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Speaker 1: Welcome to the Business of Tech powered by two Degrees Business,

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Speaker 1: the podcast where we dive deep into the trends and

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Speaker 1: technologies shaping the future of business. I'm your host Peter Griffin.

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Speaker 1: Today we're tackling one of the hottest and, let's face it,

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Speaker 1: most overwhelming topic in business right now, Artificial intelligence. I've

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Speaker 1: done several shows over the last year on AI, mainly

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Speaker 1: from technologists and scientists and startup founders who are using AI.

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Speaker 1: This one's going to be a little bit different. While

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Speaker 1: AI is starting to change how entire industries operate, many

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Speaker 1: small and medium sized business owners here in New Zealand

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Speaker 1: are left wondering does this all hype or can AI

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Speaker 1: actually make a difference for me? How do I cut

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Speaker 1: through the noise and put these tools to work in

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Speaker 1: my business without losing what makes it unique. To help

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Speaker 1: us answer those questions, I'm joined this week by Tracy Sheen,

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Speaker 1: the Brisbane based AI consultant and business coach. Tracy's an

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Speaker 1: award winning author, speaker, and AI strategist with over three

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Speaker 1: decades of experience in telecommunications, marketing and technology. She's worked

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Speaker 1: with major brands like Telstra, Optus and Harvey Norman She's

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Speaker 1: a trusted voice when it comes to making technology accessible

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Speaker 1: for everyone. Her last book, The End of Technophobia, one

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Speaker 1: Australia's Business Book of the Year in twenty twenty one.

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Speaker 1: Now Tracy's back with a new book, AI and You

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Speaker 1: Reimagine Business, which I love because it delivers a practical,

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Speaker 1: jargon free roadmap for small and medium sized businesses looking

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Speaker 1: to embrace AI. Is packed with real world case studies

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Speaker 1: and hands on exercises showing you how to streamline tasks,

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Speaker 1: boost productivity, and enhance your relationships with clients and or

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Speaker 1: without overloading you with the tech. I think it's exactly

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Speaker 1: what our businesses need as they move from experimentation with

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Speaker 1: AI to really incorporating it into their operations. Tracy's also

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Speaker 1: a lot of fun, so I think you'll really enjoy this.

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Speaker 1: Here's Tracy Sheen on AI and You. Tracy Sheen, Welcome

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Speaker 1: to the business of tech. How are you doing?

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Speaker 2: I am looking forward to stirring the AI plot with you, Peter.

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Speaker 1: And you have been with your new book AI and

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Speaker 1: You Reimagining Business. And you know there's just been a

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Speaker 1: deluge of AI related books. I've just read one called

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Speaker 1: AI Empire, which is all about the open Ai story

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Speaker 1: and all the sort of nefarious stuff that went on

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Speaker 1: in the background there as this company tried to build

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Speaker 1: the biggest AI monolith in the world and it's succeeding

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Speaker 1: and doing that. But what I love about your book,

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Speaker 1: Tracy is it's actually aimed at the people who need

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Speaker 1: to be adopting AI. And we're a country of small

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Speaker 1: businesses in New Zealand like Australia, and mid sized businesses,

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Speaker 1: and every company is now trying to grapple with this.

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Speaker 1: All these tools from the likes to open Ai, Microsoft Aws,

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Speaker 1: Canva and others. Everyone has embraced AI and the rest

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Speaker 1: of us are going, Okay, well that's great, but is

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Speaker 1: this all hype or how do I actually use these

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Speaker 1: tools in a useful way? And what I love about

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Speaker 1: the book is that it gives you some really practical

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Speaker 1: tips on how to do that and a framework to

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Speaker 1: approach it as well. So we're going to dive into that,

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Speaker 1: but before we do, just a bit about your background.

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Speaker 1: Trac you're obviously a successful author. You had a business

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Speaker 1: Book of the Year in twenty twenty one, congratulations and

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Speaker 1: that so you're back with with another book. But tell

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Speaker 1: us about your journey in business and business coaching and

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Speaker 1: the like.

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Speaker 2: Yeah, well, my journey actually is one of those ones

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Speaker 2: that you know only makes sense when you look at

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Speaker 2: the rearview mirror. So when I was six, I was

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Speaker 2: playing with electronic scales on the parent on my floor

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Speaker 2: of my parents' workshops, so one of the first in

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Speaker 2: Australia to import electronic scales. So I was pulling them

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Speaker 2: apart and playing around with the boards and soldering things

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Speaker 2: back together, trying to figure out why that worked and

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Speaker 2: that didn't work. And you can't judge me, Peter. It

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Speaker 2: was the seventies and six year olds were allowed to

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Speaker 2: play with soldering irons, so you know, fair play. I

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Speaker 2: got into selling mobile phones straight out of high school,

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Speaker 2: so that was nineteen ninety. We had very little coverage

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Speaker 2: in regional Australia, much like you guys went through across

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Speaker 2: the ditch and all the mobile phones they were the

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Speaker 2: size of house bricks. Although were really good for because

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Speaker 2: you couldn't reach your connection to make a call if

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Speaker 2: you needed to. That you could smack somebody over the

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Speaker 2: head and run like hell if you needed to. So

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Speaker 2: that was my first kind of introduction into the world

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Speaker 2: of technology, and you know, even though I was only

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Speaker 2: like eighteen, I just had that there was some kind

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Speaker 2: of knowing that this is the start of something that's

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Speaker 2: about to change everything. So I knew I was where

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Speaker 2: I was meant to be, and then my career just

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Speaker 2: kind of I bounced around a lot from there, launched

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Speaker 2: the iPhone into Australia as part of a retail channel,

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Speaker 2: helped launch as technology into Australia, you know, and was

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Speaker 2: kind of there at the forefront of all these big

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Speaker 2: kind of tech advancements, but always from the point of

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Speaker 2: view of being there for the small business community. So

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Speaker 2: I was always writing the manuals for how do the

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Speaker 2: retailers put these new tech devices into the hands of

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Speaker 2: small business owners and what is that going to mean

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Speaker 2: for them? So I've always had this real kind of

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Speaker 2: I guess passion for connecting the technologlogy with the human

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Speaker 2: or particularly small business owners. And then left corporate in

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Speaker 2: two thousand and eight, started my first business with my

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Speaker 2: now husband, bought and sold a few and this kind

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Speaker 2: of tech stuff always just kept bubbling up, did a podcast,

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Speaker 2: did a few other things, and I really started to

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Speaker 2: realize that my passion is really about, you know, continuing

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Speaker 2: to help small business owners in particular connect with these

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Speaker 2: tools in a way that allows them to get back

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Speaker 2: to doing what they actually love and why they got

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Speaker 2: into business, and maybe spend some time with friends and

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Speaker 2: family instead of always being on as a business owner.

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Speaker 1: Well, this is the dream scenario you outline in AI,

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Speaker 1: and you just a quote from it. You say, picture this.

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Speaker 1: Your business is running like clockwork. AI handles the admin

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Speaker 1: trends and to do's that usually bog you down, leaving

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Speaker 1: you free to focus on the parts of your business

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Speaker 1: that you actually like. Your customers feel like VIPs because

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Speaker 1: you give them exactly what they need when they need it.

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Speaker 1: Your team is happier because the grunt work is done

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Speaker 1: for them, and you have time to plan for the

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Speaker 1: future or take a well earned break. And it's the

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Speaker 1: dream scenario for all of us and remains elusive for

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Speaker 1: a lot of us as well. We have a productivity

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Speaker 1: problem in New Zealand, less so in Australia, but still most,

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Speaker 1: you know, Western countries are suffering with labor productivity. In

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Speaker 1: New Zealand we work probably the hardest in the OECD

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Speaker 1: in terms of the hours that we put in for

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Speaker 1: the output. So we've been told by the government we

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Speaker 1: need to pick up our productivity. They're looking at advanced

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Speaker 1: technologies like AI to do that, and that is what

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Speaker 1: we want, you know, all of the grunt work taken out,

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Speaker 1: so at least we can then focus on the more

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Speaker 1: creative stuff and the stuff that matters and relationships. You

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Speaker 1: talk a lot in the book about how key relationships are.

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Speaker 1: I guess you know, there's been a lot of hype

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Speaker 1: around AI as being the promise technology. But as you said,

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Speaker 1: you've been through these waves of technology, email, the mobile revolution, cloud,

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Speaker 1: and now AI is just the latest one. How do

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Speaker 1: we actually get those gains because it seems like through

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Speaker 1: all of those revolutions were working harder than ever. Sure,

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Speaker 1: they automated some things and made connectivity easier, but we're

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Speaker 1: just more overwhelmed than ever before. What's going on?

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Speaker 2: Yeah, look, it's I think we've got sold of Furfy

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Speaker 2: to be honest. You know, it was like, here, take

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Speaker 2: another device and then it'll make your life easier. But

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Speaker 2: you've got to buy in for this subscription and that

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Speaker 2: subscription on by the way, Oh you need to do that,

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Speaker 2: Well that wasn't included. Now you need to upgrade. So

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Speaker 2: I feel like we're just being put onto this treadmill

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Speaker 2: of increased consumerism a very little return. I do believe

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Speaker 2: that AI and kind of what will build off the

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Speaker 2: back of it, does have the capabilities to finally build

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Speaker 2: in some of these streamlines and productivity gains and promises

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Speaker 2: that we've been sold forever in a day, I think,

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Speaker 2: you know, like anything, though, it's still going to take

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Speaker 2: a bit of bit of work and a bit of

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Speaker 2: efforts to see that through. But yeah, for once I

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Speaker 2: can actually say, all right, I can see what it

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Speaker 2: is that you're talking about, and I can see how

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Speaker 2: it's going to be applicable for the average small business owner,

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Speaker 2: not a major, you know, C suite firm.

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Speaker 1: Look, it doesn't have to be a big bang thing

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Speaker 1: and be overwhelming to approach. You know, you talk in

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Speaker 1: there about what is your low hanging fruit? So every

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Speaker 1: business will have one thing that drives them bo akers.

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Speaker 1: You write in there, and what is the thing that's

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Speaker 1: going to make the biggest difference. What is the really

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Speaker 1: clunky process that you and your customers really hate? And

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Speaker 1: you know, I'm sort of seeing that in my own

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Speaker 1: business as a content creator. There are two or three

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Speaker 1: bottlenecks in the process that consistently frustrate me and take

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Speaker 1: a lot of time. But you know, AI is starting

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Speaker 1: to change that, so I can relate to that. So

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Speaker 1: what's your advice to businesses? How do you sort of

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Speaker 1: systematize this process of looking at your business, looking at

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Speaker 1: what AI tools are out there, and then trying to

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Speaker 1: reimagine your business with the use of those tools.

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Speaker 2: Hey, do you just did it? You know, it's really interesting.

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Speaker 2: Every time I raise this point with someone, they the

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Speaker 2: first thing they kind of go is, oh, yeah, yeah,

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Speaker 2: I've got two or three things. I didn't ask for

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Speaker 2: two or three things. That's the pick one. And that's

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Speaker 2: what we always do as business owners. We'll go, oh, yeah,

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Speaker 2: well there's this. Oh but if I could do this

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Speaker 2: as well and this as well, and that's what ends

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Speaker 2: up happening. We come up with two or three or

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Speaker 2: five or ten and not one, and so then we go, oh,

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Speaker 2: we can work on two or three, and we start to,

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Speaker 2: but then we get overwhelmed because we've got two or

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Speaker 2: three things to do, and so then we put it

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Speaker 2: down and we don't get back to it. So that's

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Speaker 2: why I come back and I'm going to say it

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Speaker 2: to you going to say it to everyone. Two or

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Speaker 2: three is great, pick one, pick one, and you know,

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Speaker 2: even if it's down to well it's a toss up,

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Speaker 2: that's okay, flip a coin, but pick one because if

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Speaker 2: you get that one done, you're more likely to move

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Speaker 2: on to the next thing. But if you put two

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Speaker 2: or three on the table and go, here's my two

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Speaker 2: or three I'm going to tackle, then I guarantee you

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Speaker 2: none of them will get done. So it is really

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Speaker 2: distilling it down. And if you've got a team, it's

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Speaker 2: getting the team together around the table. Everybody in the

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Speaker 2: team will have one thing in their role. Admin's got

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Speaker 2: one thing that you know drives some bonkers. It has

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Speaker 2: one thing that you know sends them around the band,

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Speaker 2: marketing's got one thing that's annoying them. So it could

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Speaker 2: be internally. First, it might be that the clients are

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Speaker 2: constantly going, oh my gosh, Pete, I just get back

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Speaker 2: to my email. Come on, man, what's going on? But

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Speaker 2: there is that we always innately have that I know

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Speaker 2: what it is, I just don't want to tackle it

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Speaker 2: because it's been sitting there gnawing away at the back

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Speaker 2: of my head for the last ten years.

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Speaker 1: So that's good advice. You focused on the one thing.

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Speaker 1: And a good thing now with these AI tools is

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Speaker 1: that a lot of them are off the shelf. There's

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Speaker 1: subscription base, so it doesn't have to be a massive

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Speaker 1: outlay to experiment. You can, in a safe way actually

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Speaker 1: point some of these tools at a problem and just experiments.

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Speaker 1: He does it save the team time? Do customers like it?

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Speaker 1: So it doesn't have to be a big bang thing anymore,

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Speaker 1: does it? I mean likes the mid journey, open AIS,

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Speaker 1: enterprise chat, cheepy even you know, a few hundred dollars

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Speaker 1: a month. This doesn't have to be a massively expensive exercise,

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Speaker 1: not at all.

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Speaker 2: And often if we look for the big bang, as

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Speaker 2: you say, like that's that's months or years to get

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Speaker 2: that sorted. You know, I'm talking about that one little

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Speaker 2: thing that you know, when we reach this point in

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Speaker 2: the customer journey, I'm the bottleneck because Jen's waiting on

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Speaker 2: me to send this thing. Okay, Well do you use Microsoft?

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Speaker 2: Do you use Google? Because chances are Microsoft or Google

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Speaker 2: already have that thing built in. If you explore what

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Speaker 2: it is that you're already using, you can probably you know,

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Speaker 2: plug in a workforce solution that's going to automate that

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Speaker 2: bit in the middle. It's not looking for something that's

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Speaker 2: going to completely change the way that everything's been working.

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Speaker 2: It's looking for that one little trigger that you can

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Speaker 2: just pull and go okay, well, let's done now. And

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Speaker 2: as you said, particularly with small businesses, we're not looking

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Speaker 2: for an enterprise solution. We want something that probably is freemium,

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Speaker 2: you know. We want to give it a crack for

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Speaker 2: seven days or fourteen days or whatever. And that's long

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Speaker 2: enough with these tools, now, that is long enough. If

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Speaker 2: you can play with it consistently for seven days or

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Speaker 2: fourteen days, you can make an educated decision by the

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Speaker 2: end of that time. Yes this is working. No it's not.

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Speaker 2: If it's not, ditch it and move on, because that's

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Speaker 2: how our bank accounts blow out at the end of

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Speaker 2: every month and we're going, how are we paying five

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Speaker 2: thousand dollars a month on SaaS platforms? What's going on here?

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Speaker 2: Who's using that one? But if you can go no,

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Speaker 2: that's not doing it, kill it, move on, find the

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Speaker 2: next one, you know, and just until you get to

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Speaker 2: that point where you like, hey, yep, that does it. Awesome.

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Speaker 2: Now look at how do we embed that?

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Speaker 1: Yeah, and it's that how do we embed that is

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Speaker 1: the crucial thing. You've actually come up with a framework.

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Speaker 1: It's not specific to AI. I think it preceded the

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Speaker 1: AI revolution. That's called reimagine. Talk us through this and

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Speaker 1: maybe use a couple of examples, because in the book

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Speaker 1: you give a couple of examples of names that listeners

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Speaker 1: will know. There's Tim Tams from Ron It's great, great product,

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Speaker 1: one of my favorite biscuits. So they have been reimagining

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Speaker 1: their business over subsequent decades. Yeah, king to hear about

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Speaker 1: Tim Tim Tams and also can for one of the

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Speaker 1: biggest tech successes out of Australia, started by a woman

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Speaker 1: who was not technical at all, was a graphic designer,

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Speaker 1: but saw the typical thing with the startup founder saw

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Speaker 1: a problem in this case with graphic design Adobe and

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Speaker 1: photoshoph and all that was clunky and big learning curve,

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Speaker 1: but has also been reimagining the business, including for the

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Speaker 1: era of AI. So take us through your approach to

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Speaker 1: reimagine and maybe use those two examples.

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Speaker 2: Yeah. So, if I you're right the concept of reimagine,

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Speaker 2: really it came about because I was chatting with some

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Speaker 2: clients and I was like, look, how did I get

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Speaker 2: you from you know, there to there? And they were like, oh, well,

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Speaker 2: we did this and we did this, and I was

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Speaker 2: like okay. So then I started to look back at

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Speaker 2: some of the businesses that I admire and I was like,

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Speaker 2: that's really interesting. They've all kind of followed this same

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Speaker 2: formula for one of a better word, and I've built

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Speaker 2: it around the word reimagine because I just love the

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Speaker 2: concept that we can't think about the way that life

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Speaker 2: has always been. It's time that we reimagine things. Right.

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Speaker 2: So if I think about Arnnce and the story that

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Speaker 2: you're talking about in particular was the development of the

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Speaker 2: hymn tam and that came about because they had identified

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Speaker 2: that Ossies were looking for a new type of biscuit,

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Speaker 2: but they wanted something that was intrinsically Australian. But they

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Speaker 2: had kind of found this English biscuit that kind of

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Speaker 2: you know, met the foundations of what they were looking for.

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Speaker 2: So they went through this process of you know, back

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Speaker 2: to the framework the relationships. They took it back to

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Speaker 2: the customer. What does the customer looking for? They want

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Speaker 2: something that's a little bit more than you know, just

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Speaker 2: a dunkable playing biscuit. They want something with a bit

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Speaker 2: of genesequa for one of the better words, you know.

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Speaker 2: So then they took a look at their entire stack.

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Speaker 2: So they went through that evolution process or that education

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Speaker 2: process of what do we got? Where are we sitting?

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Speaker 2: They identified the gap and then they mapped out, well,

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Speaker 2: where do we want to get to? What does that

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Speaker 2: actually look like? So they went to England they found

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Speaker 2: this product and then they just started to put the

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Speaker 2: pieces into place. Okay, what happens if we do this?

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Speaker 2: And they did a small batch, they activated it, they

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Speaker 2: put it out to market, They gathered the information and

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Speaker 2: people went, oh, no, that's you know, completely what are

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Speaker 2: you thinking? You know, how did you come up with veggimie?

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Speaker 2: It's off the bottom of a sparrow almost, you know.

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Speaker 2: And they went through this process of reiteration and reiteration

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Speaker 2: until they landed on this formula that has now become

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Speaker 2: known as tim Tans. But if you think about it,

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Speaker 2: they could have just like, he's our one flavor of

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Speaker 2: Tim TAM's happy days. But I don't know what the

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Speaker 2: New Zealand supermarket shelves are like, but it is pretty

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Speaker 2: much the entire biscuit shelf of a Aussie supermarket now

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Speaker 2: is you know, nine six hundred and thirty two different

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Speaker 2: flavors of tim Tams. Because they have really just taken

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Speaker 2: the concept of reimagining off the charts. You know, then

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Speaker 2: you've got your Lamington flavor and your Pinicolata and your

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Speaker 2: salted caramel and you whatever. So they've now taken it

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Speaker 2: to the nth degree of it has become part of

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Speaker 2: their foundation that now they can just tweak it every

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Speaker 2: now and again and go, Okay, here's a celebration formula,

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Speaker 2: here's a footy formula, and we're going to do a

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Speaker 2: small batch run and now people collect them. And so

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Speaker 2: it just goes to show that as long as you

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Speaker 2: keep your people and when I say relationships or people,

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Speaker 2: it's not just clients. It's got to be your team

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Speaker 2: as well. They're your people, your suppliers. You've got to

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Speaker 2: keep the humans at the center. And as long as

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Speaker 2: you keep coming back to what are they looking for?

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Speaker 2: How is this making it better, worse different for them?

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Speaker 2: How are our decisions impacting our people? And that was

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Speaker 2: how they kept coming up with this evolution process around

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Speaker 2: the Tin Tam, so I kind of love. You know

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Speaker 2: that it can be applied into whatever stage or industry

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Speaker 2: that you're looking at.

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Speaker 1: Yeah, and there's a brand in New Zealand, a very

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Speaker 1: old brand, Woodikers Chocolate, which has gone through a similar.

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Speaker 2: One of the best chocolates I have to say.

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Speaker 1: It is it is great chocolate, and they've gone through

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Speaker 1: a similar over decades iterations and now have this proliferation

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Speaker 1: of different flavors of chocolate, different types. They've got a

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Speaker 1: high end, sort of boutique range of chocolates and not

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Speaker 1: many brands get away with doing that. Obviously, iron It

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Speaker 1: has been able to do it with Tim TAM's, and

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Speaker 1: Whittakers has as well. And it's really that relentless focus

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Speaker 1: I think, as you said, you know, on people, on

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Speaker 1: customer feedback and particularly refining it based on feedback. You know,

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Speaker 1: we saw the giant of chocolate Cabre's, really not do

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Speaker 1: well in New Zealand. You know, Whittakers took them on

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Speaker 1: and won because they listened to their customers over ethical

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Speaker 1: things like using palm oil and that sort of thing.

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Speaker 2: Exactly. Yeah, and even you know, it's it's just so interesting,

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Speaker 2: isn't it. Because I remember the story of New Coke

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Speaker 2: right if anyone needed a Coca Cola drinker. New Coke

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Speaker 2: was classified as one of the biggest bombs that ever

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Speaker 2: happened in terms of marketing. You know, they scrapped the

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Speaker 2: original flavor and went to this new Coke, and people

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Speaker 2: kind of go, that was a real example of something

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Speaker 2: that failed, and I kind of go, actually, it's a

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Speaker 2: real example of the brand going. You know, we could

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Speaker 2: be arrogant and push forward with this because there's a

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Speaker 2: company we made a decision. But what did they do.

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Speaker 2: They went back and they listened to their client base

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Speaker 2: and went, Okay, we're either going to lose our entire

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Speaker 2: brand here or we fesce up and go you know what,

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Speaker 2: we're here. We made a mistake. This is off the

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Speaker 2: market now, and we're going back to what you want.

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Speaker 1: In the case of Canva, I mean, this is probably

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Speaker 1: an older business than some people would realize. Back in

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Speaker 1: twenty ten, I think it was. Melanie Perkins was a

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Speaker 1: graphic design t shirt only nineteen years of age, but

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Speaker 1: was really frustrated with graphic design software at the time

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Speaker 1: and wanted a really simple, inclusive platform. Drag and dropped templates,

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Speaker 1: all of that sort of stuff. So built that it

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Speaker 1: turned into a raging success, hundreds of millions of customers,

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Speaker 1: a listed company, multi billion dollar valuation. They've integrated AI,

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Speaker 1: but they didn't really make a big song and dance

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Speaker 1: about it, did they. It was more like a silent

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Speaker 1: integration behind the scenes because they actually realized it's not

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Speaker 1: about waiving the AI flag. That means nothing to customers.

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Speaker 1: How is it actually going to improve their experience on

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Speaker 1: the platform. And we'll only do it if we can

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Speaker 1: achieve that.

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Speaker 2: Yeah. Absolutely, And what I love about the Canvas story,

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Speaker 2: you know again, it comes back to they keep their

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Speaker 2: clients close, They keep their users close. It always everything

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Speaker 2: they do needs to be How does this improve their experience?

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Speaker 2: How does this make their life easier? How does it

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Speaker 2: save their time? How does it you know, whatever that

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Speaker 2: goal is. But the thing when they integrated AI that

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Speaker 2: I find really interesting is they were after specific wins.

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Speaker 2: So you're right, they didn't come out and go, oh,

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Speaker 2: we're now all about AI. They just come out and went, oh,

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Speaker 2: now we've got a background remover, and look what happens

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Speaker 2: if you click here. I don't care that that's AI.

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Speaker 2: I care that now I don't have to figure out

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Speaker 2: how I'm going to remove you know, that random mirror

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Speaker 2: behind me because I'm dialing in from a hotel room today.

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Speaker 2: That's what I care about. I don't care that, you

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Speaker 2: know my words can now be in a circle with

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Speaker 2: neon around them. I care that I don't have to

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Speaker 2: figure out how to make my words in a circle,

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Speaker 2: and oh I can turn it into neon. They like

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Speaker 2: a customer doesn't care that that's AI. So I love that.

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Speaker 2: Camber just kind of went, Okay, we're hearing you. This

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Speaker 2: is what's important. It's taking you way too long to

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Speaker 2: be able to dee bet your photo or to cut back,

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Speaker 2: round out, or to put an example of what a

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Speaker 2: product's going to look like on a coffee mug, or

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Speaker 2: to see how it could look if we rewrote that

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Speaker 2: particular sentence or inserted a photo of a dog on

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Speaker 2: a surfboard there. You want to just be able to

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Speaker 2: do it, call it whatever you like. We just need

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Speaker 2: to make it happen. I love that because a lot

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Speaker 2: of companies, you know, as you rightly said, Peter, they're

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Speaker 2: very We've got AI and we'd like to tell you

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Speaker 2: about our latest AI and it's about me. And here

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Speaker 2: I am with my AII product, and you need to

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Speaker 2: know about this because we've spent hundreds of thousands of

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Speaker 2: millions of dollars in production of doing this and we're fantastic.

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Speaker 2: I don't care what's in it for me, like what's

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Speaker 2: in it for the client. So I love the companies

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Speaker 2: that come about it that way.

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Speaker 1: Yeah, and as you said, some of those features, we

429
00:24:28,000 --> 00:24:30,200
Speaker 1: don't care whether they're done by AI. We just want

430
00:24:30,359 --> 00:24:33,600
Speaker 1: a better experience to do it faster, more efficiently. I

431
00:24:33,600 --> 00:24:36,000
Speaker 1: guess some of the low hanging fruit for a lot

432
00:24:36,000 --> 00:24:39,600
Speaker 1: of New Zealand businesses will be what you referenced earlier,

433
00:24:39,640 --> 00:24:41,679
Speaker 1: why don't you just respond to my email in a

434
00:24:41,720 --> 00:24:46,480
Speaker 1: timely fashion? And they'll be looking to AI to triage

435
00:24:46,560 --> 00:24:49,800
Speaker 1: their inbox and customer inquiries and that sort of thing.

436
00:24:50,480 --> 00:24:53,520
Speaker 1: But how do you deal with with with that? You know,

437
00:24:53,760 --> 00:24:58,080
Speaker 1: customers tell us they love the human touch, the acceptance

438
00:24:58,200 --> 00:25:02,440
Speaker 1: factor of in customer service off AI getting in there

439
00:25:02,480 --> 00:25:06,520
Speaker 1: to try and streamline things. How much acceptance after is it?

440
00:25:06,560 --> 00:25:09,480
Speaker 1: And how do you broach that with customers. We've seen

441
00:25:09,720 --> 00:25:13,760
Speaker 1: customer service chatbots not do very well so far because

442
00:25:13,800 --> 00:25:17,200
Speaker 1: it frustrates people they're not good enough. Maybe the next iteration,

443
00:25:17,320 --> 00:25:20,440
Speaker 1: the so called AI agents will be able to have

444
00:25:20,480 --> 00:25:24,960
Speaker 1: a more naturalistic conversation and a useful conversation. But the

445
00:25:25,119 --> 00:25:28,360
Speaker 1: generation up till now really have not been well received.

446
00:25:28,400 --> 00:25:31,760
Speaker 1: So how do you keep that human touch but integrate

447
00:25:31,880 --> 00:25:35,119
Speaker 1: AI into the customer experience transparency?

448
00:25:36,040 --> 00:25:39,840
Speaker 2: I think treaty clients like you know you've always treated them,

449
00:25:39,840 --> 00:25:43,639
Speaker 2: and if you actually value them and enjoy working with

450
00:25:43,680 --> 00:25:45,879
Speaker 2: them and all the rest of it, then I think,

451
00:25:46,280 --> 00:25:49,440
Speaker 2: you know, we're so nervous about making changes because how

452
00:25:49,480 --> 00:25:51,919
Speaker 2: is this going to impact to whatever? But you know,

453
00:25:52,000 --> 00:25:54,760
Speaker 2: most of our clients I've just found if you sit

454
00:25:54,840 --> 00:25:57,800
Speaker 2: down with people and go so hey, Peter, you've kind

455
00:25:57,800 --> 00:25:59,840
Speaker 2: of expressed this, and thank you for that, I really

456
00:25:59,880 --> 00:26:04,000
Speaker 2: like it. Listen with you know, thinking about introducing this

457
00:26:04,160 --> 00:26:06,360
Speaker 2: as a way to you know, kind of close that down.

458
00:26:06,359 --> 00:26:08,679
Speaker 2: What do you reckon if I put you on a

459
00:26:08,720 --> 00:26:11,080
Speaker 2: beta group? Would that be okay? Can you give me

460
00:26:11,119 --> 00:26:15,160
Speaker 2: some feedback on what's working what's not working? Because I'm

461
00:26:15,160 --> 00:26:17,399
Speaker 2: not going to release this to everyone until I know that,

462
00:26:18,000 --> 00:26:20,560
Speaker 2: you know, my core group of people are okay. You

463
00:26:20,600 --> 00:26:23,240
Speaker 2: find people go like oh mate, that's amazing, Like, yeah,

464
00:26:23,320 --> 00:26:25,040
Speaker 2: let me, what do you need? What do you, what

465
00:26:25,080 --> 00:26:27,919
Speaker 2: do you need? How can I help? Because you're bringing

466
00:26:27,960 --> 00:26:30,760
Speaker 2: them in, You're bringing them into the inner sanctum of like,

467
00:26:30,920 --> 00:26:33,200
Speaker 2: you know, hey, you brought this up as a problem

468
00:26:33,200 --> 00:26:36,560
Speaker 2: for me, and thank you. Help me solve it. How

469
00:26:36,600 --> 00:26:39,400
Speaker 2: do I make my business better? For you to work

470
00:26:39,440 --> 00:26:41,720
Speaker 2: with me? How to make my business better? That you're

471
00:26:41,760 --> 00:26:44,520
Speaker 2: going to say, you know, George, you really need to

472
00:26:44,520 --> 00:26:46,320
Speaker 2: work with Tracy, Like you're not going to get a

473
00:26:46,320 --> 00:26:50,879
Speaker 2: better experience. It's the authenticity thing. That's what we're looking

474
00:26:50,920 --> 00:26:56,320
Speaker 2: for now, right, Like we don't I find the people

475
00:26:56,359 --> 00:26:59,760
Speaker 2: that I work with, their clients don't care if it's

476
00:26:59,800 --> 00:27:03,000
Speaker 2: me or if it's AI, as long as the problem

477
00:27:03,040 --> 00:27:11,080
Speaker 2: is resolved. They care when the problem is escalated or

478
00:27:11,080 --> 00:27:16,840
Speaker 2: it's not addressed, or I'm ignored or I'm belittled or

479
00:27:17,040 --> 00:27:20,040
Speaker 2: you know whatever. But if I'm very upfront and go

480
00:27:21,040 --> 00:27:24,119
Speaker 2: we're going through a process of trialing AI for X

481
00:27:24,240 --> 00:27:27,359
Speaker 2: y Z. We don't know how it's going to go.

482
00:27:27,840 --> 00:27:31,199
Speaker 2: Would be great, might be a horrible, you know, a

483
00:27:31,240 --> 00:27:35,199
Speaker 2: horrible burning failure, but you need to let us know.

484
00:27:35,520 --> 00:27:40,399
Speaker 2: So I think now's the perfect opportunity to build up

485
00:27:40,400 --> 00:27:44,360
Speaker 2: that loyalty and that emotional bank account with our clients

486
00:27:44,359 --> 00:27:46,480
Speaker 2: and kind of go come along with us. We don't

487
00:27:46,520 --> 00:27:47,920
Speaker 2: know if this is going to work, but why don't

488
00:27:47,920 --> 00:27:51,440
Speaker 2: you learn with us, help us out, and we'll teach

489
00:27:51,480 --> 00:27:53,959
Speaker 2: you along the way with what's going on and certainly

490
00:27:53,960 --> 00:27:57,080
Speaker 2: what we're seeing out of the EU, you know, the

491
00:27:57,240 --> 00:28:01,399
Speaker 2: clients are voting with their dollars and brand loyalty is

492
00:28:01,480 --> 00:28:08,199
Speaker 2: exceptional with those organizations that are being very, very transparent

493
00:28:09,119 --> 00:28:16,480
Speaker 2: around how they're utilizing AI and how their business values

494
00:28:16,640 --> 00:28:19,760
Speaker 2: are now transitioning and aligning with AI to ensure that

495
00:28:19,800 --> 00:28:21,720
Speaker 2: their clients know exactly what's going on.

496
00:28:22,240 --> 00:28:26,000
Speaker 1: You're talk in the book about sort of AI governance

497
00:28:26,000 --> 00:28:28,399
Speaker 1: and has been you know, this is just whole conferences

498
00:28:28,440 --> 00:28:31,359
Speaker 1: in our run on this and lots of well paid

499
00:28:31,400 --> 00:28:34,239
Speaker 1: lawyers and consultants are working on it. And I can

500
00:28:34,320 --> 00:28:36,320
Speaker 1: understand that for the top end of town, you know,

501
00:28:36,359 --> 00:28:40,560
Speaker 1: the big companies, they need probably a team or a

502
00:28:40,640 --> 00:28:43,440
Speaker 1: chief AI officer to oversee all of this. But for

503
00:28:43,520 --> 00:28:46,080
Speaker 1: small and medium sized businesses, they're probably thinking, how do

504
00:28:46,120 --> 00:28:47,840
Speaker 1: I even approach this?

505
00:28:48,040 --> 00:28:48,160
Speaker 2: Now?

506
00:28:48,200 --> 00:28:50,840
Speaker 1: There is governance built into some of the platforms that

507
00:28:50,880 --> 00:28:55,520
Speaker 1: they're using. To some extent they are there's transparency, there,

508
00:28:56,000 --> 00:28:59,920
Speaker 1: there's security around these cloud platforms, as long as you

509
00:29:00,120 --> 00:29:04,640
Speaker 1: not in putting stuff into large language models that is

510
00:29:04,720 --> 00:29:07,400
Speaker 1: going to be used to improve those large language models.

511
00:29:07,440 --> 00:29:11,120
Speaker 1: I think businesses understand the risks around that. But for

512
00:29:11,320 --> 00:29:14,640
Speaker 1: the smaller sized businesses in Australia and New Zealand, what's

513
00:29:14,640 --> 00:29:18,480
Speaker 1: your advice to approaching governance making sure that you can experiment,

514
00:29:18,520 --> 00:29:21,680
Speaker 1: but do it safely and not really upset your customers

515
00:29:21,720 --> 00:29:23,840
Speaker 1: by inappropriately using their data.

516
00:29:24,320 --> 00:29:26,240
Speaker 2: Yeah, and look, the data is such a big thing,

517
00:29:26,320 --> 00:29:28,480
Speaker 2: isn't it, Because we've gotten so used to trading data

518
00:29:28,520 --> 00:29:32,360
Speaker 2: for convenience. But it's when we're trading our clients data

519
00:29:32,360 --> 00:29:34,760
Speaker 2: without their knowledge that it becomes a problem. So again

520
00:29:34,800 --> 00:29:37,800
Speaker 2: I think it's about getting all the people at the

521
00:29:37,840 --> 00:29:41,680
Speaker 2: table and just starting the conversation. The really important thing

522
00:29:41,760 --> 00:29:46,960
Speaker 2: to know is really nobody has the answers now, but

523
00:29:47,000 --> 00:29:49,880
Speaker 2: we've got to start having the conversations, you know, So

524
00:29:50,000 --> 00:29:51,920
Speaker 2: don't expect that you're going to walk out of a

525
00:29:52,000 --> 00:29:55,080
Speaker 2: thirty minute them meeting or a one hour team meeting

526
00:29:55,120 --> 00:29:57,520
Speaker 2: as well. Right, that's done, and you know next week

527
00:29:57,600 --> 00:30:01,160
Speaker 2: we'll be talking about this. You're going to be talking

528
00:30:01,160 --> 00:30:05,680
Speaker 2: about this for the next three years. So put something

529
00:30:05,680 --> 00:30:07,960
Speaker 2: in pencil doesn't even have to be in pen because

530
00:30:08,000 --> 00:30:12,000
Speaker 2: it's going to change. But you need to start those conversations,

531
00:30:12,040 --> 00:30:14,959
Speaker 2: and you need to be thinking about, Okay, do your

532
00:30:15,760 --> 00:30:18,760
Speaker 2: team members have their own phones or are they using

533
00:30:18,800 --> 00:30:21,720
Speaker 2: company phones? Okay, well they bring their own phones. Okay,

534
00:30:21,720 --> 00:30:23,760
Speaker 2: Well can they use chat GPT on their own phones

535
00:30:23,840 --> 00:30:27,120
Speaker 2: during business hours? Because what happens if they open up

536
00:30:27,800 --> 00:30:31,320
Speaker 2: open AI Chat GPT or whatever one that they use.

537
00:30:32,000 --> 00:30:35,080
Speaker 2: Because you know, I'm swamped at work and i just

538
00:30:35,160 --> 00:30:37,240
Speaker 2: want to get this email smashed out, So I'm just

539
00:30:37,280 --> 00:30:39,840
Speaker 2: going to quickly write it on chat GPT and then

540
00:30:39,880 --> 00:30:42,640
Speaker 2: flick it across to the work saying. You know, if

541
00:30:43,000 --> 00:30:46,360
Speaker 2: you haven't at least had that conversation, there are no

542
00:30:47,120 --> 00:30:51,160
Speaker 2: guard rails. So much like you know, only a few

543
00:30:51,240 --> 00:30:53,840
Speaker 2: years ago, companies were suddenly going, oh okay, we probably

544
00:30:53,880 --> 00:30:56,720
Speaker 2: need a social media policy. You know, get one of

545
00:30:56,720 --> 00:30:59,400
Speaker 2: the ms to write you large language model, get you

546
00:30:59,440 --> 00:31:01,840
Speaker 2: to get it to write you an AI policy if

547
00:31:01,840 --> 00:31:05,320
Speaker 2: that's what you need right now, and say I am

548
00:31:05,400 --> 00:31:09,400
Speaker 2: in this industry. You know, I'm a mortgage broker. Based

549
00:31:09,440 --> 00:31:14,520
Speaker 2: on the New Zealand Guidelines for AI Ethical Usage and

550
00:31:14,520 --> 00:31:18,320
Speaker 2: blah blah blah. I have a team of XYZ, they

551
00:31:18,360 --> 00:31:21,760
Speaker 2: have their own devices. We use Microsoft. We use this

552
00:31:22,600 --> 00:31:26,240
Speaker 2: draft me an AI policy. That can begin the conversation

553
00:31:26,440 --> 00:31:28,880
Speaker 2: with the team, because at least then you've got a

554
00:31:28,920 --> 00:31:31,560
Speaker 2: starting point to go, okay, well how does everyone feel

555
00:31:31,600 --> 00:31:35,600
Speaker 2: about this? And then they know that if they do

556
00:31:35,760 --> 00:31:38,400
Speaker 2: use their own device to create something and it gets

557
00:31:38,400 --> 00:31:43,000
Speaker 2: put through a work system, well there could be repercussions.

558
00:31:43,040 --> 00:31:45,880
Speaker 2: You know, they at least know. Okay, I'm probably going

559
00:31:45,960 --> 00:31:48,400
Speaker 2: to have to answer for that one, and I might

560
00:31:48,440 --> 00:31:53,960
Speaker 2: get a conversation with Karen from HR about you know

561
00:31:54,000 --> 00:31:56,960
Speaker 2: why we can't do that anymore. But we need to

562
00:31:56,960 --> 00:31:59,600
Speaker 2: start the conversations. That's the really big thing right now,

563
00:31:59,640 --> 00:32:03,600
Speaker 2: because going away, it's only going to become more and

564
00:32:03,640 --> 00:32:04,240
Speaker 2: more prevalent.

565
00:32:04,560 --> 00:32:06,480
Speaker 1: Finally, Tracy, towards the end of the book, you look

566
00:32:07,080 --> 00:32:13,560
Speaker 1: into the future and we're in the agentic AI era now,

567
00:32:13,640 --> 00:32:18,720
Speaker 1: which is really going from chatbots dispensing information to chatbots

568
00:32:18,760 --> 00:32:22,520
Speaker 1: being able to do things on our behalf. Take action

569
00:32:23,160 --> 00:32:27,600
Speaker 1: with approved parameters could be a purchase decision or approval

570
00:32:28,160 --> 00:32:31,880
Speaker 1: or processing information based on certain rules, we will okay

571
00:32:31,920 --> 00:32:34,280
Speaker 1: this or not. So you've got that you talk about

572
00:32:34,320 --> 00:32:39,040
Speaker 1: multimodal AI, which we've just seen Google VO three, which

573
00:32:39,080 --> 00:32:42,480
Speaker 1: is you know, audio video sync together. It used to

574
00:32:42,520 --> 00:32:44,440
Speaker 1: be sort of separate tools would do all of that.

575
00:32:45,080 --> 00:32:49,600
Speaker 1: So one AI that does sort of text video coding everything.

576
00:32:49,720 --> 00:32:52,880
Speaker 1: They're getting much better. This is all great, and you

577
00:32:52,880 --> 00:32:55,680
Speaker 1: said it's going to keep changing. But are we on

578
00:32:55,720 --> 00:32:59,760
Speaker 1: the cusp finally of seeing the promised productivity gains? Do

579
00:32:59,760 --> 00:33:00,280
Speaker 1: you think?

580
00:33:00,560 --> 00:33:05,320
Speaker 2: Absolutely? Absolutely? So. I'm already working with people. We're putting

581
00:33:05,560 --> 00:33:08,840
Speaker 2: agentic agents in still with a lot of human oversight,

582
00:33:08,920 --> 00:33:12,840
Speaker 2: I will preface that. And these things are never going

583
00:33:12,880 --> 00:33:15,320
Speaker 2: to be as bad as they are right now. You know,

584
00:33:15,400 --> 00:33:18,240
Speaker 2: we're still kind of hurting a bunch of toddlers running

585
00:33:18,240 --> 00:33:21,440
Speaker 2: around bouncing off walls, and you know, at Jim Brew's

586
00:33:21,520 --> 00:33:24,120
Speaker 2: right now, they're fueled up on red cordial and keen

587
00:33:24,200 --> 00:33:27,560
Speaker 2: to go. But you know, I was working with someone

588
00:33:27,600 --> 00:33:29,720
Speaker 2: the other day and she was saying to me she

589
00:33:30,040 --> 00:33:32,760
Speaker 2: has to get up at like eleven eleven, say, up

590
00:33:32,800 --> 00:33:35,200
Speaker 2: to like eleven pm to one am to ring all

591
00:33:35,200 --> 00:33:39,480
Speaker 2: of these places in Europe to organize things before the

592
00:33:39,520 --> 00:33:42,640
Speaker 2: CEO flies, you know, out to do the meetings. And

593
00:33:42,680 --> 00:33:45,640
Speaker 2: I was like, okay, that's interesting. So what if. And

594
00:33:45,680 --> 00:33:48,000
Speaker 2: then we looked at this agendic agent that could ring

595
00:33:48,040 --> 00:33:51,240
Speaker 2: out and make all of the restaurant bookings right, and

596
00:33:51,440 --> 00:33:53,720
Speaker 2: all she's got to do is verify yes, they've been made,

597
00:33:53,800 --> 00:33:55,800
Speaker 2: Yes they're correct, all the rest of it at eight

598
00:33:55,800 --> 00:33:57,640
Speaker 2: o'clock and seven o'clock in the morning when she gets

599
00:33:57,680 --> 00:34:02,120
Speaker 2: into the office like that would say hours a week. Perfect.

600
00:34:02,840 --> 00:34:06,040
Speaker 2: Let's try that then, but let's try that in isolation

601
00:34:06,600 --> 00:34:10,000
Speaker 2: and know that that is working before we then put

602
00:34:10,000 --> 00:34:14,000
Speaker 2: the next step in place. So it's it's we've got

603
00:34:14,000 --> 00:34:17,200
Speaker 2: to have the human and the loop right now. We

604
00:34:17,280 --> 00:34:20,000
Speaker 2: can't let these things run off fueled on red cordial

605
00:34:20,040 --> 00:34:22,839
Speaker 2: and go bouncing into walls. That's where the trouble's going

606
00:34:22,880 --> 00:34:27,000
Speaker 2: to happen. We still need, you know, the Peter Griffins

607
00:34:27,040 --> 00:34:30,959
Speaker 2: of the world to be sitting around going we didn't

608
00:34:30,960 --> 00:34:33,480
Speaker 2: want a table for six we wanted a table for sixteen.

609
00:34:33,600 --> 00:34:37,800
Speaker 2: You know, let's check that back in again. But again,

610
00:34:38,640 --> 00:34:41,160
Speaker 2: they're three, you know, they're six months old, they're twelve

611
00:34:41,200 --> 00:34:43,799
Speaker 2: months old. Depending on how all these software systems are,

612
00:34:44,360 --> 00:34:47,040
Speaker 2: they're never going to be this bad again. So if

613
00:34:47,040 --> 00:34:50,400
Speaker 2: we're not figuring out what we can do with them now,

614
00:34:51,800 --> 00:34:53,839
Speaker 2: We're cooked in twelve months time.

615
00:34:54,320 --> 00:34:58,799
Speaker 1: Good advice, Tracy, thanks so much for coming on. The

616
00:34:58,800 --> 00:35:02,279
Speaker 1: book is AI You Reimagining Business? Will put links to

617
00:35:02,320 --> 00:35:04,760
Speaker 1: where kiwis combine in stores.

618
00:35:04,800 --> 00:35:05,000
Speaker 2: Here.

619
00:35:05,760 --> 00:35:07,000
Speaker 1: Have you got an audiobook coming?

620
00:35:08,120 --> 00:35:11,439
Speaker 2: It will be coming. I have had a Nasti cole,

621
00:35:11,560 --> 00:35:13,440
Speaker 2: so I have to wait for my radio voice to

622
00:35:13,440 --> 00:35:13,839
Speaker 2: come back.

623
00:35:14,760 --> 00:35:17,680
Speaker 1: Well, you know, I think you've got such a great personality, Tracy.

624
00:35:17,680 --> 00:35:19,960
Speaker 1: I think that will be a great way to consume

625
00:35:20,560 --> 00:35:23,040
Speaker 1: the book. But thanks so much, lots of great ideas

626
00:35:23,040 --> 00:35:25,839
Speaker 1: there and as I say, really practical stuff for our

627
00:35:25,920 --> 00:35:29,040
Speaker 1: small and mid sized businesses. So good luck with the

628
00:35:29,080 --> 00:35:31,920
Speaker 1: launch of the book, and thanks so much for coming on.

629
00:35:32,080 --> 00:35:34,879
Speaker 1: Thanks Peter, I'll see you in end zed looking forward

630
00:35:34,920 --> 00:35:44,200
Speaker 1: to it. That's all for this episode of the Business

631
00:35:44,320 --> 00:35:46,920
Speaker 1: of Tech. A big thank you to Tracy Sheen for

632
00:35:47,040 --> 00:35:50,279
Speaker 1: joining us and sharing her insights on how small and

633
00:35:50,320 --> 00:35:54,040
Speaker 1: medium sized businesses can cut through the AI hype and

634
00:35:54,080 --> 00:35:57,680
Speaker 1: make real practical gains. If you want to dive deeper,

635
00:35:57,840 --> 00:36:01,560
Speaker 1: Tracy's new book is called AI and You Reimagine Business.

636
00:36:01,640 --> 00:36:05,880
Speaker 1: It's available now in paperback and digital form. There are

637
00:36:05,920 --> 00:36:07,880
Speaker 1: links to where you can find it in the show notes.

638
00:36:07,960 --> 00:36:11,279
Speaker 1: Go to the podcast section at Business deesk dot co

639
00:36:11,560 --> 00:36:15,280
Speaker 1: dot nz to find those. I think it's a really

640
00:36:15,360 --> 00:36:18,920
Speaker 1: great read for anyone looking to future proof their business

641
00:36:18,920 --> 00:36:22,600
Speaker 1: and take the first confidence steps into the world of AI.

642
00:36:23,200 --> 00:36:26,480
Speaker 1: If you enjoyed today's episode, don't forget to subscribe, leave

643
00:36:26,600 --> 00:36:30,320
Speaker 1: a review and share it with your network. Next week,

644
00:36:30,400 --> 00:36:34,480
Speaker 1: I'm joined by Mike Callender, CEO of two degrees and

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Speaker 1: Steve Yukovich, CEO of Kiwibank to delve into the results

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Speaker 1: of two degrees latest Shaping Business study. It's highlighted the

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Speaker 1: growing sense of optimism in our business community. You know,

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Speaker 1: businesses say they want to invest more. They feel they're

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Speaker 1: going to grow revenue in the next year. They're interested

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Speaker 1: in putting more money into technology, including AI. But is

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Speaker 1: it premature to say we're on the road to recovery.

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Speaker 1: Are we finally turning a corner? Well, let's find out

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Speaker 1: next Thursday with another episode off the Business of Tech.

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Speaker 1: I'll catch you then,