Experts of Experience - AI Agents Explained: Build a Digital Workforce That Works 24/7

Episode Date: March 24, 2025

In this special panel-style episode, Stephanie Postles, host of Marketing Trends and Mission Daily, joins Lauren Wood to interview Bernard Slowey, Senior Vice President of Digital Success at Salesforce. This is your inside look at Salesforce’s rapid deployment of its revolutionary AI agent, what this means for the digital workforce revolution, and how ANY company can create a customizable, empathetic digital employee. (With no code, just natural-language prompting.) Bernard shares firsthand accounts of the launch, including navigating real-time customer feedback and the crucial lessons learned about data hygiene and prompt engineering. He also discusses the delicate balance between AI automation and human support, emphasizing the importance of empathy training for these digital agents. Plus, they explore the challenges and opportunities for businesses of all sizes, from SMBs to enterprises, as they grapple with the evolving landscape of AI-driven customer experience, sales, and marketing.Press play and discover how Salesforce is shaping the future of AI in service, and what contrarian views Bernard Slowey holds about the role of data in decision-making.Key Moments: 00:00 Who is Bernard Slowey, SVP of Digital Success at Salesforce?04:18 The Evolution of Customer Service06:28 The Power and Potential of AI Agents18:06 Implementing Agent Force at Salesforce22:07 Challenges and Learnings From AI Agent Deployment33:29 Measuring Success and Future Prospects39:58 Escalation Rate and Customer Experience41:21 The Importance of Human Interaction in Support42:51 Digital Success and Customer Onboarding45:28 AI in Customer Success: Real-World Examples47:24 Data Hygiene and Internal Content Auditing 53:04 Cross-Functional Collaboration in CX01:00:28 The Human-AI Partnership 01:08:36 The Future of AI in Business01:12:51 Customer Obsession in Practice –Are your teams facing growing demands? Join CX leaders transforming their strategies with Agentforce. Start achieving your ambitious goals. Visit salesforce.com/agentforce Mission.org is a media studio producing content alongside world-class clients. Learn more at mission.org

It's this transformational moment that I think every company is like, wow, how do I enable this and how can I use this for my customers? Just months after announcing Agent Force, Salesforce is unveiling its next generation AI platform called Agent Force 2.0. Tell us how big companies are using Agent Force. I know already it's being employed. I've never been more excited about anything in my entire career. Salesforce dove into agentic AI quite early on and developed Agent Force, which I know you were lucky enough to be customer zero. We were treating it like an old school chatbot. Don't do this, if that do this, right? Instead, it was like, no, no, you're smart. We went back into Agent Force and we coached it, just like you would coach a human employee and that solved that problem.

What we forgot to do with Agent Force is we trained it on the hard skills but we didn't focus on the soft skills and we talk about this as the head and the heart. We now have a digital workforce that will augment our human workforce. You're like the original case study and companies can just copy paste your strategy. Every company in the world has this problem of they show their silos to their customers. Suddenly you now have this agent of they show their silos to their customers. Suddenly you now have this agentic layer that goes across all of them. The things that look contrarian and crazy today will be commonplace in the future and so this will probably be very common I would assume in the next year or two. You're going to see a lot of companies

going live with agent force over the next couple of months, a lot. agent for us over the next couple of months a lot. Hello, everyone, and welcome to Experts of Experience. I'm your host, Lauren Wood. And today we have another host as well, Stephanie Postel. Hi, Steph. Thank you. Thank you. I'm excited to be here.

So excited for this conversation today, and especially excited to poach this content and put it on Marketing Trends. So thanks for letting me be here. And just so everyone knows, marketing trends is another mission show that Stephanie leads. So definitely head over there to listen to that as well. But we're doing a joint episode today because we have a very special guest,

Bernard Slowey, who is the senior vice president of digital customer success at Salesforce. And today we talked about how they were customer zero for their new Agent Force product, which was really fascinating. Steph, what did you take away from the conversation? Yeah, I mean, now I feel like I'm gonna be looking at everything in my life, wondering,

how can I put Agent Force in it? What can I automate here? I mean, it was very inspiring, especially thinking about like how I can use these functionalities within my own company, which I think I had a story that maybe this could only be for enterprises. So yeah, also impressed that they got this up for Salesforce in four weeks. I have not heard of that happening so quickly. So that was amazing. Yeah. What about you? What was the most exciting parts for you?

I mean, I think that fascinating thing for me about Agent Force, and I've been nerding out on this big time because agentic AI is the next wave of AI. We've been in the generative world using LLMs, chat, GBT, all this stuff, and now we have actual AI employees that are joining our team who can own entire processes, who can make decisions on their own. And that requires us to think very differently about how we are using AI and training AI and actually coaching AI to do what we need it to do. And Salesforce has really been a pioneer in this space. And they've been very early. And I think that Agent Force is really the best example in the market of an agentic AI that is enabling customer experience to really

be what it should be. And so it was really cool to hear Bernard talk about their experience of being their first customer and the learnings that they had in actually utilizing it and how they're helping other companies now do the same. So I thought it was fascinating. I'm really excited about this episode. Yep. The authenticity was real. He definitely talked about some stories that we won't share now. Got to get into the episode, but very fun just hearing some of the little mess-ups and the feedback they got and LinkedIn posts that got a little crazy and comments. And so if you want to hear about that, you want to see how to dive into the world of agentic agents

and see how it can transform your life, this episode was lit. Yeah, let's get into it. Bernard, welcome to the show. It's so great to have you. I'm very excited to be here. Thank you so much for having me. So we want to kick it off by taking a trip down memory lane

and talk a little bit about your history and what you've seen over the past, wow, decade plus in the tech space. And I know you started your career in customer service as a project manager at AOL. Is that correct? I actually started as a tech support agent for AOL and worked my way up to project manager. Tech support agent. Yeah, yeah. I was a tech support agent. Part time when I was in college, that was where I started. Amazing.

And so you've seen a lot of change. Can you tell us a little bit about what you've seen since then until now? Yeah, you made me feel old, by the way, when you said that, which kind of made me laugh. But it has been a while. Yeah, I've been in it too. It has been a while. Yeah, God, it's incredible change actually when I think back on it because I started as I was in college and I needed a way to fund my college activities. I

worked for AOL in the evenings and on weekends and I used to be a support agent helping people set up AOL on their computers. And even if I think back to that, like they had CDs to install. And even if I think back to that, like they had CDs to install. So now it's like even just thinking of a CD and trying to put it in. And it just like at the time that was that was normal. Right. That's how everyone did. I'm going like the cloud didn't exist back then. Everything was mainframes. It was local.

And so, yeah, it was it was an interesting job because I would have people. I couldn't see them. So now we're all used to video calls. That feels really normal to us. Like it was literally just me talking to someone and then trying to describe their problem to me and me tried to describe steps for them to do. And so even if I think back to that and where we are now just on this call, right. Or I think about my son and he uses FaceTime to call home to my grandparents in Ireland.

Like it's just amazing the change in technology that we've seen in that timeframe, both in our personal lives and also in enterprise commercial. And our ability to support customers as well. Like if you think about being on the phone, walking them through a physical action of putting a CD into a computer to download.

Now it is just a whole other level of automation and ease as well. And so I'd love to hear AI agents is the big conversation. We're going to talk about AI agents a lot today because of Agent Force and all the incredible work that Salesforce has been doing. What makes you excited about AI agents, especially as we look at it in the context of where we've been even in the past 10 years?

Yeah, I think we have like these moments in time with technology, like every 20 years or something, there's just something that transforms it. Like if you think about the service industry, it started face to face. You have to walk into a physical store or whatever it was. And so you were limited in the hours of operation of that store. Right. Then we had telly service, right. All of a sudden you could phone someone. Right. And that was a big transformation in technology. Right. Seems kind of weird to think about that now, but it was.

It meant people could be available longer hours. It wasn't just the opening hours of the store. Then we had the internet. Right. And then, so then it all became very much self-service. Like every single company in the world has a portal that you can go to store. Then we had the internet. Then it all became very much self-service. Every single company in the world has a portal that you can go to and try and find out something about their product. Everybody starts in Google. Everyone searches. They go to YouTube. They try and figure it out themselves probably before they even come to you or come to your

company. So now we have this moment in time, which anyone who used ChatGPT, that first moment you use, that you kind of went, wow, you know, it's these moments in time where it just transforms technology. And so now you have this way, these agents that are going to enable you to have 24 seven availability, you know, it's always there, it's always available. It's trained on all of your content. You don't have to like predefined these specific scenarios. It has access to everything that you want it to have access to, and it's incredibly accurate. And the other thing that's amazing is like today, a lot of our interactions are text

based, but voice is coming out as fast, you know, so you're going to be able to deal with these AI agents. And it's not like a robo call. It's actually, you know, natural human language. It feels very, very natural. So you think about that in the service injury space. It's like, I'm going to be talking to an agent that's going to be helping me solve my problem or help guide me on onboarding, whatever that might be. So it's just, it's this transformational moment that I think

every company is like, wow, how do I enable this and how can I use this for my customers? I think it solves so many of the problems that we've been seeing in the customer experience space. For example, when we call, I mean, this is still to come, but when we call a company and we have to then choose the button or choose who we want to talk to and go through all of this, it's so laborious. And now we are just easing so much of that friction through AI. And I'd love to just take a quick step back to make sure everyone understands what we're talking about when we talk about AI agents, because this is still new.

Can you define it for us? Yeah. I think like people still trip up a little bit on like chatbots and agents and kind of what's the difference. And I think we've all had an experience with a chat bot on a company's website. And generally it tends to be a bad experience. Chat bots historically, like you had to define the logic that was in the chat bot. What I mean by that is you would write a dialogue.

You would literally say if this then that, if this then that, if this then that. And if you ask that specific question that that chatbot was trained on, it did an okay job. It had no emotion, no intelligence, just helped with that thing. But if you went off script, if you asked it something that it wasn't trained on, it is a terrible experience. So now with these AI agents, something like ChatGPT is trained on the internet, so it's incredible the access it has.

But what we do at Salesforce is we give you the capability to train Agent Force on your content corpus. So instead of me having to suddenly like write all of these dialogues, I can literally give this large learning model access to whatever content I want to give it access to. And so now we can answer any questions straight out of the gate related to that content.

But where it gets much more powerful is that's called unstructured content. At Salesforce, we also have a lot of structured content. So a lot of information about our customers that's stored in something called our C360. Right. So you start to use that structured content and you can personalize the experience. I know who Lauren is. I know the product she bought. I know she just recently became a Trailhead Ranger. And so you can really personalize this into the agent experience while it's given answers. That's just something you could never ever do before. You know, it's pretty incredible. When it comes to AI agents, I hear the pieces around adding in the custom

data and you've got your own LLMs that you can work with. But to me, how I understand them is they're more goal oriented. Like they have somewhere like a problem they can solve, and they can head that way without building out chat bots and adding in information. Like it's really built off, like you said, if this and that, only the scenarios that you built out. But is it correct to understand that AI agents is more just like goal oriented?

Say goodbye to chat bots and say hello to the first AI agent. Agent for service agent makes self service an actual joy for your customers with its conversational language anytime on any channel. To learn more, visit salesforce.com slash agent force oriented. So today, like with our implementation of agent force, it's Q&A conversational, where you ask it a question and it comes back with an answer. And that's kind of how most of us have experienced ChatGPT. But where we're moving to is the agent can actually do action on your behalf.

And that's super powerful. So if you think about the example where you ask it, how do I reset a password, right? Generally, it will come back where you do steps A, B, C, and D. But imagine when we can actually do that on your behalf. So there's information we can get just to verify you are who you are. And then we reset the password for you. That's just a very simple example. Like in banking worlds, it's like issuing a refund on your behalf,

a retailer could be as well. So they can actually do action as well as just conversational Q&A. And that's a game changer. It's like having an employee, it's an AI employee. And I think that that's the big shift that I'm seeing when we talk about agents, is it's no longer just a tool. It's actually capable of so much more and making decisions on its own, which is also wild to think about.

Yeah, yeah. We think about it a lot as like, it's a digital employee. Just the way that we have human employees, we now have a digital workforce that we need to empower. And that will augment our human workforce, right? It allows us like a good example as well as these models have language capabilities in them, right? So suddenly we can go to all of these other languages that we might not be in today because we just wouldn't have the budget to invest in headcount to do support in these languages. Now you have it in English and you can use these large learning models to do real time

translation. So, you know, Lauren could be in Japan as an example, that's gone back and forth with our agent. That agent was trained in English, but it's able to translate and go back and forth with you and you know no difference. You know, so, so that's pretty incredible as well as these real, these language translation models just open up so many avenues for companies. Yeah, it's wild. I actually, a quick example of that is Airbnb. I'm an Airbnb host and I've had guests from other countries come and stay at my place and I talk to them in English and sometimes I get an email in another

language, but in the chat it shows up as English. And sometimes I get an email in another language, but in the chat, it shows up as English. And so I've been like, what is this? And then I went in to look at it and I was like, oh, that's what they're doing is real time translation between the guest and the host. And it's like, wow, that opens up so many more possibilities. So when we think about agentic AI

and bringing this into businesses, what is the opportunity at stake for companies to start using agents as soon as possible? It's interesting that I meet with companies a lot to talk about what we're doing and everyone's really interested and everyone wants to get started. But in a lot of cases, companies are afraid to get started. And a lot of cases they want to do internal implementations before external. When I say internal, what I mean by that is like maybe you have an agent beside your support rep that's helping your support rep, which is a great use case.

Right. But they're nervous to go external because they're worried about things like hallucinations or is it going to say something that like, oh, no, my company is going to be associated with this. And so, so that's one of the things I've really been helping companies and customers with is like I showcase what we did to say, Hey, look, there's, there's, there's rules, there's guardrails you can put in place so that it only answers certain things. And so I definitely, I see people want to get into it, especially companies, but I do see an apprehension

and nervousness on what happens if it goes wrong. For us, for that, we have in Salesforce, it was a design principle for us, was that agent forces backed by humans. If it can't solve, you easily go into the conversation with a human. It's actually pretty slick. Agent force leaves the conversation. Lauren, the support engineer joins the conversation. She can see the history of the conversation with Agent Force.

She gets an AI summary of it. So she can quickly start with, okay, I'm going to continue on from here. And so I think that's important design principle to help companies is it should always be backed by humans. Otherwise you're going to dead end. You're going to dead end people and frustrate them. What kind of company is this for? I'm thinking at least as a small business owner, is this something

that a small business owner can use or is it right now really for enterprise companies who do have a lot of data and a lot of things that they're trying to automate? I think it's the full spectrum, Stephanie, which is kind of what's amazing. If you're a small business company today, you probably can't have a support phone number, right? Because you're not going to invest in that headcount. You have other things you need to be worrying about, right? And so suddenly you have the ability to have support, right? You could have a digital agent on your website that's maybe answering some of your top questions from your FAQs and if it can't answer, maybe it submits an email a case where one of your humans can come back

afterwards. But I think it goes all the way from like small SMB to massive enterprise. Now obviously the use cases are different than how enterprises are gonna think about it, but I actually think it helps give SMBs a leg up because suddenly now you have this digital workforce that you can leverage to help you go faster. It seems like companies will be built off of this model,

like of AgentForce and having a bunch of agents. It's like a will be built off of this model, like of Agent Force and having a bunch of agents. It's like a whole different way of building a company. But even when thinking about these different marketing leaders that I talk to and the teams that they have, like they're thinking about team structures different. And I think actually startups might have a really great advantage of like, I have no employees currently, but I can have some digital ones. And now I have five or ten departments that are all, you know, digital employees. Yeah, yeah, totally. It's crazy.

Like it's, you know, it's often sometimes that you, you know, you have that advantage when you're new is that you can build around this technology that's there versus having legacy hold you back a little bit. I see this a lot in my consulting work because I work with a lot of startups who are in that position where we kind of have a blank slate. Or it's not too hard for us to take a step back and redesign how we're approaching AI, especially AI and CX. And then I also work with organizations that are much larger who it's challenging.

Like we have to really change our fundamental structure in order to now work with this AI and bring it into our existing system. It's just more complex and it takes more time and intention, although I will say, I think the intention is important no matter where you're implementing AI and really how you're doing it and what you want it to be doing.

But there's definitely an opportunity for earlier stage companies to start off with AI as a foundational principle. Totally agree. So I'd love to talk a little bit, or a lot actually, about Salesforce's agentic AI journey, because Salesforce dove into agentic AI quite early on and developed Agent Force,

which I know you were lucky enough to be customer zero. And I want to get into that story and understand one, what was it like really bringing in an agent workforce into your team? And then we're going to get into the lessons and the learnings and all that good stuff. But first, tell us just what was it like starting to use this? Yeah, it's kind of crazy to think about. We have our big sales conference, Dreamforce, around September every year.

And we had Dreamforce last year, which we pivoted to Agentforce as a company. Agentforce just kind of happened like this, as I said, this technology exploded. We were very lucky that we were working on an incredible product that could leverage that. So our whole Dreamforce conference was pivoted to Agent Force. And I was kind of standing there.

I was in that conference and I was like, wow, if anyone should be an amazing use case of this, it's what me and my team do, because we're responsible for our help portal at Salesforce, which is where customers go when they get like 60 million visits a year. It's like the second biggest portal at Salesforce. And it has a lot of content. It actually has 740,000 pieces of content. And it does a good job.

People find what they need. But we always heard two common pieces of frustration. It's too much content. I can't find what I'm looking for when I need it quickly. And so that was the opportunity with AgentForce, right? As you can now have this conversational experience, ask it a question, get the answer you want and go back and forth. So I challenged my team.

I came back from DreamForce and I said, let's get this up and running in October. So that was four weeks it took us. That shows how easy this product is. Because if you think about Salesforce, right? It's a massive B2B enterprise, hundreds of products, you know, it's complicated. And we launched on October the 11th. So it was just over, I think we were four and a half weeks that we got it up and running and we launched it on our help portal, which was pretty incredible. I've been in, you know, I worked for Microsoft for 15 years, I worked

for GitHub, I've been in lots of technology companies and to get something like this launched so quickly just showed the flexibility in the product. Did you tell anyone that you were doing this or did you like run on the down low or you're like, I'm just going to see what I can make. Surprise. Surprise. We're live.

Here you go, Mr. Benny. You're a great example for you now. No, we did tell people we were doing it. I felt like we were the perfect use case. I think service is a great use case, right? Because there's a clear ROI, right? It's like, hey, if we can have customers solve with this agent, then more than we're getting the solution,

what they need, et cetera. So you're seeing a lot of companies as they look at these agents, service is kind of the number one use case. And that's not to say there's like marketing's use cases, sales, there's hundreds of other ones, but I think companies are kind of honing in on like, okay, service is something

where I could really see this thing having an impact. And so that's why I felt we should be, you know, my leader, Jim Rowe, too, I know you had on the show before, he always challenges us on to be customer zero, you know, use our own products, be a showcase for our own products so that I can go talk to customers and say, here's how we're using it. Here's the mistakes we made. Here's the impact we're seeing from it. And so we really want it to be the customer zero of age and force.

That was our goal. Which I think is generally if you can be your first customer, you always should be just as a principle when it comes to customer experience. That allows you to really learn deeply what your customer is going to experience. Totally. Totally, totally. So like launching in four weeks is insane, especially if you think about how new this technology is and how complex the Salesforce system and help center is as well.

Can you give us a bit of an insight into like what you launched? I'm assuming it wasn't like the whole thing. I'm assuming you kind of took off a piece and said, okay, we're going to launch this. Yeah, it's interesting. So like, if I reflect back to that, like I was so nervous and like I was so nervous, like I had major anxiety because this was like, it's going to be available for people to use. And you know, once people have access to something, they're going to tell you what they think about it. And so we, we went live, we started small actually, we went live to what we, a cohort of authenticated

customers. What I mean by that was a small percentage of customers who are logged into our help portal could see the experience. So they kind of saw like an ask agent force kind of on our documents. So we felt comfortable doing that because we wanted to see, well, how does it perform? How many people click on it? Like all your classic, it's like, it's like a funnel, right? You're seeing who lands on your portal out of that number, who engages with agent

force, how much did agent force resolve? How many went through to the human? So you had all of these metrics that we're measuring. And, and so we started pretty small, but then we actually, as we started having reviews internally in Salesforce, we realized we were actually going too slow and that we just needed to get out there and open it up so that we could start to get feedback and learn. I'm going to screw up this quote, but Reid Hoffman who started LinkedIn, he has

this great quote on like, you should never be happy with the first product you release, but you should release it. And so that was the mindset. I was like, it's not going to be perfect. It's going to be things that people aren't going to like, but because it's out there and because it's live, we're going to quickly iterate and improve on them. Things. First of all, if we keep it back here forever, we're probably going to be too

slow. And so that was our mindset was like, it's good enough. It's not perfect. And it will never be perfect by the way. We're going to have to constantly keep iterating. It's good enough. Let's get it out there. So then we exposed it to everybody.

So anyone who goes to help.salesforce.com, you'll now see this beautiful full screen experience of Agent Force. You can access it. Anyone can access it, whether you're logged in or not. You can go ask it a question and it will help you on a question related to Salesforce. So I'm thinking about a lot of these big companies

who probably listening to this show, Marketing Trends. I'm wondering how, lot of these big companies who probably listen in to this show, marketing trends. I'm wondering how, like, did you have people pushing back on you being like, do not launch this, here's why is the terrible idea, like where they're seeing the risks being like so large that they're like, Bernard, this is a terrible idea. Cause I'm sure in other companies, this would be happening and like how to push back against that risk adverse mentality. It's interesting is that the hardest part actually came was Mark Benioff tweeted about it and posted on LinkedIn that we were live and he got a lot of

comments after his LinkedIn and his Twitter post and I was literally like going in reading every comment every day. I could open up my morning coffee and I'd open it to see what new comments were. I can't imagine the anxiety you were feeling in that moment. Some of them are brutal. Some of them, I honestly, I didn't feel great about my Salesforce career that first day because we had a lot, like we have a very engaged community at Salesforce. Like we have our trailblazers, our MVP program.

Like we are incredibly lucky, the engagement we have from our community. But with that, they'll tell you what they think. And I like that, right? But there was times they were asking it questions and the answer coming back wasn't a great answer. Right. And you know, there was, I'll give you one example, which is like someone had put a screenshot underneath them. They asked a question about integration with a competitor product. And we kind of said something about the product and then had a link to that company's website, which is not a great situation, right. I was like, okay, I'm definitely gone.

This is the end of my career. And I'll just, this is like one of the learning moments of agents, by the way, is like, what we did then is you go into, we have something called agent builder, which is where your prompts live. So these is like, you teach agent force. There's something called the global instructions, which is like a topic where you teach agent force, the world that lives in. So you tell it, you're part of Salesforce, no code, right?

It's all in natural language. And you tell it, I want you to speak in this voice and tone. These are the things I don't want you to speak about. So you can set guard rails. Like maybe you don't want it to ask questions on your CEO as an example. So you put all of this inside the global instructions. So when we saw that happen, we were like, Oh crap. Jumped into our global instructions and said, do not talk about our

competitors and listed every competitor. It was problem solved. Great. The very next day, in the very next day, we saw a case where someone asked, how do I integrate this competitor's product with Salesforce? We have great content on that. But what happened? Agent Force didn't answer, right?

Because we'd given it this strict guardrails of what not to do. So this was the learning moment first. We went back into Agent Force and we coached it, just like you would coach a human employee. We told it, we deleted that guardrail and we said, listen, you're a Salesforce employee. You're a customer service agent. What the best interest of Salesforce in everything you do. That was what we wrote. And so we taught it, we taught it to think we were treating it like an old school chat bot. Don't do this if that dude is, right? Instead it was like, no, no, you're smart.

We just need you to think this way and that solved that problem. And so that was a huge learning for me and my team. It's like, they just prompt design, this prompt engineer and it's a discipline now that's in the industry. And it's like, it's really, really need to think through it on what you write and how you write it. This is like such a new space we're in where people are still just trying to figure out prompt engineering for a chat GBT.

And they're like, oh, maybe instead of just like, give me the answer to this, it's like, I should say, pretend you're this and think about it this way. Like the more context. And so, yeah, no surprise that, of course, you're like, oh, yeah, maybe we should do that here, too. But it's such a fast paced world right now to keep up with. Are there any other funny moments like that that came up or just like things that happened while you were rolling this out that probably are relatable to other people who would be going through this process? I think maybe coming back to Lauren's question, which I didn't do a good job of answering

on of like risk averse versus pushing. Like we definitely had like people internally, like I used to, like we obviously Slack, Salesforce, it's a massive product for us. And so we all live in Slack. I would get Slack's every single day from people in the company giving me examples of where it didn't do a good job. A lot of the times they were people that were very knowledgeable in Salesforce products asking it a very detailed question.

And a lot of the times the problem wasn't agent force. The problem is the content in the backend that it's trained on. If you don't have good content, right? If you like, it's only as good as the knowledge it has access to. And so like, and people will go and they try it with ChatGPT and they go,

well ChatGPT gives me this answer. I say, yeah, but ChatG GPT has access to the whole internet. So it can pull an answer from Reddit. It can pull an answer from some blog somewhere. And the risk of that is hallucinations, right? That's what scares companies on these agents is like, so ours is one of the, what I mentioned earlier on, but agent force you limit it to your own content set.

So with that, sometimes if it didn't have the right content, it didn't do a good answer. So we had to work on updating our content. I think it actually exposed to us areas where we didn't realize we didn't have great content. I mean, that's such an important factor, which I actually think a lot of people who are approaching or rolling out AI, building it into their systems, we all need to do it. And people are taking different approaches. But the thing I keep hearing time and time again, is that your data is critical.

The information that you're feeding to the AI is critical. And it's a very large and complex thing to think about because we have, it's almost like we have like, all of our stuff is like strewn everywhere and all of a sudden we have to organize it in a way where someone can come in and actually like intake it and use it. And I'm curious to know your thoughts on that piece and like how did you go about organizing your data so quickly to then allow AgentForce to use it or had you already had a totally

clean house and none of that had to happen? No, no, I don't think anyone has a clean house. We had, we have an advantage at Salesforce that we have this other product called Data Cloud. And with Data Cloud, like people always ask me where we started with Agent Force. And when I tell people is like, it's like when you have a new employee start, what do you do? You give them access to data, right?

You give them content, you train them so that they can start to be up skilled and be able to do their job. Data Cloud allowed us to take all of these different data sources, these knowledge articles, these products, and actually hydrate them all into Data Cloud. Then that gave Agent Force this foundation. It's able to access all of this data in Data Cloud. That's the unstructured data. As I mentioned earlier on, we're now going to give it access to structured data as well.

So I think I had a bit of an unfair advantage where I had access to data cloud because I work in Salesforce. But when I talk to customers, I'm like, this needs to be part of the solution. Like you can use it without data cloud, but if you can have a repository that can contain all of this data and can bring it all in, it can normalize it, it can standardize it, then you have a huge advantage as you go live in these agents. I mean, it's really the strength of your agent at the end of the day. Like as you were saying, it's not going out into the internet to find answers.

It's using the information that you provided to it. And that's the beauty of it. And also it means we need to do that extra legwork to make sure that the agent has what it needs. We learned this quite in a hard way. So we're a couple of months in now and our agent force implementation still feels a little bit robotic. Like it responds to you, it gives the right answer. And so what we learned is what else do you do when a new employee starts in a service world?

Yes, you train them on the hard skills. Do they have the information to answer these problems? But you also train them on the soft skills, the way that you deliver a difficult message if you're a support engineer. We spend a lot of times on that soft skill training. And so what we forgot to do at Agent Force is we trained it on the hard skills, but we didn't focus on the soft skills. And we talk about this as the head and the heart. We were very much focused on the head, the brain element of it, and not enough on the hard skills, but we didn't focus on the soft skills. And we talk about this as the head and the heart.

We were very much focused on the head, the brain element of it, and not enough on the heart. So now we're doing a lot of work. We're actually taking the training that we train our support engineers on. And we're using that around some of the prompts for agent force. So just think about as we're given agent force access to that training. So it has much more of the soft skills on how it delivers its message. It's kind of crazy when you think about that, but that was being a big learning for us.

Yeah. The thing that I'm like kind of mind blown by is you're taking a training that you give to humans about soft skills and you're able to train an AI agent on the same content. You're just teaching it in certain ways. Like we always have this good example. Like if someone comes to us, let's say, with a severity one issue, right? Like let's just say Salesforce is down. Doesn't happen very often, but some companies can have things that are down.

The last thing you want is the agent going back and forth with you on potential ways to solve that problem. You want it to go, oh my goodness, you're having a sev one, I'm so sorry to hear that. We're going to get you through to one of our support engineers and they're going, you know what I mean? Like, that's an example where agent force needs to get out of the way quickly, but it needs to have a lot of empathy in that situation. Right. And so that's the example of what we mean.

You don't want it to be like kind of robotic and try and answer that problem. It's like, no, no, get out of the way. Be very empathetic to it. And that's how you would teach a human employee to also react in that situation. One thing we haven't talked about yet is like the success that you saw once you implemented AgentForce.

I mean, one, I'd love it if you, like if you had a before and after, because I'm trying to visualize like what it was like before when customers would go on there and ask a question, what it's like now to like really understand what it looks like and then what happened after. How many cases are getting solved with Agent 4? Tell me a bit of the stats. So this visual that you can see, this was our help portal in, I guess, September last year. And so it looks like pretty much every single company in the world has some portal like this.

You can come to it, you could search on it, you could access our content, it has videos, places to learn, etc. and you can go in and create a case from it. So that's kind of what it looked like back then. And so as I said to you earlier, unfortunately, the problem with this is people struggled to find what they were looking for, right? Especially if you were having a problem, you need an answer quickly. We hear that in all of our research with customers is like, hey, if I'm having an issue, you need to be able to answer me quickly, right?

And so let me now show you what this looks like now. So this is help.salesforce.com now. And so what you can see is it's a completely different experience. It's a full screen experience of Agent Force. So you can go in and ask it any questions I mentioned earlier, it doesn't matter what you're logged in or not, you can engage with Agent Force. And what we've done as well is you asked me like, how do we determine the success, right? We believe transparency is key for trust.

So what we've done is down the bottom, you can see down here, we actually have a live ticker to show how many Agent Force conversations. So since launch, we've had 450,000 conversations with Agent Force. So since October 11th, that's a pretty huge number. And then you can see, we also try and show our human tickets as well, because we want to try and show people. But what I want to show you is just something a little bit cool here now. And I go, you can click on this.

Here's how. And what that will do is going to show you all of our metrics and how we measure success. So this is our customer zero page. And you'll actually see there's a video there that some of me and my team are in to talk about our implementation. But what we show you is you can actually look at all of our data and you can go back to any date since we launched. What you asked earlier on is like, how do we measure success? Right. And so what we look at is

think about this as a funnel, right? Someone has a conversation with agent force, right? It comes back with an answer and you go away and we consider that resolved. Right. So you asked it a question, it came back with an answer and you go away. When I say go away, you don't want to create a case for the human. So you can see our resolve metric is like mid to high 80s, right? But we also get asked questions, but is that really resolved? How can you determine that was resolved? Maybe the question I just went away.

And so what we've implemented now is we have something called customer confirmed resolution, which is in the flow of the conversation. We ask the question at the end of the conversation, hey, did this resolve your issue, yes or no? On that customer confirmed resolution, right now we're about 76%. That's a really good data point for us that all of these conversations that you're having at the highest level, it's probably about 80 something, and then customers are telling us it's about 76 when they answer that question. The other two metrics I just wanted to show you so I can help explain it is we also look

at this thing, this is the agent force conversation handoff. So you can see that 4%. So that is that week, 4% of customers who engage with agent force got handed off to a human support engineer. So that was that kind of flow that I was telling you about. Like it's really critical to us that it's an easy flow. The other metric which is interesting for us is we have this thing called abandon.

And let me explain what abandon is. You can kind of see the ask agent force in the bottom right-hand corner. So a certain percentage of customers click ask agent force. They open it up and they don't ask you the question. And we're really interested on this and why is that happening? And we think some of this is to do a kind of UX UI

where people are like, oh, that's one of them old school chatbots. I don't want to engage with that, right? And so they don't ask it a question. And so that's something that we're working on is how do we kind of pull more people into the experience? But that is kind of the metrics that we measure today. And what's pretty cool on this site, by the way,

is we have lots of blogs on how we did it. You can. There's Jim wrote up there. You all know very well. And so we're very transparent. Here's all of our information. Here's how we launched it. Go look at it and see what you think yourself. Yeah, that's this is awesome.

I love the ticker numbers on the home page. I just feel like it's kind of gamified. I'm like, I just want to sit here and watch it go up and see how many humans are involved. And yeah, that's fun. And can we also talk about the sales strategy here? I mean, you're literally showing, we are using this, and here's the results that we are getting in real time.

I think it's something, this point about transparency is so critical. It's always been critical. But when we talk about AI, it is ever more important because customers, whether they're B2B or B2C, will trust you more if you are transparent with when you are using AI versus when you are not. And we see that in the data. And I just want to, I just think it's a really great, really great website. You did a great job.

I got him into Ticker was not my idea, but I love it. And at first I was like, a ticker? Why would? Because it's going to hit half a million soon. And you're like, wow, that's a pretty incredible number. And then, yeah, to your point on transparency, if we're not using our own products and we're not showing them, why would a customer buy it? So it's this trust piece of, OK, Salesforce is using it.

Here's all the metrics we measure. And like we debate the metrics as well. Like people are like, well, is that really a resolution rate? And we're like, yeah, you're right. We need to do better there. And so we introduced that customer confirmed resolution, which is people actually telling us, yes, you solved my issue, you know? And so we're just like any support leader in the world.

I have the same pressures they do to kind of show all of that sort of thing. And so we're transparent. Here it is. Here you can see it. Mm hmm. I love that you guys are like that you're like the original case study and companies can just come in and like copy paste your strategy. And by you doing all this legwork, I mean, I think about back when I worked at Google, we were always trying to figure out metrics of like which ones mattered. And we used to get excited about ones. And then people would come in and be like, actually, you don't want that metric to be high.

That's bad. That means you're having a problem. And like there was always so much debate. And so the fact that you guys did this first and you already have like a whole entire like basically you can copy this entire strategy and just do it with another company. But I'd love to hear who else has done this. Like who else has copied this? I love what you said there, Stephanie, because one of the other things that we like had these

long debates on is that handoff to human. Internally, we call that escalation rate, which is a real support mindset metric. You say that to people externally and they're like, what's escalation? Is that a bad thing? At that whole page you saw, our marketing team built that page. We partnered heavily with our marketing team on how can we tell this story easily to customers so they can go use it and kudos to our marketing team, handoff to customers way better than our human is way better than escalation rate. But the thing I want to tell you about, like we had a long debate, that escalation rate

was down at like 1%. And sometimes it was 2%. And now we're at 4%. And people are like, Oh my God, what's going on? And it's actually a four because it was too hard to get from agent force into a support engineer. We too much friction in the process. And so we want to, we've simplified that process. You can literally come and go talk to a human, talk to an agent, whatever that might be, and it will create your case and send you through. And so we think that escalation rate will probably get a little bit higher.

And we're okay about that because that means it's a good experience for our customers, which is the most important thing we're doing. But it's interesting as people can get driven by metrics, you know, it's like, oh, no, it's a four percent. Yeah, but that's a good thing. You know, and so so that's just like as you talk with that Google and that like debate and metrics, we do that a lot internally as well. I think that this piece is something that so many companies struggle with, especially as a CX leader.

I would always say, let's make the experience best for the customer. But it's not always the most cost efficient way, because it's better if we don't have a human talk to them. If we just make the customer figure it out themselves, or if we just have the AI do it, it's a cheaper option, but it's not the best experience. And we all know as consumers that when you want to speak to a human and you can't speak to a human,

there is probably nothing more frustrating. So I share this story with my team all the time. Like when I was kind of earlier in my career at Microsoft in Dublin in Ireland, we had this project that was literally called Automate and Eliminate. And if ever there was a name on a project that tells you you're doing the wrong thing, Automate and Eliminate was that. And like I remember I won like a gold star or some monthly award at Microsoft for driving up this number of Automate and Eliminate. And what did we do? We just made it really hard to get to the human. We put lots more

clicks in the flow. And so we saw people drop off and we were high-fiving each other. So it's my example of like, whatever leadership defines is like, these are the metrics. These are the things, sure you can do things to do that, but it can have terrible, terrible impacts. I think it'd be fun to hear maybe some lessons that you've gotten from either Microsoft or any previous companies that have influenced what you're doing with Agent Force and how you're thinking about, you know, like we're talking about with metrics or building out a team or really anything you're working on. I'd love to hear a bit about that. Even if I think about my role, I'm the SVP for digital success. And

someone called me recently in a webinar unicorn, which I didn't know how to think about that. But like, what it is, is that not many companies have a leader on a team that are 100% focused on the digital experience when you think about service. Right. A lot of the times, like I got passionate in this in my career because like I used to didn't need Windows support from Microsoft and massive support footprint, thousands of support engineers. But I always say like, no one gets up in the morning and says, I want to contact support.

They're all going to go online. And so I started to really hone in on digital and spend a lot of time there. And then kudos to Jim Rolte. He created a function, and I joined to come lead it. And my team wake up every single day. We wake up in the morning thinking about, how can we improve the digital self-service experience

for our customers? That's our day job. It's not enough. I find in many companies, they have people that run functions and then it's like, oh, and also you should think about digital. And so that's the big thing for me is you have to have people that are invested in it. I have a team of over a hundred people now that are working on, agent force is one thing we work on, we have other things, but they're all waking up in the morning thinking, how do we improve the digital experience for our customers?

Whether that's, you know, that's not just support motions. We also think about success motions, right? You've bought our product. How do we help you onboard? How do we make sure that you're getting, you're getting the value from that product. So you renew, right? Like that's critical.

Like supports kind of that moment something goes wrong and I need help. But we also need a great digital journey to help you on. And that's what my team 100% focuses on. And that's been a big learning in my career is like you need people that that's their day job. That's all they worry about. So I'm naive.

Is this not normal to have this kind of role? Like is this role not, oh, okay. I'm like, it sounds like perfectly like,, it makes sense. We should have it. Yeah. Yeah. No, it's funny. Like there's, there's a, there's a LinkedIn community now for digital success and there's like digital success webinars and like that didn't exist a while ago, you know? And so, so I get asked to attend these things and talk a little bit about my role and Salesforce. That's where the unicorn thing came up because I think I'm the only SVP that's on digital success, which made me made me laugh. But no, it's not.

It's not something that unfortunately for a lot of companies, it's on top of someone's current job. Yeah, I just heard a quote in my interview the other day where someone's like, the things that look contrarian and crazy today will be commonplace in the future. And so this will probably be very common, I would assume, in the next year or two. Yeah. I love that. The way that we can utilize AI in customer success is still yet to be seen in many use cases. And Salesforce is really...

I mean, Salesforce has pioneered customer success, period. So it makes sense that you are getting to lead that function. The new wave of what customer success really means. I'd love to hear some examples of other clients that you've been working with, other than Salesforce yourself, to really utilize Agent Force and how that's been taking place. Yeah, it's actually interesting. That site I showed you, if you scroll down to the bottom of that site, you'll also see other customers that are using it as well.

So I feel like a majority of my job now is going to talk to the customers about what we do. So that wasn't my job a couple of years ago, but we have some great examples like Open Table is a big company that's using AI agents now. And so we share with them what they're doing and they kind of check. I also want to learn from these other companies, by the way. Like, how are you implementing and what are you doing? What learnings can I take from you?

So OpenTable is a huge one. Vivint, I actually have them in my house. They're a security alarm system, camera system. If you go to their website, you're going to engage with an agent. Remarkable, which probably behind me somewhere. I literally have one that I'm using right now. Yeah, yeah, yeah. They're the best.

Incredible, and the best, amazing. You go to their website to engage with support and you'll engage with Agent Force. And so they're just kind of three top of mind examples. Like there's huge companies that we're working with right now. I can't kind of get into the names of some of them that are getting ready to do implementations.

And so that's where me and my team come in a lot because we share what we did, our lessons learned and our mistakes, so that they can get ready to go live. So you're going to see a lot of companies going live with AgentForce over the next couple of months, a lot. Are there any key questions that you keep getting asked, especially among these like larger companies coming in, are there themes where people are like asking similar questions?

Yeah. Well, one of them you all touched on earlier, which is around the data hygiene. There's this new terminology my team are talking about recently, which was a new one for me called data collisions, which is you have data that content is a good example where maybe you have a couple of articles on something that's similar and maybe you're using like an acronym name or something and the agent can't pick the right piece of content. It's a collision of that content. And so that comes back to this kind of data hygiene piece that you asked about earlier.

It is really important that you have the right data. We've spent a lot of time actuallying older articles, stuff that's not relevant anymore so that the agent's not trained on it. So that's definitely a very, very common one. The other one I would say is the experience from agent to human. We talk about that a lot, because in our experience, it's like you have a choice. You can have the human join the chat. So they come in, it's a seamless experience.

Or maybe you don't have the time at that moment so you know, they come in, it's a seamless experience, or maybe you don't have the time at that moment so you can create a case to like have someone come back to you at a time that works for you. And so we spend a lot of time designing that experience. And so a lot of customers are like, how did you do that? Show me how it works. And so that's another one that we spend a lot of time on as well. Do you have to go through like expectations with them?

I know when we talked previously, you were kind of talking about how a lot of people come in and they just expect AI to work right away. This better be perfect. I better fix all my problems. And you had a good analogy around like, what do you treat your employee that way in week one? Be like, what did you do? Why did you mess that up?

You got that thing wrong. I can't remember the name of the bias, but as humans, we have a bias for machines. That machine should always be correct. The example, the great example is bias, but as humans, we have a bias for machines that machines should always be correct. The example, the great example is like self-driving cars, right? Like we're afraid to let them onto motorways because there's like 0.000 whatever percent chance is that we'll have an accident. Humans have accidents all the time. Right?

So self-driving cars are actually a safer option than a human, right? But we don't want that to happen until it's near perfect, right? And so it's similar with some of these agents. It's like people expect the answer to be perfect all the time. And it might not be. And it might not be for multiple reasons. Like we talked about content. If the agent doesn't have access to the right content,

if that content's wrong, then your agent's going to be wrong. You know? And so there's so many reasons, like there's so many reasons behind it. Like I gave you the example earlier on of like, if you don't like the prompts are in position the right way, then it might respond in a different way than you want it to. And so there is that expectation setting. And that's why I think that experience agent to human is critical because you need to make it easy that someone can go, Oh, actually, you know what?

I just want to go through to the human. How have you gone about creating the guard rails beyond just the, here's the content to pull from. But as, especially as we think about the more like empathetic skillset of the agents, how do you like set values in place with the agent and how have you made those decisions around what to train it on? It's interesting actually. We spent a lot of time as a team just thinking about what do we not want it to answer questions

on. And so one example is we have a simple guardrail that you should only answer questions on Salesforce products, which I think every company would do. It's funny, I look at our conversations every day. I go in and read some of the ones and I can see like we have a sediment analysis that runs on our conversations that tells me whether they are positive, neutral or negative. And I can go look at the negative ones and see what it was.

And so like some of the negative ones, people ask like, how do I cook pasta? And so like agent force didn't respond. And I'm like, wow. Like, and I think it's because like, people think chat GPT. And so they want to go ask it anything. And like, no, we've confined it into the world of please don't answer anything. Just answer questions related to Salesforce. You know, so that was one, it seems obvious, but like that's a, that's a design choice. If you want, you could give like these things access to the internet and say, hey, go answer all of these things.

Other things that was funny, like we were sitting down going, God, we don't want it to try answer questions on Mark Benioff. We don't want people to be asking questions about our CEO. And it comes back and says, you know, because that's not ours. It's a support person. It's a support site. That's not what it should be for. So we set guardrails. If someone asks about one of our leadership team, it will point them to

our investor relations page, you know? So it's really interesting. Like it's, it's an exercise you need to do with your team. Where do I want it to answer? And then probably more importantly, where do you not want it to answer? And I think that that's, you know, it's one of those steps that has to be talked about before implementing. So many companies want to just dive right in. But yeah, this is one of those things.

It's like, make sure your data is clean and then also be aligned on where you want this agent to play and where the boundary is. Where's the fence to the playground? Totally. And the other thing I'd say, Lauren, is like companies kind of treat it like a traditional software release, right? Like, hey, we're going to go do all this work and go to bang, release this thing. And like, it's not a one and done. It's a constant refinement. It's a constant looking at the performance.

Why was it doing things this way? Like did we not have content for that? Do we need to adjust our prompts? Because like we said earlier, it's an employee, right? And it's grown, it's getting better all the time. Like ours is far from perfect right now. It'll get better and better and better over time. So you've got to be thinking like that.

It's not an old school traditional software release. It's a digital employee and you've got to be constantly refining it. I feel like this is a perfect segue, knowing the timing that we have left into more of that, like the closing the loop between sales marketing, CX. Because right now it feels like we're entering into a different world when it comes to businesses. And it used to just be, you know, you've got your awareness, top of funnel, your customer comes in, you sell to them, hopefully retain them. Customer support is sometimes, you know, either in the middle of that or at the end, depending.

Now it feels like everything's kind of merging together and more conversations have to be happening between these teams. Like you just mentioned, Bernard, when people have an issue, you might want to come back and change the model. Okay, this happened over here when someone was coming into the flow. This now needs to be adjusted. How do you see the world going forward with this cross-functional collaboration space

that we're in? Every company in the world has this problem of they show their silos to their customers. You have marketing that's all about lead gen and how are we driving the pipe, et cetera, and okay, now you have sales, we're gonna create that and we have a customer. Now you kind of have your post sales function,

support, success, and they tend to be siloed. And suddenly you now have this agentic layer that goes across all of them. So an example of that is I see with companies that they struggle to pass the relevant information between the different departments. I'll give you a very simple example. Sometimes a success team doesn't have the relevant information of why the customer bought the product. What do I mean by that? Sales sold it for a certain reason, right?

They sat in a room and said, hey, you buy this product and it's going to give you this feature, it's going to give you this ROI. They sell and they're gone. I'm not, this is not Salesforce, by the way. I'm just saying this is what a lot of companies tend to think about it, right? Seen it many times. Yeah, yeah, right? And then suddenly it's like customers are okay. Like, and so your success team needs that information, right?

So that they can now figure out, how do I do a tailor onboard for Lauren to make sure that she gets that value of why we sold it, right, or why we marketed it originally, right? And so now you have this agentic layer across the mall that's able to see all of this data. It's able to see what did marketing do? Why did we sell it?

What was the business outcomes the customer said they wanted? And now I can tailor. Like we get really excited with agents is that today our agents really about the support persona, but we're going to light up these other personas like a success manager, right? It would help you with your onboarding, right? Even today our agent's text,

we're getting ready to launch voice, right? Which is pretty incredible. Our agent would ring you and say, hey, you know, I see you just signed up for Salesforce. I see you bought it for these reasons. I'm here to help you onboard. Let's schedule an onboarding session. You know, like that's something today

that not every customer might get because maybe they're a smaller customer, something like that. So suddenly these agents gives you this ability, this digital workforce to do all of that at huge scale. It seems like too, this is an amazing time for like CX leaders and marketing leaders all to also be at the product leader table,

to be able to influence products that are being developed because they have a lot more Intel and everyone's going to know more about the customer and more about what sold them and why they're excited about that than ever. And so it seems like it's just there's going to be a lot of collaboration opportunities that bring marketers and CX and other leaders to a table that maybe they were not really at previously. Totally. And one of the conversations we've been having Stephanie is like, I think the danger with some companies is you could go create agents for all of them divisions. You can have a sales agent, a marketing agent, a support agent. And for us, we want to make sure when our customers experience its agent force, right? So it's one agent, but it might

be behind it, you have an army of agents that are skilled in certain things. You could have a renewal agent, a success agent, a sales agent, a support agent, but depending on what you ask it, it brings the relevant agent into the conversations. And for the customer, I'm just talking to agent force in my world, the companies will call it different things. I'm just talking to that company's agent. I don't realize there's all these different agents behind it. So he suddenly, because what companies do today is like they showed our organizational seams, right? I always like my example with this

is portals, right? Companies will have a support portal. They'll have a, you know, sales portal and they've all in Salesforce, we did it and we're working to try and bring all of them together. The danger is you do that with agents as well. You build all of these separate agents versus leveraging the capability that it can work across at all. So then we have to train our agents to be cross-functional. That's what I'm wondering, how? Like how Lauren, do you train these agents and people to think differently about building

this structure when you're like, okay, don't learn, don't think about anything I've ever learned before. Now think different, do different. Like how do you do that? You can still have, so you still have like your, your subject matter expertise and your company should still build your sales agent, you know, and still have so you still have like your your subject matter expertise and your company should still build your sales agent, you know, and your support team should support. But what you have with agent forces, we have this a this agent to agent transfer.

And so what it should do is based on the questions Stephanie asks it. So let's say like you ask it like maybe you have a licensing question or a pre sales type question in that scenario, agent force is able to recognize that question is related to this domain. I'm going to bring in this agent to answer that question. It's more about the technology, recognizing what the customer's intent is, and then bringing the relevant agent into that conversation. OK, that feels a little easier. So instead of me being like, oh, I have a, this feels like it's a customer support question.

I don't need to know that as the customer. I just need to go be like, help SOS. This is what I need. Blah, blah, blah. I'll just voice it into the system and then behind the scenes they'll know like, oh, actually that's a finance thing. She's having problems. Coming back to if we're using structured data and let's say you are a customer, right?

And you're logged on. We're then able to start to use some of this information as well to know what we should come back with, right? Like maybe we can see, okay, Stephanie's day two with our product, right? She's on-boarding, right? We need to use our on-boarding aids. So there's ways we can use our structured data as well, like to help us and understand where you are in your journey and what you're trying to do.

I just wanted to bring it back to a real life example here that this is a real life problem that this is solving. When we call up a number and we wait on hold and then we get through and we end up being on the wrong number and then they're like, oh, let's transfer you to this other place and you can wait on hold over there again, which is the most frustrating thing in the world. And this is the beauty of agentic AI is that the consumer or the customer no longer needs to deal with that because the AI knows what it is that we're asking for and can directly put us in touch with the right agent

where we don't have to wait on hold because. Totally, totally and it knows who you are, Lauren. That's the most important. It knows who you are and it's tailored that experience based on who you are. I'm very excited by this. I was just on a chat line with Adobe trying to cancel my like crazy enterprise account that I accidentally signed up for two years ago and I still don't even know if it's canceled. I was on with like four different chat bots and they kept being like,

but actually, do you want to buy this thing? I'm like, no. And then I come back to it and be like, oh, that never got canceled four times. And I think it's still a problem. And they didn't know enough information about me. And they kept asking me stuff. I'm like, I don't know. I think you should know this. I think I'm your customer. You should know this.

So they probably do, but they just don't want you to cancel. They don't have agent force yet. It's a problem. So I wanted to talk a little bit about the impact on the humans in the loop here and how this is, I mean, obviously AI is having a huge impact on business and with new employees, these AI employees, it's going to impact the existing employees. And the thing I keep coming back to is what are the skills we need to be learning to really

work with AI now that we have these new types of friends that we're working with day in and day out? It's interesting. So one of the things I'll come to your question in a minute, but just I think one of the other things is this like fear of what to kind of do for my job, et cetera. And so one of the things we've been really trying to do is like with our support engineers is making sure they're part of our agent force launch. So we use our support engineers to look at the performance of agent force to help go actually, what would you have done that in that scenario? Because they have more expertise in our products than anyone else in the company,

maybe outside our engineering team. So since day one, we've included our support engineers so that they feel really part of it. And hopefully it takes away some of the volume that's probably easier for them. And they're left with the more complex scenarios. We're always going to need like incredible support engineers. So that's the first thing I'd say. On your question, it's been interesting. I was having this conversation with my team today.

We just hired a prompt designer slash engineer. And you know that role, I don't know how far back you go, but it didn't exist. There was no such thing. Right. Like, you know, and so I was even laughing with I was super curious on what type of applicants we will get. I was like, God, this really have I know when people put like 20 years experience or something and there's no possibility of 20 years experience.

So I was like, I wonder like who's going to apply for this. We actually got a rock star. I can't wait for her to start. But like to your point, there's these new roles starting now. We have a director of our LLM operations. You'd have told me two years ago, I'd have a director of LLM operations. I'd be like, what are you talking about? Is this English you're speaking? And so I do think it's up to people to be start training on some of these, like depending on what your interest is, like, you know, UX designers, there's now this prompt design, which is a new flavor of UX design, you know, and then there's understanding these models and more about them.

So I think it's it's really exciting. And I said it to my team is like, wow, look at us, we're blazing a trail, we're creating these new opportunities. There's opportunities for existing people in my team, we're getting more deeper into it, it might create new roles for them. So it's kind of cool, to be honest with you, on some of these roles that are opening up. Yeah. I mean, with any technological innovation, new roles have been created. And of course, right now, a lot of people are afraid, oh, is AI going to take my job? And as you know, your job to be today, probably in some cases, but there's going to be whole

new jobs, whole new careers, whole new departments maybe that are even created. I know I've been talking to a lot of people about the new role of the AI manager, the agent manager. Like as a human needs to now manage this team of agents and train them and guide them and coach them. Yeah, and I think your point is I feel in a lot of situations they augment the human. You know, I was just on a call earlier today. I have a team, a video production team. So we have a Salesforce support YouTube channel. It's an amazing use, like the second fastest growing YouTube channel in Salesforce. And we have

a lot of things happening in Salesforce, which shows you like how much it's grown. But they were talking to me now about how they're using AI for their video scripts, you know, and something that would have normally taken, you know, hours and days is now taking minutes, you know, so it's not that it's replacing their role, it's allowing us to go faster and to implement more videos at a quicker timeframe. And so that's great because it means we're getting more out there for our customers to self serve on.

So I think you'll see more examples like that where it's like, it's augmenting my job. It's allowing me to be more efficient at my job. And then it frees up time for more valuable activities as well. I mean, I think about, especially in the realm of customer success, if we can spend more time listening to and thinking about our customer instead of doing operational, you know, scheduling meetings and things like that, that just like eats up our time, we're much better off thinking about our customers,

spending time with our customer, listening to our customer, and then bringing that insight back into the organization. Because those human-to-human interactions, that is what AI will definitely never be able to replace, right? So let's lean into that. So one of my favorite questions that I ask of all my marketing trends guests, who are all normally CMOs of the Fortune 500, Fortune 1000 is what's something that you believe that very few agree with you on?

I love this question, but I'm going to steal this question and I'm going to use it with people and I'm interviewing them because then I think you'll see how our brain thinks. I have to think about this a lot, by the way. So kudos to you. You had me kind of like, oh my God, what will I say to this one? The thing I landed on is like, I don't think data is everything. And I think a lot of leaders in marketing, support, whatever it is, they just live in data.

Now, I live in data. I look at data all the time, but sometimes I think the best decision goes against what data tells you. And so like I always push my team is just because our data is telling us something. Like, is that really what's happening? It doesn't often tell you the why and the why someone chose to do something, the why they made that decision, the why they went that way. And so I challenge people. Of course, you should have data.

Data is foundational to everything you do. I live in scorecards and metrics, but I really challenge people, of course you should have data. Data is foundational to everything you do. I live in scorecards and metrics, but I really challenge people. Sometimes it's about going with your good instinct, you know, and saying, hey, no, I think this is the right idea. I've been doing this for a long time. I'm going to go against the data and I'm going to try to do something myself. Have you done this recently? I'd love to hear a story if there is something that comes up around this. I don't know if I have a perfect example, but even coming back to agent force, like, you know, data probably should have said don't release agent force to the whole world at once, right?

Like it's doing an okay performance or resolution rate is X or whatever, you know, you look at the data and you're like, let's just continue to go slow. Let's just iterate and over time we'll get it better and better and better and then we'll go large. And if I'd have made that decision, I don't think we would be where we are now. Because we went big, even when the data told us it wasn't doing an amazing job, it was doing a good job, it meant that suddenly it was exposed to more people and there was more pressure on me and my team to make it better faster.

And so that's like, that's an in like where it was like, it forced us to go faster by going against the data and releasing it to everybody. I think about this often. I'm so glad that you share this take or this opinion Bernard, because going back again to what AI will not be able to replace, it's our intuition. And it is so important that we hold on to that intuition. And if anything, strengthen it now that we have AI doing a lot of the logical thinking for us, where we can say, is this right?

Just because the data says it doesn't mean that we need to do it that way. It is insight, it is information. We can take that, but we still need to use our human critical thinking skills to decide is this the right way to go. Totally. And your intuition is built up over years of decisions, bad decisions, things that went wrong. And so AI doesn't have that. And so sometimes your human instinct is the best way to go. And it's the best way to go. Yeah, AI probably a lot of times has all the risks

that have ever happened in how many years it's been tracking data. And I think what's amazing about humans is being like, I'm gonna do it anyways. And that's actually where most of the breakthroughs have happened, the biggest companies, the most life-changing things is like, yes, it's showing me this might be a terrible idea to do

based off these things. And I'm to send a rocket to space anyways. Yeah, exactly. Right? No, it's a great, no, you're crazy. Right? Why would you do that? People are going to die. Yeah. Have you changed how you lead your team at all? Now that AI is such a big part of your day to day. I think it's a lot of my focus right now. And I actually kind of worry a little bit that I spend so much time here. Like my team has lots of other elements.

Like I talked about like our YouTube channel, I manage all of our email campaigns for onboarding. And it's just like a ton of things to my team. And I worry actually a little bit that I'm so much of my time as an agent force that people that aren't working on it in my team feel like they're not working on the big shiny thing. And so it's about prioritizing my time and making sure I'm still spending times in other areas so that they can see that it's still, because it's not all agent force, you know, we've lots of other things we do that's super

important. I think that the AI hype cycle definitely has a lot of people's attention at the moment, but it's really important to remember that it's not everything. It's the shiny new thing, but there's still a lot else. Although I do tell my team, I think everything that we do today will change. Even if we go in that example of we send emails to customers, hey, you know, you bought Salesforce. You should do these things like and it feels so 1980s now, you know, and like you can imagine a world, like I said earlier, proactive agent, right, that's looking at signals and saying, oh, Stephanie hasn't turned on this feature yet, you know, and it either reaches out in text or voice or, you know what I mean? And so like it all becomes automated.

So like I do think everything we do today will change. I think some things will change completely. Other things will augment. Other things will be a little bit different, you know, and so, but I think everything will change. It's it's kind of similar to that quote, whereas like if you have a hammer, everything you see is a nail. And that's kind of what I see with everything right now.

I'm like, I do think I will be in many of these things and they will be completely different. And so I'm kind of like seeing everything as a nail, like everything can be disrupted and it's amazing. And what a great future we get to live in with like all the things we don't have to do anymore when this comes to me. Yeah. Like how much do we use chat GPT now in your daily life?

You know, I mean, on that point, I actually have a question for both of you, which is what is your favorite personal use case of AI? Yeah, no, I have a good one because someone actually shared it with me was we're going on spring break vacation in a few weeks. And someone shared to me about like actually putting into chat GPT where you're going on vacation, who you're going with. I have an eight year old son. These are the things I like, et cetera, et vacation, who you're going with. I have an eight year old son. These are the things I like, et cetera, et cetera, et cetera. Here's how I'm going to be here.

Here's the food we like to eat. And it gave me a tailored inventory of what I should do on my holiday. And I was like, wow, like some of this is really cool. Not saying we're going to do everything on it. I want to relax at some point as well. But like, what a cool use case, you know, of like being able to get that inventory of what to do. Yeah. Oh, that one's way more fun because I'm like, what a cool use case, you know, of like being able to get that inventory of what to do. Yeah. Oh, that one's way more fun because I'm like, I think about the stuff that I'm

in now and I'm still it's still so work related, but I love having it just like poke holes in anything I'm doing. So if I'm, for example, coming up with, you know, some questions for an interview with Bernard and uploading the whole document and being like, pretend you're like a top podcast host and tell me which questions are gonna result in a lame answer and which ones are gonna go nowhere and which ones are more thought-provoking and contrarian

and I keep making it poke and then I get a new one and I'm like, now look at this one and tear it apart and pretend you're a CMO. What won't resonate with you? What parts don't you care about? Basically be really aggressive with everything I'm giving you and it just, I feel like gives me such good output by saying, pretend to be this like cutthroat killer in the podcast industry.

I'm like, ah, OK, this is great. I'll give you a good one, Stephanie, because I know you have kids that someone shared with me recently is they were at home and it was a rainy day in Seattle. And they asked chat GPT and it gave them games to play in the house with their children and that they have never played before. Oh, I love that. Especially if I could say like, here's the things that I have.

I've got this random tree you can climb. I have, you know, oh, that's a good one. I love that. I'm stealing that for all four of my kids. There you go. Pairings in 101. I know. I'm taking it.

It's hot tips. Yeah. Pairings in 101 from Bernard here. There you go. I'm taking it. It's hot tips. Yeah. Well, Bernard, we have one question that we ask all of our guests on this show to close it out. And that question is, what is one piece of advice that every customer experience leader should hear? Oh, that's an easy one for me because I talk about this a lot. I don't think the word customer obsession, I find people say them words and they don't really mean it. Like it's like, it sounds good. It's a nice thing to write on the wall,

but like you got to be spending time even in the digital space, right? Like agent force, a good example, like I read every day some transcripts from agent force, the ones that were bad, right? I'm meeting with customers. I'm meeting with our NVPs who give very critical feedback on like, what should we be doing different? How do we make it better? And so like, I think to be truly customer obsessed, you have to be looking at your calendar and going, how many hours a week am I actually talking to customers or reading something that was interaction with them? That's what it means. And I just think if you're in the world of CX, that is critical to anything you do. And it goes back to the data point you made.

It's not just the data. We have to actually have those conversations, really be there with our customer, listening to them, understanding what's the need behind their need and digging deeper with our questions. So I could not agree more. Thank you so much. This was awesome. Thank you so much. This was awesome.

Thank you all for letting me jump in and being in this conversation. Super fun and excited to run it on Marketing Trends as well. Thanks, Bernard. Yeah, great to meet you both.