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Speaker 1: Welcome to Fear and Greed Q and A where 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 Aylmer. Over the last couple of weeks we've

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Speaker 1: been talking plenty about agentic ai, about the potential for

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Speaker 1: it to improve productivity and some success stories too. So

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Speaker 1: why aren't more Australian businesses doing it Well's holding them back?

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Speaker 1: And how do they take that step from using agentic

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Speaker 1: ai in isolated projects to rolling it out across an

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Speaker 1: entire enterprise and really turbo charging growth. Today's episode is

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Speaker 1: recorded live at the Agent Force World Tour Sydney. Fear

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Speaker 1: and Greed is partnering with Salesforce for this event. Kevin

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Speaker 1: Doyle is the Regional VP Agent Force and Data Cloud

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Speaker 1: and Zed. Kevin, Welcome to Fear and Greed.

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Speaker 2: Sean, thank you so much for having me.

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Speaker 1: So I want to get into the questions about how

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Speaker 1: to do it beforehand. Who's doing it so far? Who

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Speaker 1: in our region is doing a good job.

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Speaker 3: Yes, we're seeing a huge amount of interest globally. We

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Speaker 3: have eighteen thousand customers now using ai agents and agent

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Speaker 3: Force through Salesforce here in Australia at Agent Force World

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Speaker 3: Tour Sydney. We've heard from some fantastic examples of customers.

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Speaker 3: People like Zero, people like Australia Posts, people like Fish

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Speaker 3: at Pikel, people like Pepsi Co are all transforming their

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Speaker 3: businesses with AI and with AI agents.

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Speaker 2: Okay, so how are they doing it?

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Speaker 3: So when when AI first really hit the mainstream with

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Speaker 3: CHATJBT going live in November twenty twenty two, one of

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Speaker 3: my favorite quotes that came out of that was I

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Speaker 3: don't want AI to do painting and create music. I

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Speaker 3: want AI to do my dishes and fold my laundry.

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Speaker 3: And what was And it's like, what we've seen is

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Speaker 3: that big shift towards boring AI. What are the parts

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Speaker 3: of your job that you cannot stand? What are the dull,

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Speaker 3: the mundane, the things that can be repeated really really easily.

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Speaker 3: And how do we get agentic AI to help with

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Speaker 3: those things? And so if you think about Australia Posts,

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Speaker 3: you know they handle millions and millions of deliveries every

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Speaker 3: single year. They have the bedrock of the economy of

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Speaker 3: this country. And yet so many of people calling up

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Speaker 3: Australia Posts will say, hey, what's the one thing they

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Speaker 3: ask where is my order?

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Speaker 2: Where is my package?

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Speaker 3: And so right now, Well, what was happening before agentic

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Speaker 3: AI is you'd have to go on you try to

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Speaker 3: get hold of someone. There might be a massive, massive

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Speaker 3: wait time. You then ask the question. Someone on the

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Speaker 3: other line is bored out of their minds saying okay,

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Speaker 3: you know the same thing over and over and over again,

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Speaker 3: and then they give you the answer. The whole thing

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Speaker 3: might take thirty minutes. Well, now an agent can do

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Speaker 3: that for you. And so they're getting through eleven thousand

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Speaker 3: cases every single month. Where now you can go online,

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Speaker 3: you can talk to an agent live and now in seconds,

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Speaker 3: in real time, you can find out the answer to

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Speaker 3: that question. And that frees up their support team to

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Speaker 3: handle the interesting, the things that need that human touch,

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Speaker 3: the escalations, and so it means that the employee experience

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Speaker 3: is better, the customer.

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Speaker 2: Experience is better. It's ultimate win win for the organization

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Speaker 2: and for the people they serve.

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Speaker 1: Okay, so how did the first presentation to Australia Post

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Speaker 1: at this demo stage and was like, wow, this could

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Speaker 1: change our business, to the point where it is changing

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Speaker 1: their business. The so called last mile is it an

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Speaker 1: architecture that the organization needed. How did they think about that?

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Speaker 2: So it definitely starts with the end in mind.

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Speaker 3: And so what we've seen is when you sit down

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Speaker 3: with a really innovative company like Australia Posts and they

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Speaker 3: understand how agentics work and the future that it can

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Speaker 3: provide for them, their employees and their customers, you get

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Speaker 3: a million use cases coming out and you always end

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Speaker 3: up with this fantastic whiteboard if here's one hundred things

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Speaker 3: that we want to do, and then well, what's going

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Speaker 3: to be the easiest to get done and what's going

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Speaker 3: to lead to the highest amount of value?

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Speaker 2: And so after you.

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Speaker 3: Plot all of that out, you then go, what can

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Speaker 3: we do now? Because we need to prove this to

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Speaker 3: the organization. We need to prove that this isn't hype

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Speaker 3: anymore than this is a reality. And so the easiest

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Speaker 3: way to get agentic anything live is you think about

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Speaker 3: what little bit of data can I use where it's

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Speaker 3: a little pocket of data and it's pretty good. And

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Speaker 3: so for them it literally was, well, every single time

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Speaker 3: a package comes in, it gets scanned at every single stage.

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Speaker 3: They have that data sitting there and so we have

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Speaker 3: that available to access. That's an agent that we can

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Speaker 3: turn on relatively quickly, and so it certainly starts with

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Speaker 3: how do we do Phase one on data that we

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Speaker 3: have that's going to deliver measurable value for a business

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Speaker 3: which is either going to be greater revenue or a

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Speaker 3: massive decrease in cost, and then will that be enough

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Speaker 3: to pay for Phase two? What's the next thing on

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Speaker 3: the whiteboard that we can get through? And so that's

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Speaker 3: the journey that people are on. What's been a challenge though,

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Speaker 3: and I think the nextus really of the question is

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Speaker 3: there's a fantastic stat that came out of MIT about

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Speaker 3: six months ago that ninety five percent of AI pilots fail.

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Speaker 3: And that's scary because you think about how much this

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Speaker 3: has dominated Australian boardrooms for the.

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Speaker 2: Last three years.

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Speaker 3: Every chair, every CEO, every member of the C suite,

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Speaker 3: they are all getting huge amounts of pressure on them

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Speaker 3: to get AI, to get agentics, to get it live

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Speaker 3: for their workforce and their customers. And then they try

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Speaker 3: something and in ninety five percent of these instances it fails.

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Speaker 3: And the reason why is either they didn't have the

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Speaker 3: data in a good place or they tried to just

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Speaker 3: slap in an LM or an AI model.

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Speaker 2: And hope for the best.

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Speaker 3: And they weren't actually thinking about their employees or their

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Speaker 3: customers in the lens of when our customers interact with us,

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Speaker 3: what's going to be the easiest way for them to

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Speaker 3: engage with us. When our employees use out AI, where

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Speaker 3: is it built into the flow of their work.

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Speaker 2: We don't want them accessing a different tool.

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Speaker 3: We'ren't accessing tab tab tab, switching between different It's like, well,

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Speaker 3: what do they use right now and how do you

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Speaker 3: make that experience a little bit better? And certainly that's

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Speaker 3: the starting point for Australia Posts and for any customer

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Speaker 3: that we see moving from pilots into success. That five percent,

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Speaker 3: that's where they've been and that's really where we've seen

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Speaker 3: astrained organizations really focus their efforts over the last six

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Speaker 3: months twelve months.

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Speaker 1: How hard is it to get you mentioned the c suite,

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Speaker 1: You've also got many of these companies have boards. Of course,

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Speaker 1: you've got people on the floor doing their jobs. How

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Speaker 1: hard is the people part of it?

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Speaker 3: The people part of it is really interesting because if

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Speaker 3: you start at the top, you've got what I call

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Speaker 3: the CEO conundrum, which is the board is putting a

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Speaker 3: huge amount of pressure on the CEO, saying, where's AI,

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Speaker 3: where's the gentics, where's our more revenue, where's the productivity

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Speaker 3: improvement that we've heard so much about. You've then got

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Speaker 3: the organization looking up to the CEO saying, we don't

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Speaker 3: know how to do this, We've never done it, and

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Speaker 3: this isn't something I can do in a pocket. I

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Speaker 3: need the whole organization doing it. Imagine that I'm the

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Speaker 3: CMO and I'm leading the marketing efforts and I want

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Speaker 3: to run deep personalization at scale. I want the email

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Speaker 3: that you received to be personalized to you, the email

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Speaker 3: that goes out to your wife to be personalized to her. Well,

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Speaker 3: I can't do that without the data that exists that

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Speaker 3: the c YO has a handle on. Or maybe I

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Speaker 3: need the e commerce startup that sits with the person

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Speaker 3: that runs out digital team. So CEO, this is your

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Speaker 3: problem to fix. CEO has never implemented.

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Speaker 2: Augentic AI before, and so they've just.

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Speaker 3: Been getting squeezed and squeezed and squeezed and wondering, well,

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Speaker 3: how on earth do I do this. You then marry

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Speaker 3: that with the fact that ninety percent of all knowledge

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Speaker 3: workers in Australia are using agentic AI and AI in

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Speaker 3: their lives already, but it's all shadow AI. It is

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Speaker 3: in their personal login and they're copying and pasting really

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Speaker 3: important private data and they're putting it into an LLM

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Speaker 3: or into a different product in order to get their

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Speaker 3: job done. So you've actually got everyone in an organization

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Speaker 3: wanting to move in the same direction. They want things

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Speaker 3: to be easier, faster, more productive, but they just don't

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Speaker 3: know where to start. And so the key to the

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Speaker 3: people situation is you need a really strong leadership group

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Speaker 3: who will say this is a priority for us.

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Speaker 2: We need to move from hype to reality.

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Speaker 3: We need to cross that last mile and when to

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Speaker 3: find out what is the easiest, fastest way to not

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Speaker 3: only win our employees trust, but also to make a

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Speaker 3: measurable impact that will then pay for whatever The next

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Speaker 3: rounds of this is going to be.

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Speaker 1: Okay governance now, I literally in the last couple of

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Speaker 1: days have spoken to someone and she was a chair

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Speaker 1: of a board and said, we can't do AI at

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Speaker 1: the moment, we don't have our governance in place. And

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Speaker 1: I thought to myself, if you don't do it now,

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Speaker 1: I think you're in trouble, but I didn't have an

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Speaker 1: answer for a governance.

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Speaker 3: So let me reflect on our own AI journey at Salesforce.

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Speaker 3: And so we're an eighty thousand person company. We now

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Speaker 3: have forty agents live and the result we've got measurable impact.

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Speaker 3: We've saved over one hundred million dollars of cost within

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Speaker 3: our business from the forty agents that we have live.

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Speaker 2: Now, where did we start.

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Speaker 3: It wasn't on a big global customer facing agent handling

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Speaker 3: all the PII data that's live for your instance and

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Speaker 3: only your environment.

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Speaker 2: We started with, well, what.

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Speaker 3: Do we think is the lowest risk on a pocket

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Speaker 3: of data that can make a miserable impact that we

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Speaker 3: can get live really fast. And the answer to that

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Speaker 3: was actually an employee facing agent. And so where we

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Speaker 3: started was with eighty thousand people. You can only imagine

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Speaker 3: our poor IT help desk and the number of people

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Speaker 3: like me messaging them every day saying I left my

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Speaker 3: laptop in a taxi.

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Speaker 2: Can you please what do I do now?

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Speaker 1: Yes?

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Speaker 2: Or I can't access my VPN.

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Speaker 3: And so, as a great example, so two years ago

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Speaker 3: I messaged I actually lost access to my VPN and

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Speaker 3: it wouldn't dial in, and so what happened then me,

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Speaker 3: Kevin Doyle.

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Speaker 2: I caught up and I logged a ticket and then

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Speaker 2: I then waited eight and a half hours for someone

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Speaker 2: to call me back.

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Speaker 3: They then called me back. They ran me through a

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Speaker 3: few steps. I was able to access my VPM. The

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Speaker 3: productivity loss. There was one day of my life where

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Speaker 3: I couldn't access any systems and I couldn't do my job.

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Speaker 3: The same thing happened to me a month and a

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Speaker 3: half ago, and I went into Slack, which is one

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Speaker 3: of our internal tools that we use. I went into

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Speaker 3: the agentic it help desk and I said, Hi, I've

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Speaker 3: lost access to my VPN, and it says, Hi, Kevin,

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Speaker 3: thanks very much for blogging your ticket, and AI agent

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Speaker 3: will join me. Shortly, an AI agent has joined the chat. Kevin,

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Speaker 3: how can I help? I've lost access to my VPN?

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Speaker 3: What can I do? These are the steps that you

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Speaker 3: need to carry out. Try all these things? Did they work? No?

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Speaker 3: They didn't work for me? Well, then try these things

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Speaker 3: did that work? No, it didn't work for me. I'm

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Speaker 3: going to connect you to someone right now.

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Speaker 2: Hi. Sophie has joined.

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Speaker 3: The chat and instantly, in the course of four and

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Speaker 3: a half minutes. I wasn't able to fix that problem.

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Speaker 3: And so the things that I really liked about this

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Speaker 3: store and things to take away is number one. The

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Speaker 3: first agent we got live was for our employees, and

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Speaker 3: I got all of our employees comfortable with the role

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Speaker 3: of agentics and how it's going to influence their lives

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Speaker 3: and also their customers lives. The second what a phenomenal experience.

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Speaker 3: I went from eight and a half hours to someone

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Speaker 3: helping me immediately because Sophie now she wasn't doing the

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Speaker 3: dishes and the laundry, she wasn't doing the drudgery of

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Speaker 3: her role that she previously had. She now has the

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Speaker 3: capacity to do the more advanced, more interesting use cases,

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Speaker 3: more interesting cases to help other people in the organization.

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Speaker 3: And that's again, that's been such a form. Like I said,

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Speaker 3: I said, it's one hundred million dollars over the forty

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Speaker 3: agents we've got live across that organization.

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Speaker 2: Wow.

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Speaker 1: The thing I find with it with fear and greed,

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Speaker 1: we try and put scripts together using an agent ride,

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Speaker 1: and it is amazing how easy it is. I mean,

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Speaker 1: I think sometimes you see AI as this big bogeyman

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Speaker 1: out there that I need to get my head around,

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Speaker 1: but if you just jump in, it's actually easier than

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Speaker 1: you think it is.

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Speaker 3: And it's interesting that we've got a couple of customers

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Speaker 3: who they want to test how comfortable the Australian consumer

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Speaker 3: is with AI agents, and so what they will do

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Speaker 3: is you'll call it the support center and they'll say, Hi,

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Speaker 3: thanks so much for calling insert online insert bank. We

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Speaker 3: have an AI agent that is available to chat with

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Speaker 3: you immediately, but if you'd prefer to way and talk

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Speaker 3: through a human, the wait time right now is forty

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Speaker 3: seven minutes or press three and we'll call you back

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Speaker 3: at your convenience. And we've seen already I repeal clicking

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Speaker 3: one every single week.

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Speaker 2: It's trending up into the right.

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Speaker 3: People are getting more and more comfortable every day because

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Speaker 3: they know, well, I can talk this AI agent.

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Speaker 2: It's pretty high likelihood it's going to help me out.

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Speaker 3: And if I can't, I know I can press another

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Speaker 3: button and I'm going to get Sophie who's going to

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Speaker 3: give me a call or you know, as soon as

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Speaker 3: she can.

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Speaker 2: So I'm no worse off. There's only upside in the

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Speaker 2: conversation for me.

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Speaker 1: Fantastic, Kevin, thank you for talking to Fear and Greed.

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Speaker 2: Great, Thanks so much, Sean.

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Speaker 1: Now it's Kevin Doyle, Regional VP, Agent Force and Data Cloud,

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Speaker 1: A and Z. Recorded here at Agent Force World Tour, Sydney.

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Speaker 1: This episode is part of our series with Salesforce exploring

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Speaker 1: how agentic ai is transforming Aussie businesses. Head to agentforce

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Speaker 1: dot com Agentforce dot com for more information. I'm Sean Alman.

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Speaker 1: This is Fear and Greed, Q and A