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Speaker 1: Welcome to Fear and Grade Q and A. Will we

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Speaker 1: ask and answer questions about business, investing, economics, politics and more.

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Speaker 1: I'm Sean Alma. In the last few years, dare I

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Speaker 1: say months, enterprise AI has evolved enormously. It's moving beyond

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Speaker 1: the large language models to a focus on agentic AI,

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Speaker 1: and it's not slowing down. Today's episode is recorded as

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Speaker 1: part of the Agent Force World Tour Sydney. Fear and

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Speaker 1: Greed is partnering with Salesforce for this event. Per Luca

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Speaker 1: is the senior vice president of Product Marketing for Agent Force. Sanjna.

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Speaker 1: Welcome to Fear and Greed.

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Speaker 2: Thank you for having me Sea.

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Speaker 1: So I thought the I fine adoption was fast. Wow,

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Speaker 1: that's nothing compared to AI. Why are we adopting it

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Speaker 1: so quickly?

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Speaker 2: You know?

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Speaker 3: I think when there is a delightful experience like getting

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Speaker 3: access to knowledge answering your questions easily, there is It's addictive,

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Speaker 3: you know, folks want access to with it. And I think,

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Speaker 3: you know, I've been in a space for a long

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Speaker 3: time before we were calling it AI. We were calling

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Speaker 3: it big data machine learning, and we just didn't have

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Speaker 3: the tools at the infrastructure level. It's not like you

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Speaker 3: could play around with a predictive AI model the same

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Speaker 3: as chat GPT, and now the access to the democratize

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Speaker 3: everyone can play with this technology.

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Speaker 2: So folks are excited, and.

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Speaker 1: It is exciting because even if you don't think you

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Speaker 1: know much about it, if you try it, it is

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Speaker 1: quite phenomenal what it can do in your everyday life,

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Speaker 1: let alone your work life.

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Speaker 3: Absolutely, and it's just the tip of the iceberg for

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Speaker 3: what we can experience as consumers At Salesforce, right, we're

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Speaker 3: looking to apply these technologies in an enterprise setting to

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Speaker 3: solve business problems. So it just it keeps getting more

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Speaker 3: interesting as you look at that application.

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Speaker 1: Okay, now what does concern me a little bit, Sanchna.

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Speaker 1: Most of us are trying to comprehend exactly what a

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Speaker 1: large language models doing. You're talking about moving beyond that

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Speaker 1: to a more sophisticated agent driven architecture. What does that mean?

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Speaker 2: We have to move fast on. We can't rest on

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Speaker 2: our laurels.

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Speaker 1: Fast to move fast.

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Speaker 3: I mean what we're really talking about here is you

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Speaker 3: can think about LMS as creating what I would call

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Speaker 3: raw intelligence, right, just like the stuff that outcomes are

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Speaker 3: made of behind the scenes, Right, it's helping you generate text,

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Speaker 3: it's trained on the world's information. But for our customers,

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Speaker 3: they're looking at very strict customer outcomes for the folks

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Speaker 3: that they serve every day. So imagine you're a large

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Speaker 3: retail company and LM sound so great because you know,

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Speaker 3: you think about the possibilities of styling for a customer

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Speaker 3: and like a digital concierge. But what about something like

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Speaker 3: orders and returns? Right and LLLM off the shelf doesn't

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Speaker 3: know your return process or your order process at your company.

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Speaker 3: Only you know that, and only your systems know that,

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Speaker 3: and those systems run on salesforce. So we can sort

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Speaker 3: of bring together the business logic, the context the day

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Speaker 3: with the ry intelligence of large language models and create

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Speaker 3: something pretty special that really helps our customers use this

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Speaker 3: technology to drive better outcomes at scale.

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Speaker 1: So what you're alluding to there, which I find really interesting.

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Speaker 1: Sometimes you don't want a yes or no answer, you

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Speaker 1: don't want a perfect response. Other times it's absolutely critical

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Speaker 1: that you have a one hundred percent correct answer yes.

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Speaker 1: How and it's kind of the whole last mile thing

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Speaker 1: where you get a great demo. But how am I

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Speaker 1: ever going to introduce that into my company, right, But

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Speaker 1: I'm just interested in that tension between when it's an order,

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Speaker 1: it's going to be one hundred percent right, can't be

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Speaker 1: out a nine point nine. But if it's an idea

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Speaker 1: of style, it can be somewhere you know about eighty

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Speaker 1: percent good.

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Speaker 2: Absolutely. I mean, let me ask you a question, Sean.

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Speaker 3: Have you ever had this experience where you open up

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Speaker 3: chat Gipt or Gemini and you ask it a question

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Speaker 3: about a brand that you interact with and you're like, Hey,

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Speaker 3: I'm really looking at return this product, how does it work?

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Speaker 3: And it sou it's really nice to you and it

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Speaker 3: says something delightful to you.

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Speaker 2: Yeah, but it's wrong. Have you had that experience?

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Speaker 1: Absolutely, and you know you can abuse it and it's

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Speaker 1: still nice to you, and it's still wrong.

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Speaker 2: It tells me I'm the prettiest girl in school. It

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Speaker 2: loves me. It's amazing.

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Speaker 3: But for businesses, right, if you're thinking about the psychology

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Speaker 3: of the customer experience, right, you can't get that wrong.

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Speaker 3: As you said, you need some sort of control over

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Speaker 3: the experience that elms are providing. And so what we've

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Speaker 3: been working on for the past year and a half

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Speaker 3: really since Agent Force launched is listening to customers seeing

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Speaker 3: what they want to see from us. And it's funny

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Speaker 3: as consumers, we hate chatbots, but people that run service

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Speaker 3: teams kind of love them secretly because it's one hundred

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Speaker 3: percent case deflection for the five things that can answer, right,

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Speaker 3: but for the other ninety five things or nine hundred

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Speaker 3: and five things that a customer might answer, it can't

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Speaker 3: do anything. And so what we've done with agent forces,

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Speaker 3: we've brought sort of the predictability that you get with

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Speaker 3: the ch bot workflow based question and answering with that

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Speaker 3: kind of dynamic nature of an LLLM, the how are

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Speaker 3: you doing today? The let me think of a unique

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Speaker 3: idea for you, and we've brought them together so customers

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Speaker 3: can create experiences that are delightful, are that have that

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Speaker 3: consumer grade fund to them, right, but that also have

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Speaker 3: that control of executing a workflow when necessary, right, returning

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Speaker 3: in order, maybe helping if you look at a regulated

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Speaker 3: industry helping you with your financial planning, right, we don't

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Speaker 3: want to keep that up to chance, right.

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Speaker 1: Yeah, And sosis where governance fits into it, the fact

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Speaker 1: that you can actually put governance over your processes, you know,

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Speaker 1: escalate issues if they know it might be a customer

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Speaker 1: that's very upset. You're escalating that beyond the large language model.

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Speaker 1: Is that I mean architecture, I space is what it's about.

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Speaker 3: Yeah, I mean what I love about this update to

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Speaker 3: our platform. I could geek out on the technical part

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Speaker 3: of it all day long if you've left me, but

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Speaker 3: I know we don't have all day. What I love

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Speaker 3: about it is it actually bringing us back to a

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Speaker 3: very core business question of what is your ideal customer experience?

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Speaker 3: What do you want that person on the other side

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Speaker 3: of the chat to feel and think? And then you

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Speaker 3: can design that agent to do exactly that. Do you

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Speaker 3: want the agent to always introduce itself, you know, ask

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Speaker 3: three of the same questions every single time it interacts

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Speaker 3: with the customer, because it tells them something, it gives

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Speaker 3: them some context. Maybe whenever a customer talks about, you know,

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Speaker 3: anything related to something inside of the store, you invite

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Speaker 3: them in and you book an appointment.

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Speaker 2: Right.

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Speaker 3: They can now create that more reliable and predictable experience

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Speaker 3: using agent forust while still not compromising what's best to

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Speaker 3: read with these lms at creativity that you get with

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Speaker 3: them too.

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Speaker 1: So at the conference, with certainly a bunch of great

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Speaker 1: examples ran. The thing that I still think a lot

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Speaker 1: of companies struggle with is that last mile. Someone comes

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Speaker 1: in and says, Wow, look at this, this is what

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Speaker 1: your business can do. That's fine. Getting someone to get

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Speaker 1: to work on a Monday morning and do something differently

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Speaker 1: so that the agent does what it's supposed to do.

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Speaker 1: That's a really, really tough last mile.

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Speaker 3: You have to bring people along. And you know, there's

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Speaker 3: there's so much. I'd say ninety percent of the chat

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Speaker 3: right now about agents in general is about the plethora

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Speaker 3: of use cases that you can bring to life. But

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Speaker 3: let me tell you that last mile of observability, testing, iteration,

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Speaker 3: making sure that the right people in your organization have

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Speaker 3: access to the right performance metrics of the agent.

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Speaker 2: That's the stuff that is that's the last mile.

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Speaker 3: That's when you go from just a pilot idea or

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Speaker 3: proof of concept into truly transforming your organization.

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Speaker 2: Right.

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Speaker 3: I mean, I'll give you an example. You know, I

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Speaker 3: have a website manager on my team manages websites. He's

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Speaker 3: done it for twenty years. He's an expert, he's fantastic.

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Speaker 3: When we launched Agent forst on our website, something very

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Speaker 3: interesting happened, which is that because the website is his domain,

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Speaker 3: he started paying attention to the different questions people were

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Speaker 3: asking that agent, the utterances as we call them, right,

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Speaker 3: and he started using those as sort of leading indicators

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Speaker 3: to put a strategy in front of me of Hey, Sanjana,

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Speaker 3: you know, people are asking a lot.

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Speaker 2: More questions about pricing than they were six months ago.

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Speaker 3: I think we need these pages, we need this experience,

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Speaker 3: and the agent, we need this SEO strategy. So if

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Speaker 3: I were to reduce it to a role change, my

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Speaker 3: website manager is now an agent manager.

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Speaker 2: And that is cool.

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Speaker 3: I mean those are transformations that are subtle and they're quiet,

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Speaker 3: and they're behind the scenes, but they're impactful.

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Speaker 2: You know, that's what changes an organization.

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Speaker 1: So in that example, the creative ability of your website

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Speaker 1: manager in a sense came to the fore. I'm just wondering,

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Speaker 1: does that mean that it's the creatives. It's the people

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Speaker 1: think outside the box. They the people who potentially do

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Speaker 1: even better simply because they're looking at trends, looking at

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Speaker 1: and while gentik is very good, you still need that

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Speaker 1: kind of outside or human influence.

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Speaker 2: Absolutely.

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Speaker 3: I mean, the best people on your team are going

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Speaker 3: to be the ones that push the envelope, that use

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Speaker 3: new tools, that are constantly reinventing themselves and their role

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Speaker 3: and thinking of new ways to do that. AI is

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Speaker 3: just another way to do that. And I fully understand

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Speaker 3: the fear. So folks are very very fearful of these technologies.

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Speaker 3: But you know, are head of our service practice here

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Speaker 3: at Salesforce Stream Growth. He always talks about this, which

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Speaker 3: is that when we were transforming our own support organization,

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Speaker 3: he's very aware of this fear, and so we've dropped

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Speaker 3: people along and he now has folks that he's reskilled

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Speaker 3: to be prompt engineers that are living inside of the tool,

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Speaker 3: iterating on it, making it better, thinking about the ideal

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Speaker 3: customer experience because they can actually make a greater impact

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Speaker 3: now with these tools, which is a very cool thing

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Speaker 3: to see.

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Speaker 1: It's scared to ask this one, Benja. But okay, sofore

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Speaker 1: we're going to be in three years? I mean, you're

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Speaker 1: beyond large language models. I'm just catching up to that.

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Speaker 1: But way will we be in three years?

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Speaker 2: You know?

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Speaker 3: I think we are just going to be seeing the

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Speaker 3: fruits of our labor right now.

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Speaker 2: We're going to be seeing real returns.

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Speaker 3: Agents aren't going to be maybe that exciting, Like, it's

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Speaker 3: not going to be an exciting thing we talk about.

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Speaker 3: It's going to be, you know, as embedded in our

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Speaker 3: business as pulling up a spreadsheet is or writing a

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Speaker 3: slide deck. Right, It's going to be a tool that

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Speaker 3: we all know how to use and customize. It's going

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Speaker 3: to be more in our vernacular. We're going to be

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Speaker 3: able to understand what's a good use case for an

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Speaker 3: agent and what's not.

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Speaker 2: That's actually the.

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Speaker 3: Most fascinating thing is that the agent conversation has helped

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Speaker 3: re energize every other conversation because not.

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Speaker 2: A reuse case is agentic.

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Speaker 3: And so I think, you know, there's a lot of

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Speaker 3: pressure on us as leaders, as consumers, as just participants

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Speaker 3: in this market to understand this technology, to move ahead,

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Speaker 3: and to really embed it deeply in our teams.

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Speaker 1: Any other example I like in my life time is

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Speaker 1: social media, the introduction of social media. I actually find

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Speaker 1: AI easier than social media because social media, to me,

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Speaker 1: there are certain channels for age groups or demographics or whatever,

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Speaker 1: whereas AI to me seems almost more democratized or something. Right,

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Speaker 1: And maybe it the mergers that's the case. And while

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Speaker 1: some large language models work better for some things, I

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Speaker 1: get all that. Yeah, but it's almost like everyone is

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Speaker 1: at the same level, whereas in social media it's, you.

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Speaker 3: Know, depending on I mean, Sean, be honest, how long

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Speaker 3: do you spend on TikTok and days?

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Speaker 2: Be honest here, let's be honest.

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Speaker 1: I I've got young kids quite a bit. Actually otherwise

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Speaker 1: I wouldn't.

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Speaker 2: But you're you're so right.

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Speaker 3: I mean, AI is so pervasive and you know it.

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Speaker 3: I think we're still in sort of that phase of

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Speaker 3: we're playing around, folks are trying to go from pilot

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Speaker 3: to production. But in three years it's going to be

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Speaker 3: a tool that we all understand how to use.

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Speaker 1: Sanjana, thank you for talking Fear and Greed.

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Speaker 2: Thank you so much for having me.

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Speaker 1: That was Sanjana Paralika, Senior vice president of Marketing for

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Speaker 1: agent Force. This episode is part of our series with

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Speaker 1: Salesforce exploring how agentic AI is transforming Ozzie businesses. Head

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Speaker 1: to agentforce dot com for more information. I'm Sean Almer

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Speaker 1: and this is Fearing Greed Q and a