2024 is the year AI at work gets real.
According to LinkedIn‘s Work Trend Index on the State of AI, most business leaders say “they wouldn’t hire someone without AI skills. But with many leaders worried their company lacks an AI vision, and employees bringing their own AI tools to work, leaders have reached the hard part of any tech disruption: moving from experimentation to tangible business impact.”
TruSummit Solutions is committed to helping you maximize Salesforce AI in your organization. In this first of a three-part series on Salesforce AI, TruSummit’s Solutions Director Danielle Nelson explores the foundations of Salesforce AI, including basic readiness assessments and a path to securing executive buy-in for your AI initiatives.
Watch the full recap below and follow us on LinkedIn for our next Salesforce AI LinkedIn Live session.
TRANSCRIPT:
Speaker 1 (00:01):
All right. Okay.
Speaker 2 (00:08):
We are live. I’m just double checking another monitor here to make sure that we are good to go. Bear with us guests that are joining. Let me see what’s going on here.
Speaker 1 (00:34):
Okay.
Speaker 2 (00:34):
There we are. We are live. We’re good to go.
(00:39)
Hey everybody. Thank you for joining today. I am Becky White, Director of Marketing at TruSummit Solutions, and I’m joined by Danielle Nelson, our Director of Solutions. And we are here for our first ever LinkedIn Live. We are so, so excited and also so trepidatious. We are fully expecting some bumps in the road as we navigate this journey to a LinkedIn Live today, but we fully expect that there’s going to be some bumps in the road to your Salesforce AI journey as well. And that is why we are here to talk to you about the foundational aspects of getting to know Salesforce ai. We have a brief presentation, a couple of slides that Danielle is going to walk you through. We really want to keep this as informal and conversational as possible, so we’ll encourage you to leave comments and questions in the LinkedIn feed. We are monitoring it. If you see me moving around, I’ve got Command Central here with several monitors, laptops, everything at the ready. But go ahead, leave your comments, questions, and we want to make sure that we make this as impactful for you for the next 25, 30 minutes. So I’m going to turn it over to Danielle and we will start sharing our slides. And Danielle, take it away.
Speaker 3 (01:53):
Hi, how are you doing? Are you seeing my slide, Becky? Everything Okay. I’m
Speaker 2 (01:58):
In that upper third.
Speaker 1 (02:00):
Okay.
Speaker 2 (02:02):
But we will, yep, we’re good to go.
Speaker 3 (02:04):
Okay, perfect. Hey everyone, good to be talking with you. I can’t see you, but great to see you. And so just want to introduce you to myself, Danielle. I’m the Solutions Director here at TruSummit Solutions. I’ve been in the Salesforce ecosphere for about 20 years. Spent the first half of that as an end user and on the business side, and then spent the last half consulting and working with folks like you from a TruSummit perspective. We were founded in 2020 by the great Jordan Joltes, and we’re headquartered out of Pennsylvania. And one of the biggest things that we think about is how do we enable our customers on the Salesforce platform in ways that add value to them in ways that you are getting the most value out of your technology spend in thinking about what’s coming up next, which is why we’re talking about Salesforce AI today.
(02:59)
So as we think about today’s session, just to give you kind of a roadmap in terms of what we’re going to talk about today, we’ll do a quick AI breakdown, just general, let’s talk about artificial intelligence. We will talk about some stats, interesting information that was recently released about generative ai. We’ll do a breakdown of Einstein tools. There’s a lot out there. It can get confusing, but we’ll talk through each of the different use cases and what that means from a value add perspective. We’ll talk a little bit about readiness. How do we know that you’re ready for Salesforce Einstein capabilities? And then think a little bit about executive buy-in, as we know from a platform perspective, any change or modification you make into the platform, you want that buy-in from the top down so that you do get the most value from the development that you’re doing. And then we’ll talk about what’s coming up next. So if we think about artificial intelligence, it starts with us, the human element, the data we provide, our actions, the context in which we’re doing those actions and providing that data and the norms, our societal norms, our business norms all compile to provide capabilities from an artificial intelligence perspective like predictive analytics. So when we think about predictive analytics, it’s really using that historical data and information to provide informed predictions about future events.
(04:38)
It is widely used. I don’t think I need to speak more about it because everyone’s like, yeah, duh, know that. And then we think about generative ai, right? This is less about prediction and more about creation, right? Creating new data chat, GBT, mid journey content and information that really mimics the patterns found in training data, generally used in creative fields, but also has definite business access as well. And then we think about diagnostic analytics. So this is really helping organizations understand and realize any reasons for past events by identifying anomalies and patterns and historical data, starting to think about root cause details to support better and brighter in the future. And then we think about prescriptive analytics. Again, we’re going beyond predicting, beyond generating, and really saying, okay, now that I’ve got all of this information, what are the recommended actions that I should take to achieve those desired results? And again, this is all just kind of general artificial intelligence detail, but when we start to think about Salesforce, a lot of what they’re putting out there is around generative ai. That’s the really exciting stuff. So Salesforce recently released a generative AI statistic detail, and we’ve got a couple points around those stats specifically around world usage. Interesting to note that from a US population perspective, 45% of the US population is using generative AI in some capacity, but we are also from a North America perspective, a dominant player in generative AI from that market perspective.
(06:46)
Interesting stat there. So then if we also think about adoption, so who’s using this? Why are they using it? Are there any differences or nuances that we should be aware of? Absolutely. What we know is that from a statistics perspective, generative AI is predominantly used by younger generations, particularly millennials and Gen Z. But by contrast, we’ve got Gen X and baby boomers who are less likely to use it. And a lot of that less likely reason is really around understanding what it is and how it will impact their life. And how can we take it from this very shiny thing that everyone’s talking about to very tangible outcomes for my day-to-day for my professional life. These are the things that we need to think about when we think about artificial intelligence is how do we communicate and educate folks on what that really means? And then when we think about the evolution of it, there’s a lot of fun toys out there across the board, but when we think how is it going to impact our business day to day, what we know is that there’s a strong trend towards adoption and prioritizing this usage in the workplace.
(08:04)
And as you can see by the stats, two thirds of IT leaders surveyed are prioritizing this within the next 18 months. And 33% have said it’s a top priority. And so that’s why we’re having these conversations, and that’s why it’s important to really understand how do you know if you’re ready or not? What do you need to do to get ready and how is it going to add and maximize the value that you’re getting from the platform, which is what we’ll go into next.
Speaker 2 (08:31):
There’s another stat, Danielle, that I’ve been really kind of harnessing and using a lot lately. And in fact, I think I even used it in the promotion of this webinar, which came from LinkedIn’s Work Trend Index report, which was just released I think two months ago. And that stat is that 80% of business leaders agree that AI adoption is critical to remaining, but only 60% think that their company, but not only, but 60% think that their company lacks a vision and plan to implement. So they know it’s important. They know that business leaders at large know that they need to be tackling it, but they don’t know. They don’t have any confidence that they know how to. And then that complexity is layered in by this concept of BYO ai. So folks just bringing their own AI tools and to what you’re saying here, using their own gen AI tools, the way that they want to maximize their day or do more with their tasks. So it’s really interesting to me that dichotomy
Speaker 3 (09:41):
And that is a great fact. And the reality is it is about education and connection and being able to say, what is this? How can I use it? And how can I connect that to my day to day versus this very obscure black box super cool thing that I don’t know how to use yet. And then on the flip side, knowing that probably team members on your team today are using some sort of capability outside the bounds of your business organization and your business technology. And so I think a lot about AI tools being similar to how we had that communication tool resurgence over the last number of years. So where does Slack fallen versus teams versus chatter versus all of ’em are doing very similar things in terms of that capability of direct messaging and group messaging, but they have different purposes and reasons. And I think that’s the same with artificial intelligence capabilities, is knowing when to use it, why to use it, and what value am I going to get from it.
Speaker 2 (10:51):
So tell us all of that then. Yes. So
Speaker 3 (10:56):
When we think about Salesforce AI tools, and I apologize, what you’re about to see on the screen is going to be an eye chart. There’s a lot, there’s a lot going on. And what we try to do today is really kind of compile information so you get an understanding of and flavor of all of the different ways that you could leverage the Salesforce AI capabilities across your different functional areas. So when we think about that top of funnel, we’re thinking about marketing. So how do I expand my prospect base? How do I start to prioritize or think about better prioritization of prospects and customer relationships? How do I grow and expand that and that there’s a ton of AI enabled tools for that using the Einstein one platform. And so from a marketing perspective, we think about utilizing event thinkers and real time affinity profiles, tailoring interactions based on customer behavior.
(11:55)
Remember when we talked about there’s that human interaction component, being able to leverage the data and information that’s coming in to again, personalize that communication, those interactions and getting them at the right moment in their buying behavior. Also, from a marketing to sales perspective, implementing AI scoring in key account identification, there’s a ton of market space out there. How do you prioritize the high value prospects and focus and hone your efforts on what are the most promising opportunities that you absolutely need to start doing with this kind of scoring capability and that much better with the artificial intelligence component there? And then really starting to segment your customers, right? Segmentation of customers has been going on forever. And Becky, you’re in marketing so you know this, but how do you do it without having to basically brute force that segmentation, build your own models in terms of those marketing campaigns?
(13:01)
Think about lookalike modeling. These are things that we have been trying to do in that technology investment and spend perspective for a while. Why use your time doing this with root force when you can use automation and intelligence to get you there? And so when we think about that next step in the process, we think about sales, sales. We’re constantly in communication with our opportunities with our customers. How do we in this day and age, personalize emails, personalized interactions without having to spend minutes and hours on follow-ups and thinking about how I tailor every interaction from my prospecting client because that’s what’s expected today, is that me, and thus any interaction you have with me is going to be about me. And so really thinking about how do we use the data that’s already there, the actions that are already there, the information and context and norms to provide that detail and generate that kind of communication pattern without me having to really do that heavy lifting.
(14:17)
There’s always going to be a point for human interaction. This is also critical, right? Is you definitely want to not lose sight of that, but also start to think about what are the low value items that I can sweep from my day to day and then focus more on those high value items. So when we think about the next step in the process, order management, e-commerce. So if you’re using commerce capabilities, really thinking about how do I personalize and again, make very, very specific actions and interactions add value to my customer in that e-commerce and order management process. Thinking about how do I tailor product suggestions? It used to be back in the day you would have these suggested products, so you’d have a product and then here are all my suggested and recommended products, but those were defined by someone in the backend making those determinations versus having data already existing in the system, providing you the very best information in a dynamic way to that customer.
(15:27)
So these are things to think about of number one, are you ready for it from a data perspective? And number two, how can you really start to integrate these capabilities into the different experiences that you might have? And I’m going through these quickly and I know that, and that’s on purpose. There is a lot of great documentation out there on all of these capabilities and tools. And as Salesforce does is they are constantly evolving these. And so I just want to give you a flavor of all the different applications you can have based on that customer experience knowing that these will continue to evolve and there’s a lot deeper detail available to you. So when we go on to service, so we think about all the things we had just talked about. So how do I mind for the most interesting insights from a conversation or from a case, how do I think about connecting dots between what might exist in knowledge and in recommendations in order to close my cases faster?
(16:35)
How do I use the automation capabilities and the AI capabilities to conduct more case deflection? How do I think about the interactions and the different channels people will want to grab support from? They might not want to email, they might not want a phone, they might want to chat. So these are things to think about is your core capabilities of how you support your customers and how can you integrate and immerse the AI capabilities in there to make the job a little bit easier and the experience a heck of a lot better? And then we think about the platform capabilities. We can’t forget the people who are building and making things possible within the platform. How do we start to allow them to be more creative and organic and thinking about things that are disruptive and interesting versus some of the day-to-day. And so Salesforce is offering these platform capabilities from an AI perspective to get us a little bit further down the path in order to continue to construct the needed capabilities and functionality within the platform.
Speaker 2 (17:56):
I’m really struck by with I guess fear for many of my colleagues who on the marketing side anyway, I’m thinking back to previous instances that I’ve worked in or that I’ve managed and thinking about the old garbage in, garbage out adage and okay, wow, you knew you had not great data, not clean data. But that is really going to come to, and I mean that’s going to come to an inflection point now with AI because you truly are not going to be able to leverage the capabilities and maximize what you could do with the AI tools if you don’t have that solid data foundation. Am I right?
Speaker 3 (18:39):
A hundred percent? I mean you can leverage it, it’s just going to be wrong.
(18:45)
You’ll want to really, and that takes me to that readiness indicator is how do you know that I’m ready for Salesforce ai? A lot of these tooling is already enabled based on your licensing, and so I should be able to flip a switch, right? Kind of. So here’s what I think about when I think about the readiness capabilities. First thing I think about is to your point, data preparedness. Do I have the appropriate number of data records? Are those data records accurate, comprehensive? Do they reflect what I would want that large language model to be evaluating? If I do great, I’m in the green, I’m ready to go. Maybe I almost have the number of data records, maybe it’s almost ready, in which case I might have a little work to do when it comes to data. And then if I’m red, I don’t have the right number of records, I don’t have the right data, it’s not comprehensive, it’s not complete and it’s not accurate.
(19:51)
That’s a big red. We need to do something about that. So when we think about how Salesforce looks at it from a readiness indicator perspective, the reason why anchored on number of records is because it will tell you in the last two years how many records do you have that would help this model be enabled and be something that will actually add value. And we’ll talk a little bit about readiness tools in just a minute. The other indicator I think about is use case mapping, right? Can I map those Einstein capabilities, things that I want to do to my strategic objectives from an organization perspective? If I can map it, great. I’m in the green. Am I loosely connected, right? I could get there, maybe if I fudged a little bit, there might be a little work to do or is it super cool, but not sure how it would help our strategic objectives.
(20:51)
That means you’re on the red, you got to think about this. And what I would argue is, and again, I work for True Summit Solutions, I don’t work for Salesforce. However, I do think that the tooling allows for so many different use cases that absolutely you should be able to find some connectivity there. And then when we think about the third indicator, we think about executive buy-in, do I have an executive champion, someone who is informed, interested, onboard for spend, understands the bumps along the way and is able to say, Hey, I’m going to lead the charge. We understood that 67% of IT leaders want to do this in the next 18 months. Do we have that executive champion or am I in the yellow here where I have someone who’s interested, thinks it’s cool, doesn’t really know how to align it, and isn’t ready to really think about the change management and the budget and the timeline for it? Or am I in the red where the executives, my team has acknowledged it said, that sounds great, but it hasn’t really made it to the next step of either education or buy-in into the process.
Speaker 2 (22:12):
And that’s such a great point. And we actually had a comment in the chat about this as well, which is that executives have a tendency because they have so much on their plate to get, they can be overwhelmed by hundred percent the potential scale of this. So let’s say that I’ve got, I feel as the marketing leader, I’ve got my records in a row. I feel that I’ve got my use cases identified and my outcomes identified or my desired outcomes identified, but I don’t have that buy-in. What can I do?
Speaker 3 (22:49):
And I think there’s quite a bit of items that we can do. And so as we go into our next slide and start to think about that transition from someone who has awareness to who that champion is, it’s all about to that person’s point, how do I narrow the field and really prioritize what’s needed for that executive to be able to buy in? So things that I think about that you can do for that is strategic alignment, compelling and material links to core objectives. Can you tie the investment and the time that I’ll have in really building my AI use cases within the system to my core objectives of either growth, retention and process efficiency? Can I make those ties? That’s the first level. The second level in terms of that executive champion is really a give me a vision. It’s so big, so large, I could do a lot of things with it, but how do I start to compartmentalize that and say, I’m going to start here and then I can grow to here and to here and to here and to here.
(23:59)
Starting to think about the long-term view and then narrowing in on your near term, which will give you into your execution. What is a tangible plan for development? What are the costs? What are the impact? What’s the change management? What are things that I need to think about and really plan for as we buy in to the AI capabilities? And what that does for your executives is it really starts to get the folks thinking about what’s the experience impact from a customer view, a partner view, a distributor view a store view, what are those improvements that just by nature of turning on some of these capabilities, we’ll move the dial for ’em. And then also thinking about the tangible value. What’s really hard in challenging sometimes about technology investments is how do you understand and set the baseline for what your return on investment is? How do you quantify what we think we’ll get in terms of dollars and outcomes? And so when we think about that, we’ve got a strategy, and I’m going to go over that in just a minute, around how we change the value statements into dollar statements.
Speaker 2 (25:30):
Sorry, I was not able to unmute myself fast enough, but I wanted to build to that really quickly. And one of the comments again from the same individual, so thank you, Patrick, for commenting, was really about tying all of those elements of gaining executive buy-in together and then deploying potentially a small pilot program. So on the execution, identifying all of that, but then scaling it down and saying, okay, let’s test and learn. And I think that that’s a phrase that most executives will align to is, okay, we’re not going to spin a ton of wheels. We’re not going to spend a ton of cycles, but let’s test. Let’s learn, and then we can adjust accordingly. So love that point. Again, thank you.
Speaker 3 (26:16):
And I think the beauty of the Salesforce platform in general is it is all about that test and learn, right? Start small and then continue to grow, continue to expand your processes, get better, refine. And that actually takes me directly into our value definitions. So I’m going to start with the template that I use when I think about artificial intelligence and I think about the capabilities that it introduces. I think about my mental energy as a human. I can spend my mental energy on low value tasks, or I can spend it on high value tasks. And you’re probably saying, well, duh, Danielle, yes, you want to spend it on a high value test, but let’s take an example. So if we were to go and say just customer relationship management, we have a starting point. The baseline back in the day, and maybe even today, people were using Rolodexes in Excel to manage their customer base, to manage their prospect relationships.
(27:21)
Maybe it’s an email, maybe it’s on a napkin, right? That’s the baseline. What that doesn’t do is it doesn’t give me a lot of time and energy for high value tasks at this point. My low value tasks, I’m measuring data in somewhere. I’m trying to format it appropriately. I’m trying to keep it up to date. Those are low value tasks. And then when we think about that next layer, I’m opening up my mental energy for more high value tasks by driving consistency. So I’m standardizing. So think about moving from the Rolodex into a CRM capability. Now, yes, I still have the data entry. I still need to manage my records, but it frees up my mental energy for just a little bit more of those high value tasks. And then we think about the rationalization stage, the fit and improve. So let’s say the CRM was Salesforce, right?
(28:18)
I’m now able to modify things within the environment. I’m able to have precise data capture through configuration in code. I’m able to fit it and improve it for my industry, for my process, and really kind of personalize it to me. And again, as I’m doing this, I am freeing up my mental energy from those low value tasks to those high value tasks. And then the fourth is automating create, just thinking about innovation. And so when we think about innovation, we think about automated workflows, quick actions, data-driven decision making, being able to use those capabilities within the CRM that I don’t need to think about anymore, and it just naturally plays in and completes on my behalf. And then at the very tippy top, we think about the challenge we want to disrupt. And we don’t mean that in a negative way. We mean it in a like, Hey, now that I have, let’s say an AI capability built in, I’m able to use all of my mental energy for those high value tasks and use the system and the data and the programming for those low value tasks.
(29:33)
And so when we think about the value definition, the way that that starts to come into play is through if we were to take a sales example, so let’s take just a general email, right? From an email perspective, I’m spending some time here figuring out who am I sending this to, what the content is, how I’m going to position things, leaving me very little time to hustle. At this point, I need to just continue to grow my market share. Now I’ve introduced an email template, I’ve expanded my reach, I have a little bit more time and room for high value tests, but I’m still choosing a template, figuring out what to add in there. And then we think about data-driven email templates, right? At this point, I’ve got the template. It’s using data that I’ve entered into the CRM and now it’s a little bit less of my time, and I’m able to really start to think about how do I build relationships, long lasting relationships with my customers.
(30:40)
And then when we think about automations and triggers, thinking about those workflows and those specific data elements, that will trigger an email. Again, I have to program that, but it leaves a little bit more time for me to do things like strategic account planning. I think this is one I’ve heard a lot is I want to be able to really land and expand from a customer basis perspective, but I have no time. I need to just continue to be hustling. That’s where the technology and the tool capability really help free up that mental energy for those high value tasks. And then we think about Einstein copilot, what we just talked about. Not only do you have the automation, you have the triggers, you have the data, you have the predictive capabilities and the prescriptive capabilities, but you can really start to think about how do I move some of those other low value tasks to the Einstein copilot so that I can really start to disrupt from a market perspective?
(31:43)
I can start to explore previously unexplored markets and grow segments from a strategy and execution perspective and really focus on what’s going to have high value outcomes versus low value tests. But you’re asking yourself probably at this point, well, what does that mean though in terms of dollars? You said dollars. How are we going to get something from a qualitative state into a quantitative state? And so same example that I’m using, I think about an email. It probably takes someone about 10 minutes to do that front and back in assuming that their salary is a dollar a minute. And I’m going to say, Hey, it costs me $10 Now for every email that’s sent out, if I introduce a Salesforce email template, okay, I’ve probably saved myself about three minutes. And so I’ve got a cost saving of $3 data-driven email templates. I still have to program it.
(32:38)
I still have to monitor it, I still have to have the data in there. So I’m going to say it takes me about five minutes. So I’m saving $5. And then with the email automation and triggers, got to still program it, but probably about two minutes to get that to done. Now I’ve got $8 shaved off of that initial $10. Now imagine a scenario in which I didn’t really have to think about it. It took seconds instead of minutes. Now I’ve saved that $10. I’m making a little bit of an embellishment there, right? But now, if I were to think about it holistically from a scale perspective, and I had a hundred salespeople for that same email, I’m now at a cost savings of a thousand dollars. And again, these are wide sweeping generalizations. My recommendation is you start to think about it, you start to track these KPIs and then figure out, hey, what is the use case and what is the benefit? And what could I do in terms of those overall dollars to donuts in terms of savings?
Speaker 2 (33:41):
And every marketing and salesperson is now like, okay, yes, do it. Let’s do it all. Turn it on, turn it on, toggle the switch.
Speaker 3 (33:52):
But that’s not all.
Speaker 2 (33:54):
There’s more.
Speaker 3 (33:56):
There’s more. And so when we start to think about not only just the dollar, the process efficiencies in terms of gain, what if you don’t do it? What if you say, you know what? I don’t mind spending $7 on an email, or I don’t mind being there at the $2 mark. What is the cost of inaction? What happens if I don’t do this? When I think about that initial email, well, probably nothing really matters, but hey, I’ve now, from an email template perspective, I’ve reduced my ability to grow. I don’t have data-driven email templates, which means I’m not personalizing my email information and there might be an inaccuracy. So I’d have an increased rate of turnover from an email automation trigger. You’re not personalizing, you’re not communicating directly to me, you are making it about you more attrition, higher attrition, and then not exploring or not having the ability to explore markets and additional segments from a growth and strategy perspective.
(35:03)
Net new expansion goes down. And so again, you can quantify those, put dollars to it, but I think there’s two sides of this coin is the cost of more efficient and effective productivity and the ability to focus on high value tests. And then there’s the cost of not doing anything. So simply by staying stagnant as your competitors and as your different businesses continue to grow and act upon this, you are now going lower and lower in terms of your ability from a value perspective on the platform and your ability to dynamically change for the marketplace. So when we think about the value exercise, it’s a very, very small use case. It’s an email template, but as you can see, you can see how you start to build that value use case for your executive. And as we talked about before, taking that value add and then being able to articulate, Hey, this is what we can do from a pilot perspective. This is what we can do just to get some immediate gains. And this is maybe a long-term roadmap that will have substantial savings and or gains based on the direction that you go with your artificial intelligence strategy.
Speaker 2 (36:29):
We had another really fantastic comment in the chat, and it was about the overcoming the inherent feeling of lack of control in the examples that you’re providing. And so all of a sudden when we’re letting the machine do it and potentially do it better than us, that’s a scary thing. And so there’s this change management component or aspect of this whole conversation that has to take place from just a people perspective of assurance, assuaging concerns, explaining the education factor because that loss of control is scary. And self-appointed control freak, I can completely say that 100%, although this comment came from the chat, not from me. But yes, I can definitely see that there’s this whole other element too of education and change management within the org
Speaker 3 (37:27):
A hundred percent. And I like the way that you said it assurance, right? And that’s why when we’re talking about artificial intelligence capabilities and that Salesforce offers, and again, there’s a lot of documentation and we could provide that maybe after today’s session around that Einstein trust layer around the fact that there are bumpers and boundaries to this capability. But I also think there is a certain extent of the proof is in the pudding, right? You got to turn on, you have to see, you have to refine, and then you continue to see, and that’s how you build trust is the recognition that it’s not going to be day one turned on and a hundred percent solving all the problems. No technology is going to do that for you. It’s more let’s turn it on, let’s evaluate it, let’s refine it, and let’s keep moving forward. And again, this is one of three sessions. And so I love that is from a change management perspective, how do you include people in the conversation? How do you make sure that they understand this isn’t about obsolescence, but more about evolution. What more can you do during your day that is a high value task than doing these kind of incremental, more manual, more low value tasks? And that’s the message I would go with is what more interesting things could you be doing and focusing on then this?
(38:57)
So great comment. Really appreciate that. Anything else, Becky?
Speaker 2 (39:01):
No, not on this one.
Speaker 3 (39:04):
Okay, perfect. So as we’ve gone through, we did a quick AI breakdown. We talked about some stats, some interesting information, Einstein tools, readiness indicators, kind of that value mapping for the buy-in, and then next time. So we’re almost at the end of our time here and I would love to have you join us again next time. We’re going to be talking about activating Salesforce ai, so getting more into the tool, doing a little bit more value mapping for marketing service and the platform, and also doing a live demo of Salesforce AI capabilities. As we close out or open this up for more q and a, if you’ve got a use case that you’re interested in that you’re like, Hey, I would like to see you value map this particular use case, put some hard dollars to it, let us know. Post it in the feed and we’ll tackle it next time. I’ll hand it back to you, Becky.
Speaker 2 (40:04):
Awesome, thank you. So if there are any additional comments or questions, you’ve seen me kind of responding in real time in the chat, so I’d love to see those now. But as we wrap up, we do have two quick calls to action in addition to this amazing ticker that’s running across the bottom of your screen. I feel very, very new station, right? Very cable news right now, but we are going to be doing another session in mid July, and during that session, we would love to have the use cases you want to talk about to surface. So feel free to drop those in the chat and we will work on those over the next couple of weeks and get them prepped for the July session.
(40:56)
So we do have an AI Adoption Playbook that you can download. It’s a slightly more in depth version of this presentation, and it’s something that’s a great shareable resource and it gives you just various step-by-step actions to take to really lay that foundation for AI in your org. If you scan this QR code, it will take you directly to the file, no form required, and you can download right away. So I’ll leave this up for just a second and anybody who wants to scan can, or you can of course contact me through LinkedIn and we can sync up to get you that asset. The other thing that we have that’s really, really cool are these AI readiness tools that we’ve been working on and are nearly ready for beta release. And we would love for you all to be our beta testers. So sign up for early access to our AI readiness tool.
(41:48)
Again, you can scan the QR code, it’s going to take you to a really brief form for fields only, and we will follow up directly with you to obviously learn a little bit more about your org and how we can get you the right access to the beta tool. But we’re super, super excited about this and we would love to collaborate with real users out there so that we can make sure that everything that we’re doing is best meeting your needs and your business objectives. So that will be up here for just a second as well. I’m not seeing any other comments or questions in the chat, so I think we’re probably good to wrap up this first ever LinkedIn live virtual high five. We did it. Congratulations, great job. Thanks to everyone for joining and for sticking with us for the conversation. It was a really good one. And we will have a session again, as I mentioned in July, and then a third session in August. We’re doing AI all summer long, so stay tuned. Follow us on LinkedIn to ensure that you get the posts and the updates on the next LinkedIn live. And that’s it. Awesome. Thanks everyone. Have a great Thursday. Take care. Bye.
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