries where these new AI pricing configurations are landing best? Yeah. This is fully a pricing webinar today, I think. The horizontal pricing strategy and the industry pricing strategy sort of follows that same structure of compounding value, like we talked about, where the horizontal platforms are priced as a baseline. The industries and the vertical offerings that we have, where they have much more acute value and much more precise value, therefore higher value, if you will, are priced at a premium offering for our customers. In terms of that compounding value and that stair-stepping model, our Financial Services Cloud is priced as an uplift on top of our core Sales Cloud, if you will. This is where you see that value compounding structure really come to fruition. Are there industries where AI pricing configurations are landing the best? I can give you two, and then maybe Connor, you can add in. Yeah. I think financial services is an area specifically where the datasets, the regulated sort of environments, the out-of-box functionality we've built for KYC and household management, these are specific areas where we have priced premium capabilities for sort of the financial services industry that we price on top of our core Sales Cloud, but which maybe doesn't need those areas in the horizontal selling kind of way. Same thing on health, and again, where you see this sort of regulated environment where you have PII information, you have information around HIPAA compliance, our offerings that have these sort of compliant boundaries have all of this nested value on top of the horizontal offerings. This is where you see AI for industries really command that premium price point, if you will. Maybe you can add a few from your standpoint. We're seeing a lot of momentum in our consumer goods market right now with our CG Cloud, and we're seeing all the leading CG players migrate over to our platform. There's really two scenarios. There's the customers who already had CG Cloud today, and now they're agentifying their processes with our out-of-the-box agents for CG Cloud, and we're getting an uplift as they're starting to deploy those agents. We're seeing a lot of net new customers that are buying, deploying, and creating global models for CG Cloud. But in the starting position, they're agentifying their work processes. With CG Cloud, the out-of-the-box use case, they're able to deploy in 30, 45 days on top of their existing platform. We're seeing tremendous momentum for that right now because the AI is purpose-built for trade promotion management, for retail execution. It's an agent that sits alongside the salesperson to understand, what's the package that I sold to the customer? Have we sent the rebate check back to them for the display that they put inside of their store? All the approvals and workflows are flow through the back end of the system that the agent drives it, and it brings in the best of both worlds, the determinism and the probabilism on top of the industry solution. We are seeing these industry models and these industry purpose-built agents really driving value and speed for our customers, which is so critical as things get more competitive in the marketplace. Wonderful. Our next question is going to be from Saumik Chatterjee of JP Morgan. What are you seeing in the early days for adoption of Agentforce 1 Edition, and how do you envision the customer sales motion to upsell working? We are seeing an explosion of upgrades to the Agentforce 1 Edition. It has been absolutely a phenomenal motion for us, and we think it is going to accelerate because we are adding headless into the model as well. Before, it was about unlimited Agentforce for the internal users, so an agent sitting alongside a contact center worker to help walk through a customer issue and to guide them through resolution, leveraging the full knowledge of the organization. Now it is going to be not only that agent sitting on top of, but then also what are the headless interfaces that that employee is going to potentially want to leverage to drive. Agentforce 1 Edition has been a big winner for us, and we see it accelerating as we move through the foreseeable future. Yeah, I am so excited about the Agentforce 1 Edition. When we sort of invented that offering for our customers, we were listening deeply about what their needs were. What they all told us is, number one, they wanted to be multi-cloud customers. What Agentforce 1 Edition has is it not only has, let us take in the case of Sales Cloud, has all the best offerings for what Sales Cloud can do for a sales organization, but it also has Slack, it also has Tableau, it has Agentforce, it has Data Cloud, and it has flex credits sort of in its core. Yeah. What this means is for the first time, Sales Cloud customers are experiencing the benefit of Slack or the benefit of Tableau or the benefit of Data Cloud or Agentforce, et c. What we are really so excited about around sort of the sales motion side of this, a lot of it is user-driven. A lot of it is sort of application-driven. It is almost like product-led in that more usage, more scenarios of expansion now start to occur because all of those offerings are natively there and available for the user to start discovering. I think your point is dead on, Connor, around headless. Headless really allows usage walls to break down between applications. It is just about getting your job done, and we are serving that in new and exciting ways with the platform itself. I think the sales motion side, the adoption side is clear, but the selling motion is a lot of user-led expansion and user-led sort of iterations on what they do with the software every day. That's right. Our next question is coming from Paul Oppenheim of Ardsley Partners. Slack as the front end for usage is a really powerful position. Given that position, can you monetize carrying various frontier models similar to an Amazon Bedrock? Who wants to take that? I guess the notion of the model router or picking your model. Well, I'll start from the monetization lens, and Connor, you can kind of expand on that from the customer lens. But look, I think this is a moment where customers want choice to sort of complete their work, and I think this is also a moment where some models are very expensive to complete low-value work. Some models are very cheap but maybe they're not as efficient for all the kind of work exercises that are required. I think our position here continues to be that with Slack, and we agree with your sentiment, by the way, that Slack is probably the world's best canvas to consume models with. We think it breaks down the sort of the technical digerati of making it hard for the average user to sort of find AI productivity in their everyday work and workflow. We are really excited about Slack as that front-end kind of experience. On what kind of work can you get done, yeah, we think customers have the right to choose. We think customers have a right to choose various frontier models to drive various tasks. We are very, very excited about the partnership we just announced with Anthropic. We are going to expand those partnerships in new and exciting ways to really be focused on the right tools for the job. It is not a really healthy strategy for you to cut butter in the enterprise with a chainsaw. What we really want to do is make it easy for users to get productive and use the right model to serve the right task into the enterprise. You can probably expand on that from what customers are telling you. Well, customers are really excited about Slack because there are so many unstructured conversations that will happen about a customer. All the frontier models want access to that data because they all see the value that taking their frontier models, applying against that data, the unique scenarios that we can start to create for customers, together with the Slack data, with the Salesforce data, with the third-party data that we are ingesting into Data 360 to get the complete picture of the customer. It really is the ultimate layer of bringing all the pieces together. Clearly, the more models we can put forth, the more choice we can provide, cost options and whatnot, what is the right model for the right job? That is definitely an area that I think we are going to continue to drive and explore, because ultimately it is going to drive more value for our customers. The frontier of models want to get into it because it is the best demonstration of the value that their models can bring to an organization to really pull that full knowledge together and solve that problem on behalf of an employee or customer. Everyone is aligned to Slack as that key surface. The next question we will take is from Ted Wang, ExodusPoint Capital. Could you talk more about the industry cloud opportunities, in particular Life Sciences Cloud? Wondering what the growth opportunity is there and for other industry clouds. Yeah. I think every customer we serve is in an industry, and the good news is we have a lot of industry pre-built capabilities to transform and help those organizations adopt AI like never before. We have 13 different industry solutions. That list continues to expand, of which Life Sciences Cloud is one of our newest ones. We are so excited about this opportunity because every organization is reinventing itself not just on the basis of what human capital and human labor can do, but now this expanding opportunity around agentic labor and agentic process enablement gives us an amazing runway to keep helping every one of these customers transform. The Life Sciences Cloud opportunity, and we've seen this really accelerate since putting it into the market, roughly, I think it was less than a year- Yeah. ...has been one of our fastest-growing industry clouds. I think because of this opportunity to safely transform with the Salesforce platform, a trusted platform like you showed in the architecture today, that is what gives a lot of companies the excitement and trust that they should transform their industry with Salesforce. Also, these pre-built workflows, these pre-built capabilities, these agentic front ends, give us new ways to help these customers find new value creation opportunities for themselves. This, I think, cloud continues to have huge runway ahead of it. I'm very excited about this customer transforming. I've been with a lot of global companies, especially in France, that have really taken this cloud and embraced it to accelerate. I think this is going to be one of the growth drivers for our future on the industry platform at large. Similar to CG Cloud, life sciences is going through a big upgrade cycle right now. For the most part, we weren't in the life sciences business, so this is all greenfield for us. Yeah. Now a customer's trying to sit down, and I made this in my opening comments, the application companies today, they have applications. They may be trying to build some agents. They don't have the data layer. They don't have the interface layer. When thinking about Life Sciences Cloud and how you deploy it to satisfy the needs of the end sales users, you want to have the right interface to meet those user requirements. You want to have agents built in. You want to be able to leverage the full totality of all your knowledge internally. To some degree, we're bringing in a full platform that's fully agentified with data, agency workflow processes, and interfaces that we can, in a greenfield space where we didn't have a solution, now we're selling the full picture. We're not just selling an application from that perspective. To some degree, it's an unfair advantage that we have right now to capture share inside of Life Sciences and these other industry clouds built on the standard industry framework that we're building for these industries. That gives us a real advantage, and that's why we're seeing such aggressive revenue growth in Life Sciences, in CG, and the other clouds that we've brought to market today. We need an agent that can manage microphone failures. That's one thing that would help us. All right. Thank you, Ted. The next question is from Jackson Ader of KeyBanc. "Are there sales enablement changes or product training initiatives that need to be undertaken for the new AI motion, or is it pretty seamless for the existing AEs? Yeah, I'll take this one since I support a large part of our sales organization. Yes, there's a change, and it's a change in conversation. It's a change in where value is being derived with inside of our customers, and we have a very robust enablement motion that Miguel Milano's been driving of training and driving. But the best training happens on the job. We're not just talking about AI solutions. We have them deployed internally. Our employees are using Slackbot on a daily basis. They're using our Hunter agent and consuming leads from our Hunter agent inside. If you go to salesforce.com, you'll see Piper, our Piper agent, that helps generate opportunities, that helps create custom presentations to customers as they're looking for product, and then booking customer appointments. Our AEs are living the experience at the same time as they're selling the experience, and that makes it so much easier for them to translate. When I go in front of a customer today, my teams would spend one to two weeks putting together a background and a brief on what conversation to have. Today, I just type into Slackbot, "Hey, I'm meeting with the CEO of XYZ company. What should I talk about?" It goes into Slack, and it sees all the unstructured conversations. It goes into Salesforce, and it says, "Hey, here's what they've bought." It goes into Service Cloud and says, "Here's the issues and the cases that they have." I get the complete picture of the customer, something that literally has saved weeks of time for our customers today, and our AEs are using those tools on a daily basis. Yes, there is training. There are new business value models that we are creating that we have to train our end users up. The most important fundamental fact is they are living the experience on a daily basis, and they are able to bring that experience to our customers. When our customers see how we are using AI today, it is very eye-opening, and it drives a lot of momentum and accelerated sales cycles as a result. Yeah, Connor, you and I have worked together for a long time. Even time before- Yeah. ...our time at Salesforce. We are getting a little bit old now. The transformation that is going on in the selling environment, I think you personally need to take a bow on because you are leading our company by example around what does it mean to really drive utilization and activation of everything that has been sold so that you can ultimately drive value? This is not just me, your friend, saying it. I think you actually are leading the industry in this way. The element of transformation that is really exciting is when we grew up in our careers, you used to sell first and then sort of deploy. Yeah. Now what is happening is organizations are deploying, seeing that value, and then selling is almost happening on the other end of that. It is almost a complete inversion for how we grew up in our careers together, for what selling kind of means. Back to your point, it is not exactly the easiest transformation. We have to almost unlearn what we have learned for 25 years around sell and then deploy. Now it is about a deploy and sell and realize value kind of world. I think that ultimately, this means that we will add more value for the customers that we jointly find a lot of passion serving because our customers are actually getting benefit from the software, not just getting more software. Yeah, no, and that's why we've been really aggressive of putting consumption into our frontline sellers' commissions. If they sell something, they have to deploy it, and that's going to be tied to part of their compensation. We're going to lean more fully into that. Because we all know that if customers are getting value, they're going to be more apt to buy that second and third application. Going back to my original comments, we have 10,000+ customers using our AI solutions, and now we're seeing the second, third, and fourth. Because the customers, when they see value and they see value being created, they want more of that because that's going to translate to them supporting their customers in a deeper way. Yeah, and I think that point is actually being crystallized in one of the metrics we share with you regularly, that 50% of the Agentforce, the agent-specific use case, 50% of the bookings there is actually coming from customers refilling the tank. Yeah. Yeah. In that exact motion. I think when you get the salespeople aligned, the customers aligned, you deploy together, you get value out of it, they're willing to come back and buy a lot more. Yeah, well said. Wonderful. Our next question, this appears to be coming from a customer, Andrew Russo of BACA Systems. Thank you, Andrew. "We have Agentforce 1 Edition. We upgraded to it to be able to drive business value for our team. Users are loving it. We are using Salesforce across our entire organization, from sales to the manufacturing floor and finance. That being said, will Salesforce be evaluating moving sales and other automated things like sales autonomous sales agents to be outcome-based? It is much more palatable for our CFO to look at trading payroll for outcomes versus payroll for usage. First off, we always listen to our customers. Andrew is someone from our customer community we deeply listen to because he deeply cares and is routinely at all of our events and gives this feedback to us live. Andrew, first off, I am happy to tell you that yes, we will be driving more outcome-based sort of offerings in sales. We will be driving more outcome-based offerings in service. We will be doing more outcome-based offerings across our platform because we 100% agree with you, my friend, that the more that we can drive value exchange between us and the customers that we serve and making it easy for you to talk to your CFO, we want to make that easy for you. Because again, tracking tokens and token spend doesn't always equate to business value exchange. Outcomes really allow you to sort of start to scale and predict the value not just sort of consumed, but the value realized from our platform. This is something that we are really excited to talk about at Dreamforce in just a few weeks' time. You should expect to hear more about, as more of our agents move into the outcome world, how they will find mutual value between us and your organization. But again, thank you for everything you do, Andrew, for our community, and thanks for coming onto the webinar here this morning. Yeah, let me just add to that. This is where our scale really comes to advantage because we can have various pricing models for our customers based on the individual use case versus a collection of use cases, whether it be agents or data or Slack, from that standpoint. So, charging on a per lead that gets qualified through Hunter, that is a direction that we are definitely going. Now, clearly from an AI standpoint, when I see sales autonomous sales agent, like how far we can push sales into agents to take that off of the sales team so smaller transactions just go through an autonomous agent, we are going to be pushing that as hard as possible. Yeah. In fact, internally, we are actually seeing our agents drive revenue in smaller transactions with no human touch. As the models become more sophisticated, as our determinism becomes more effective, we are going to push down into that. I think that is going to create new monetization models for Salesforce and for our customers, so they are only paying for the value that they are going to derive. Thank you, Andrew, for those thoughts. Our next question is from Tyler Radke of Citi. "You mentioned last quarter that a large portion of Agentforce net new AOV was driven by top-up credits. What are the high-value use cases that are driving top-up actions? Does that change with the Claudeforce announcement?" Maybe for the benefit of anyone who is not familiar, just explain what a top-up action is. Sure. Essentially, when we have a sell of credits to a customer, it is you are buying capacity for an Agentforce or a Data Cloud to be used for usage that might be a service use case or a sales use case or a data processing use case, et c. So, an initial sale might supply you with a certain amount of capacity. When we talk about a top-up credit, that means a customer has consumed all of that capacity and needs to refill the tank and put more in a tank because their usage is going beyond maybe their expectations. It is a great bellwether of success that customers are actually driving usage and retiring the credit that they have bought against one of the usage scenarios. Because ultimately, as we mentioned earlier on outcome-based pricing, that means they are getting benefit from that usage. So of the high-value use case that we see for driving top-up actions, one of the clearest signs of value between us and our customers, for Agentforce specifically, has been in the customer service domain. Today, we use Agentforce at Salesforce. You can go to help.salesforce.com, see the solution live and running on our own website. You can see how many cases we are driving, how many interactions that we are resolving, all autonomously with the power of that platform. That is the clear use case that are truly starting to emerge is customer service and customer service resolutions are probably the highest value use case that is there. There are others. We also have deployed Piper, our digital SDR agent on salesforce.com as well. You can have a conversation with Piper. Piper actually is an agent that is working to qualify you, nurture you, put you into a selling funnel. That's the kind of usage that, again, you buy a bunch of credits. Once you get more usage, you top up those credits because you're obviously qualifying or nurturing more leads using the power of digital agents to drive that activity. What are some of the others that your customers are seeing? Yeah. So it's a great question. So, from a consumption standpoint, the service use case drives roughly five times the amount of AWUs as the other use cases, just because of the intensive workflows and the sophistication of the determinism behind the agent that's required to satisfy. That's why we're so excited for the Fin acquisition because it's going to be bringing in a service use case to a part of the market that we're not serving today, and so it's going to be very complementary to our current service use cases that we have inside of Agentforce. Services by far where we see the most top-up actions. But what I've seen over and over again, especially in our retail space, is that people are looking for super agents. So they're looking for a single agent that they can drive agentic commerce experience. If a customer needs to do a return or claim there's something wrong with their product and get that fixed, they want to have it in a single user interface. So now we're seeing this concept of super agents of multiple use cases layered together to go and solve a customer's issue. The Claudeforce announcement is only going to accelerate that. Because Claudeforce, we're going to be using, as I mentioned in my earlier comments, some of the Agent Script, which is a really technical term, but in essence, it opens up to developer. You can plug in Claude into our Agentforce platform to drive faster deployment. So that's what our FDEs use today to really configure and get agents up and running in 30 days. Claudeforce is going to accelerate it, and because we have a platform with out-of-the-box use cases, you can start to layer those use cases up. I'll give you one customer example. We have a customer, we actually have a lot of customers that fall in this scenario, where they'll buy a shopping agent from one vendor, and then they'll have a service agent from another vendor. So they've got two separate agents that a customer has to go to resolve an experience. The customer doesn't know, I go to this agent for this or that agent for that. They just want to be able to talk to the agent and get it resolved. Our framework and our architecture allows us to have a single agent experience to be able to jump from a shopping experience into a service experience, all contained inside of one agent that helps lead to more top off, because now there are multiple ways that they can consume those Flex Credits that Bill was talking about. So as people are shopping more, they can use more Flex Credits for shopping. As they are driving more service actions, they can drive Flex Credits to drive those service actions. Ultimately, the customer is seeing more value, and their customers are having a much easier experience in working together with that brand. Okay. We are coming up on the top of the hour, so we are unfortunately not going to be able to get to every single question that is in the queue. We will do our best to follow up with those of you if we are not able to get to your question. The last question is coming from Arjun Bhatia with William Blair. How are you handling model choice and model routing? Will Agentforce be served by a preferred model? Do customers have choice to bring their own models? Yeah, that is a great question, and I think it is probably a question really on the minds of a lot of our innovation teams today. Ultimately, making sure that the right model is used for the right purpose. But I think it starts with when we built Agentforce and we built the architecture of Agentforce initially, we have always allowed our customers to bring their own model. We have allowed them to optimize what each of the prompts that Agentforce powers behind. You have the ability to pick what models you use to complete those tasks. Because in not every case, you need a premium model to perform routine workflow, if you will. We will continue to open up the platform and allow our customers to bring their own in a perspective. Sometimes they have built their own models, and they want to use those models as part of their routine workflow, and so we need to open our platform for that kind of usage altogether. But the further part of the question about will Agentforce be served by a preferred model, I do not think there is a one-size-fits-all structure that we think is preferred or not preferred. What we are going to continue to do is as model innovation continues to exist in the world, we will keep testing the right models for the right purpose and the right domain. We will make sure that we will always select probably the best initial model, but allow customers the choice to override to provide the best fit for their organization at large. So yeah. I think as we continue to get into the place of arbitrating what is the right offering and the right routing solution, that is an area that we are happy to talk more about at Dreamforce in a few weeks' time around how the innovation platform is starting to emerge. Here is one thing that I would add to that. We are working with all the model providers. We are working with open source models as well. Ultimately, what we are trying to do for our customers is we are trying to abstract that complexity from them. Because all the customer cares about is what is the end outcome that they are getting. Is their service case getting resolved? Is their lead getting generated? Are we providing the right pre-summary brief for field service to the end user so they understand the work that is going to be provided? Our platform allows us to abstract that. It is not the preferred model, it is what is the right model. The right model. that we need to provide to solve that. If it is a lower cost model, great, we do a lower cost model, and we can have that value exchange with our customers. Ultimately, our mindset is going to be what is the right model to solve the problem that the customer has so we can deliver the right outcome, and that is where we are grounded right now. The flexibility of our platform is going to enable us to be able to drive that on behalf of our customers, which is going to be an advantage in the marketplace today. Yeah. I am going to sneak in one other question that an investor had on the gross margins of all of this, because I think it is very tied to this question. Obviously token pricing has shifted a lot. You get a new model launch, the older models might get less expensive or more expensive if they are trying to force you up to that new model. There is a lot of confusion in that, to your point, Connor, on, okay, what do I do if I am a customer? Which model is right for my use case? We take that ownership on. We help you decide what makes sense for you. If you are really, really set on this is the model I want to use, great, we will do that. But if we think about the efficiency-accuracy curve, which is really what everyone's trying to solve for, we want the most accurate and most efficient outcome. Choosing the right model for the right task enables us to take advantage on a gross margin side of the efficiency and token pricing changes that are happening. We are being really thoughtful from innovation to pricing and how we are thinking about the underlying gross margin impact of the business on where does that fit, how do we get the best kind of agent routing to the right model to be able to solve for the most accurate, best outcome for the customer while solving on the back end for the gross margin side. It is a constant moving target, but the teams are working really well together to make sure that happens. Before we close today, one quick reminder. Mark your calendars for our Investor Day. It is coming up on September 16th at Dreamforce. You are going to be able to tune in for a deeper look at our latest innovation and financial framework. I want to make sure I am thanking Connor and Bill and Valmik for being here to speak today and overcoming each and every technical hurdle very seamlessly that was encountered. To our audience, thank you so much for joining us, and we will see you next time. Thank you. Thank you.