Name: Brainstorm Tech 2024: Salesforce AI CEO Clara Shih on building trust in AI and advancing CRM solutions
Uploaded: 2024-07-16
Duration: 14 min 29 s
Description: Brainstorm Tech 2024: Salesforce CEO Clara Shih on building trust in AI and advancing CRM solutions

Brainstorm Tech 2024: Salesforce CEO Clara Shih on building trust in AI and advancing CRM solutions

Brainstorm Tech 2024: Salesforce AI CEO Clara Shih on building trust in AI and advancing CRM solutions

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Clara Shih, Chief Executive Officer, Salesforce AI  Interviewer: Jeremy Kahn, FORTUNE

Brainstorm Tech 2024: Salesforce AI CEO Clara Shih on building trust in AI 

So Clara, I want to start out by talking a little about trust. Trust has become a really big issue for companies that are hoping to deploy particularly generative A I Solutions. A lot of companies are complaining that they're finding the technology very unreliable. They're getting frustrated because of that. They're afraid to deploy it at scale. And earlier when we were speaking, you said that you felt a lot of A I Solutions have yet to kind of find product market fit. I wonder if you could expand a bit on that and also say, tell us how salesforce is trying to overcome this problem in its own A I solutions. Sure. First of all, thank you so much for having me. It's great to be back um at fortune brainstorm tech. Um So trust is a big topic. Um I'm really proud to share that it's the number one value of sales force and has been since the company started 25 years ago. And um there's trust in the sense of what you describe in terms of, you know, A I hallucinations and um toxic output. And that's why the first thing that we built when we were creating our generative A I products was our Einstein trust layer that has data security, data privacy, ethical guardrails, everything from data masking and citations and an audit trail um to um our toxicity filters, et cetera. Um But there's, there's this broader question of, do we trust A I to drive business outcomes even if I can mitigate the data security, data privacy types of questions. And I think that's where I've seen a lot of companies and customers struggle. And so they come to us and they want to know how they can really deploy these solutions in a way that actually moves the needle for their business because you know, these efforts, they're expensive. And so I think, you know, where salesforce is, we're really well positioned to do this is our customers. You know, many of you in the audience already have their trusted data and their trust, trusted business processes that they've built into salesforce over the years. And so it provides this ideal grounding for the A I to really be to inject in the context that's needed for the models really to be able to perform well, whether it's using it for simple retrieval, augmented generation question answering or as we move into some of these more agentic use cases, interesting, I want to go to questions to the audience sort of try to make this session interactive. So think of your questions and if you put your hand up, I'll try to come to you. But I'm first going to ask Clara, we spoke a little bit about how sometimes like narrowing the use case for the technology is a way that you can actually build up more trust in what the technology can do. And the fact that, you know, for sales force, if you're using Einstein for a particular sales case, you don't have to worry about the fact that it's, you know, it's not going to plan your kid's birthday party, it's not going to write a letter. But can you a little bit more about that? And, and what, what we sort of meant by the idea that if you can pick a more narrow kind of vertical within your business to deploy the technology into and kind of constrain it to that, that, that, you know, that can help with trust. Yeah, I mean, trust is contextual, right? There's a question of, do I trust the A I to help me figure out which customers to call on this quarter to hit my number? Do I trust the A I to help me answer customers' questions through an Einstein service agent so that I can deflect the easier cases and keep my contact center reps for the more complex cases. So those are very specific outcome oriented trust questions. I think it's easier frankly than creating an A I that can do everything, absolutely everything. And I know there's companies doing that. I commend their efforts. But when I talk to businesses, what they want are those specific outcomes, right? How do I really get all of my sellers performing like very top 5% of presidents club sellers. How do I get all of my marketing campaigns to perform like the best ever marketing campaign that I did? And with that context and with the examples in the past, right? Because salesforce isn't just a database of customer data, it's a database of customer outcomes. So we know what worked in the past, what didn't and you can use those examples for both, for both few shot examples, you can use it to fine tune models. And that's really we're able to unlock these tremendous outcomes that we're seeing at everyone from AAA, from insurance to ADP payroll, biggest payroll processor in the world to Heathrow airport, to opentable across a wide variety of industries, geographies and customer segments. Interesting. And at salesforce, I know you've been eating your own dog food, you've been deploying these A I solutions internally as well as selling them to customers. What's the experience been like internally? It's been, you know, we'd like to drink our own martinis to say, but it's bumpy at times. I really like that accountability of us being customer zero because that's how we are able to sell with confidence because we have deployed it internally. So we use everything Einstein internally from deploying self service search answers. So when any of our employees. I had a question the other day about parental leave benefits for I'm trying to hire rather than logging a ticket. I just went to our employee portal. I typed in my natural language question question. It was automatically grounded in who I was, which you know, I'm in the state of California. So was my employee and it gave me the answer all of that powered by the Einstein trust layer at I retire Einstein platform all the way to Slack A I, right. We know a bunch of us took some time off over the fourth of July. We got back to Slack and then we had to catch up on all these channels, conversations, different deals. We're working on Slack A I summarizes it in an instant, right? And so all in, we've saved over 50,000 person hours in productivity by deploying our own A I solutions and other A I solutions for our employees of those various use cases. What's, what do you think has been the most impactful? It depends on the role that someone is in. I mean, I know our sales people, they're using Einstein co pilot to do their account planning and their reach out to their customers, our customer service team, they're getting assistance in the moment to resolve customer issues factor. Instead of having to look up every knowledge article and piece it to the customer, we're able to use data cloud and Einstein to automate a lot of that for me personally. Just given the nature of my work probably Slack A I is what I use every single day. I want to get questions who's got questions for Clara? Please raise your hand and I'll come to you. We've got a question over here down in front. You can just stand up. Thank you. Um I'm just curious because the way you describe how A I is gonna be used for customer service sounds a lot like marketing and marketing begins to sound a lot more like advertising. And you, you describe a lot of things that you see, the major consulting firms do like mckinsey's and accenture's. There's some reports that 20% of their revenue is from digital transformation to A I. Do you think using A I is gonna kind of collapse the roles of those different organizations and how they serve the Fortune 500? I do. I think that A I plus data will allow us to actualize a vision that, you know, predates me at sales force, but it's what we call the customer 360 where instead of shipping our org charts and being limited by what the sales team knows versus what the customer service team knows versus what the marketing team knows. Um We're able to really be customer centric and across every customer touch point, you know, pre sale at the top of the funnel post sale, actually transacting the sale, um, loyalty all of that becomes much more seamless. And we've seen this with some of our customers. I'll just share an example. We work with a global apparel retailer. And during COVID, like many companies, they had trouble hiring and retaining enough contact center reps, but they really wanted to, they weren't able to keep up with, with the volume of requests that were coming in from customers. And so the customer whole time started expanding. And so they came to us, started using our Einstein A I platform. And something amazing happened, which is not only did the resolution time on customer support issues decrease by 15% but they actually started seeing the customer support rep start to play a bigger and broader role. They started to be able to answer sales questions and marketing questions. They actually became brand storytellers and it kind of in me of how in, in the matrix in the movie, you know, Keanu Reeves, you know, gets downloaded um new skills and all of a sudden he knows Kung Fu like that's what we witnessed. And when you talk to these customer service reps, you know, a lot of them feel like they're doing the best work of their careers because they now feel empowered by A I I other other questions for Clara. Uh I see one back there if you can stand up and let us know who you are. Yes, Sterling Audie with uh with Barclays. So as A I starts to incorporate more data from more disparate. So uh sources, some of those sources are not necessarily just in, you know, your cloud. How are you expanding or implementing the trust model to be able to control that as those different data sources are implemented? That is such an important question. I mean data is at the foundation of all A I, right? Good A I good A I depends on good data and something that, that my colleagues did again predates me rejoining the company, but they built something called the sales force Data cloud a few years ago. And what the data cloud does is it, it unifies and harmonizes all of the company's structured and unstructured data across ERP systems. Our CRM of course, other CRM data lakes, data warehouses like snowflakes, data data bricks, big queries. And what we realized was that every company has multiple of these data silos and applications, many multiple of them. But and within these data silos are data that's actually highly relevant to sales people and highly relevant to service people and marketers. So for example, almost every modern company today has a data lake that logs website and mobile activity. So if a customer or prospect goes to your website views product pages that gets logged in a data lake, right? Probably everybody does that. Even legacy companies are doing that now. But the problem is your sales team all aren't logging into your snowflake, right? They don't even know what snowflake is or what data lake that company usually has, but they actually should know because that's a timely signal for them to prioritize and reach out to that particular prospect. And so that's what data cloud does is it unifies and harmonizes these real time signals for use in CRM. And by Einstein A I other questions down here in front. Those are questions. Let's get a mic. No, no, we wait for the mic. Thanks so much. How's it going? Healey Cipher. Uh So you have a company called Boom Pop or an A I travel company. One of the things you have in the room is a bunch of founders who are trying to build A I applications because foundational stuff is kind of like out of reach for us, you know. And so I've been thinking about it a bunch and argued about it with a bunch of friends. It feels like there's kind of three things you can do to have a good A I strategy building an application, proprietary data, just your data, something like a learning platform or Great Uiux. How does that resonate with you? What are we missing? Like if you were sitting here trying to compete on building an application that doesn't get steamrolled by open A I? Like, what do you do? Great question, especially as a former founder myself. I think there's so many pockets of possibility to use A I to completely rethink traditional industries from health care to wealth management, to banking, for example. And I do think that when you think about the traditional model view controller, right? It's the data model and so structured unstructured data. What's proprietary? What are the pockets of unstructured data that traditionally haven't been mined and haven't been use? Because we didn't have to be able to help us analyze it and generate metadata to organize it and understand it definitely. And then being able to create that learning loop, right? The reinforcement learning both from human feedback, expert feedback, as well as from objective outcomes. As I mentioned earlier, you can only get so far with, with RL. But if you have customer outcomes like sales data conversion data, now you can start to create a really powerful flywheel over time. And that can, that needs to be built for every single domain and every single segment. And that's all Greenfield for the types of companies that I would build if I were going out to start today from a U standpoint, I'm not so sure that that is so defensible. I mean, certainly amassing a big user base is important so that you can collect more of that, that human feedback and expert feedback and outcome feedback. But I think a lot of U is going forward are going to be generated themselves. So the companies themselves will design their own U or yeah, think it's like a niche that you could have an outside start up design a co pilot for I think that, well, so first of all, a couple of thoughts, so regarding co pilots, I think that that conversational UI that we are familiar with that is but one of many UIs that are possible with A I and we're going to see more coming just as a teaser. Slack is a phenomenal place for a team of human workers to have conversations with and collaborate with a team of A I and you can build applications on of Slack to take advantage of that. And then I think secondarily is that A I is able to generate pretty compelling user experiences. You mentioned sort of more agentic A I coming along in terms of salesforce. When are we going to see a salesforce agentic system debut? Thank you for teeing me up. We weren't going to announce this until Wednesday, but mark tweeted it. So we've, we've announced Einstein's service agent. It's a continuation of our co pilot platform going from single turn chain to multiple chain orchestration and initially for customer service, but we're going to open it up to all types of CRM applications in the near future. Do you have a timeline on when it might be available? It will be, it will be available in the coming months. It is an active pilot right now with a number of customers including some of the organizations here and we're seeing really promising results so far. Great. Thank you. We're about out of time. But thank you very much Clara for joining us. I really appreciate it and thank you all for listening.