WEBVTT

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Michael, welcome to the show. Would you please

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introduce yourself? Hi, Sue. Lovely to be here.

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Good to have you. I'm Michael Ramsey, CEO and

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founder of Talk AI Global. And we are an AI strategy

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implementation firm. And what we do is that we

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help companies move from AI curiosity to ROI

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on their AI investment. Talk to me a little bit

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more about what's your vision for those you serve?

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Yeah, sure. So my vision is exactly that, to

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ensure that companies are able to get tangible

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returns from the AI investment. As you have said,

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what I've noticed in the market is that there

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is no structure to the implementation of AI.

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I've been on that side where I've been approached

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by many companies and I've built proof of concepts

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and different MVPs for companies. And what tends

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to happen is that it's usually coming from...

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the technology or from a siloed approach. And

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that approach generally does not work for something

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like AI because AI is expected to disrupt workflows.

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And by doing that, it needs a more structured,

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holistic approach to the organization, starting

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with the leaders of the organizations having

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an appreciation for what AI can do. and then

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tying it to tangible business objectives. So

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my vision for the people I serve is that they

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begin with their vision when they think about

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AI. So instead of thinking technology first,

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they think business first. What am I trying to

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achieve here? And how can I leverage AI to get

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there? And by doing that, you ensure that AI

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is used only in the areas where it can give you...

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the maximum returns. So as you know, a business

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may not necessarily need to put AI everywhere.

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And if it does that, it may be in problem. And

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what I've found is that, as I said, oftentimes

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the approach to AI comes from a place where a

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technology partner approaches a firm and they

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demoed something and it looks shiny. Because

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it looks shiny and it looks like on the surface

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it can do something, especially in a demo stage

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or maybe when it gets a proof of concept, they

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are interested in it. So they invest some money

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in it. But then when you talk about the scalability

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element of it, it's not there because it wasn't

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fully thought through to say, okay, do I have

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the structure? Do I have the data? Do I have

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the people? Do I have the right tech stack? Right.

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Some of that tends to happen because I've had

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those conversations where those process have

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had to help to help put some of those things

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in place. But when you have already been approached

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by a company and they say they want to do a particular

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project, it's very difficult for you to tell

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them what to do in their business. Right. Because

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they have made up their mind. They have done

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a business case sometimes. And nothing is wrong

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with doing a business case. Did you do a business

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case, for example, on all the potential areas

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that AI could be using in your business? That's

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the issue, right? You may just be doing the business

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case just as a rubber stamp just to ensure that

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your board sees that it was done through a process.

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But that process ought to start with vision.

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Where are you looking to go as a business? And

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when I talk to companies now, and I wrote about

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this in the book that is to be released in August,

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So when you're looking at revision, the focus

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ought to be on four strategic pillars, right,

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generally speaking. And these are four areas

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that most activities under business cover. It's

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either revenue, your operations, customer experience,

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or compliance and risk. So one approach they

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need to take is, which one of these areas am

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I going to? look to where I can use AI in. And

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it could be based off of existing initiatives

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that you have. Maybe you currently have a compliance

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issue because of a change in the regulatory environment.

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So now there is additional paperwork to be filed.

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So now, because you have that, you could potentially

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then look and say, okay, how can AI help me?

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to be able to can complete some of these regulatory

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requirements submit these things to the regulators

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faster more efficiently while not necessarily

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taking up more time for the business right or

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can i improve my regulatory scores so that my

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brand perception is higher in the market it's

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one year on the regulation then you go to operational

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efficiency we can just look generally i think

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even though there's a crossover but what you

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look on the operational efficiency you can think

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about um finance. You can look at other areas

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of the business where you can crunch down the

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times it takes to complete certain activities.

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For example, a lot of businesses spend an inordinate

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amount of time doing reports. So these are areas

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that AI can enhance the workflow. So that reporting

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can be done faster and decision making can happen

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quicker because there is more relevant data.

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So, for example, you know, sometimes you're doing

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accounting function and it takes a long time

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before you know exactly where the financials

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of the business is because there's so much paperwork

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to be done in order for you to get an up -to

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-date picture of your business. These are some

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of the areas that AI is being used to streamline.

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Oh, that's great. Yeah. On the customer experience

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side, it is being used to improve the customer

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relationship. With that being said, I don't expect

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companies to fully automate customer experience.

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It needs to be augmented with human touch. But

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what AI does, it enhances this experience. Yeah,

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it's amazing. And I love that you've thought

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that through so much because, you know, I'm used

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to dealing with entrepreneurs, you know, smaller

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visionaries, you know, not big corporations,

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but I know, you know, that shiny object syndrome

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is real. Like you see a new tool, must have it,

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you know, this is why AppSumo does so well. It's

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like, you know, buy this, buy that. This looks

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really cool. Hey, I'm going to, and then you

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end up with this Frankenstein of your tech stack

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that. You know, and it may not have ever even

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addressed anything that was really important

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to you. So starting with that vision first, like

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you're saying, you know, where do you want your

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business to go? And then, you know, what do you

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need? What do you what's the main next step that

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you want to tackle so that you're able to be

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strategic rather than just have a really cool

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collection of neat AI things? Exactly. Exactly.

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Right. And to be honest. The process works for

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small businesses as well as large businesses.

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What tends to just happen is that the solo founder

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or a smaller team, they're able to go through

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the process a bit quicker, right? So the larger

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team may need a one or two day workshop in order

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to really get the team together so that there's

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consensus. Because one of the issues with larger

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companies is that there's no consensus, right?

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And without consensus, the vision will never

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scale. So you need consensus because if you have

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one executive who is of the opinion that the

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business isn't ready for AI, then that executive's

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presence will cause a team to not necessarily

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buy into what's happening. So his idea for using

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AI is in operations, but another executive believes

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that the low -hanging fruit is in sales or compliance.

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Right. So without that prioritization and that

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buying, you tend to get conflict. Yeah. Right.

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It happens with other projects, too. But with

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AI, it's a lot more sensitive, as I said, because

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it's with a lot of technology. It's the ultimate

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in some process. Now with AI, it's almost like

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you're bringing in a human into your operation.

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You're expecting it to operate in a dynamic environment.

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And when you bring someone in your organization,

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you need them to have the full buy -in. In a

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dynamic environment, things need a lot more unity.

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This is not just a tool. If it's a tool, you

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could have some difference of opinion and still

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get something out of it. But this is something

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that's expected to transform your entire workflow.

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Yeah. And if at some point in the workflow there's

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a major hurdle, then you won't get the benefit

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from it. Right. Right. So suppose one executive

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refused to respond to an AI bot. Right? Yeah.

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Now what? Then what? That's right there is a

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roadblock. Right? So you need a unified approach.

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And as I said, with a smaller team, what tends

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to happen is that it's easier to get a unity

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because everyone is basically there. They're

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on the same page. There are less potential use

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cases to have conflicts around. So you just get

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through to the vision. The same thing. You go

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through the vision. You get a prioritization

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of your use cases, right? You look at your data

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infrastructure. Again, it could be a simpler

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architecture, right? So therefore, you could

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also be able to then move to the building phase

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a lot faster. But it's still important to understand

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where is the best use first. Yeah. Rather than

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just letting a tech demo determines that. Right.

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Oh, that's so great. I love that. I love that.

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And at its heart, here we're talking about one

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of the most futuristic things that we've ever

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had come into the marketplace. Obviously, it's

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fairly new on a larger scale. And the longer

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vision of time, you know, AI has been a very

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recent development, but it all still boils down

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to the vision. It does. It does. Right. And that

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is that is coming from just my strategy background.

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Right. Which I believe is unique in the tech

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space where when they talk about strategy for

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them, sometimes it's just about the data on the

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tech strategy. But at the end of the day, it

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does come down to people. Right. So therefore,

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you have to start with the vision for business

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because the business is still a group of companies,

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still a group of people. Yeah. So it starts there

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and then trickle down to the other areas of the

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business. And with a transformative technology

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like this, there is the additional fear of displacement

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that if not managed correctly, you will never

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get the return that you expect from the business.

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Because if you're taking it from the approach

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that, okay, because I'm maybe thinking about

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using two less people, so I'm going to quietly

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implement this thing. No, that's naivety, right?

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Again, I've seen that in institutions where if

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people decide to put up a roadblock, they can

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put up a roadblock. So therefore, you better

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be able to articulate a vision for them and to

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figure out how you can include them in the process.

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not just know but in the future so so the um

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the company that's thinking primarily about just

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cutting stuff may not certainly the best company

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um to go forward using ai right what you can

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think about potentially scaling without adding

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any additional people yeah that's a different

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approach right but you keep your people and you

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can enhance their roles with ai yeah right so

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because there's still going to be people in the

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loop Certain rules, what you used to spend the

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entire eight hours doing, now you're only going

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to do it for two hours. So therefore, the company

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needs to figure out what are you going to do

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with the additional six hours that's going to

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benefit the business in a major way to justify

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still keeping that person. I love that. It's

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so important because I think, you know, everybody

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has heard that phrase, oh, AI is going to take

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our jobs. Well, yeah, it could take, I don't,

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I can't even think of any job it couldn't do.

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Brain surgery, no problem, you know, down the

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road. Maybe not yet, but eventually. But there

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are things that only a human can do right now.

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And I think if we allow, strategically have AI

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help us do the things that it can do just as

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well as a human, it does free us up for that

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extra time. Like you said, what about those extra

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six hours now? Maybe we can do deeper work that

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humans only could do. Exactly. And when you talk

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about the deeper work, it's about the relationship

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side of business, right? Yeah. I believe too

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many organizations have too many people in back

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office shifting papers, right? And I'm not saying

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that to advocate for them getting rid of those

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people. I'm just saying an organization's life

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breath is based on getting new business. Yeah.

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And oftentimes you don't find the people who

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are focused on getting the business. being put

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at the limelight of the business. And what AI

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will do is to put those people at that center

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where their value is being understood at a larger

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scale. Because one of the last things AI will

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be able to do is sell convincingly, especially

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high -ticket items. Because there's a trust element

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in sale. Just like how there's a trust element

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in brain surgery where... I may trust the guy

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to do it than AI, unless AI can show me that

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he has done it maybe a thousand times. Brain

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surgeon maybe just needs to graduate from a reputable

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university. But eventually, with enough reps,

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you will trust AI. So you're right, AI will get

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there at some point. But the last thing it will

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do is to replace relationship building and trust.

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So now organizations will now be looking to transform

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our distributed stuff. Yeah. More people will

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be focused on relationship building. More people

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will be focusing on sales, right? So if people

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are not, so that's what I'm saying. If people

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are not comfortable with sales, you may have

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to get a little bit more comfortable with it.

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Or you can get more comfortable without actually

00:14:54.700 --> 00:14:56.740
building these systems for companies. So if you're

00:14:56.740 --> 00:14:59.159
more tech savvy, you can also learn because the

00:14:59.159 --> 00:15:00.740
material is out there now to learn how to do

00:15:00.740 --> 00:15:02.820
the thing on the technical side. But staying

00:15:02.820 --> 00:15:04.460
in the middle now and trying to shift papers.

00:15:05.070 --> 00:15:08.289
those days are going quickly. And you have seen

00:15:08.289 --> 00:15:10.409
it happen now in anything related to writing.

00:15:10.909 --> 00:15:14.389
Because that is what it has transformed over

00:15:14.389 --> 00:15:18.350
the past three years. But that is not the only

00:15:18.350 --> 00:15:20.970
use case for it because there's a lot of development

00:15:20.970 --> 00:15:24.970
happening now with agentic AI. And with agentic

00:15:24.970 --> 00:15:26.789
AI, what it's going to cause is that there's

00:15:26.789 --> 00:15:29.090
going to be an entire transformation of back

00:15:29.090 --> 00:15:33.179
office workflow. So the workflow is going to

00:15:33.179 --> 00:15:37.440
be designed with AI in mind, meaning all the

00:15:37.440 --> 00:15:41.519
processes are going to be mapped and AI potentially

00:15:41.519 --> 00:15:46.279
doing all those steps. And what you're going

00:15:46.279 --> 00:15:49.759
to need now is people to more or less monitor

00:15:49.759 --> 00:15:54.019
and do what I call reinforce those systems. Because

00:15:54.019 --> 00:15:57.220
AI, just like what you see sometimes use chat

00:15:57.220 --> 00:16:00.659
GPT, and it asks you a question like, the feedback

00:16:00.659 --> 00:16:03.700
it has for feedback up or down thumbs up or down

00:16:03.700 --> 00:16:06.340
many people will be doing a lot of that for for

00:16:06.340 --> 00:16:11.340
different um roles right it won't start there

00:16:11.340 --> 00:16:13.299
might start with additional things being done

00:16:13.299 --> 00:16:15.419
but a major part of it is going to be reinforcing

00:16:15.419 --> 00:16:19.159
those systems to say it's learning from the nuances

00:16:19.159 --> 00:16:22.519
yeah right because it's it's training and um

00:16:22.519 --> 00:16:24.860
it might be trained on the existing workflow

00:16:24.860 --> 00:16:28.389
it may be trained on outside data for a company

00:16:28.389 --> 00:16:31.730
that is similar to your industry. But every company

00:16:31.730 --> 00:16:35.049
is nuanced. And therefore, once it is implemented,

00:16:35.309 --> 00:16:37.970
you may need people to be able to reinforce that

00:16:37.970 --> 00:16:40.429
it's made the right decision under each conditions.

00:16:40.730 --> 00:16:44.470
And the more nuanced the environment is, the

00:16:44.470 --> 00:16:47.110
longer you'll be dependent on people for that.

00:16:47.669 --> 00:16:51.769
And trust element as well, right? So even when

00:16:51.769 --> 00:16:55.750
it becomes great between what potential policy

00:16:55.750 --> 00:16:58.940
regulations, Or otherwise, there is still going

00:16:58.940 --> 00:17:02.700
to, and just for your own safety in terms of

00:17:02.700 --> 00:17:04.900
protecting your brand, you're still going to

00:17:04.900 --> 00:17:09.059
want to have AI, sorry, a person to ensure that

00:17:09.059 --> 00:17:12.640
there is some guardrails to prevent one major

00:17:12.640 --> 00:17:16.769
hiccup from damaging your brand. Oh, yeah. Because

00:17:16.769 --> 00:17:19.890
it could happen. And it has happened in the past

00:17:19.890 --> 00:17:23.970
where when even Google, that is what caused Google

00:17:23.970 --> 00:17:25.910
to miss out and come in first to the market.

00:17:25.990 --> 00:17:28.470
Because Google for years was seen as the leader

00:17:28.470 --> 00:17:31.390
in AI development. But between Google and I think

00:17:31.390 --> 00:17:35.190
Microsoft, they released some products prematurely.

00:17:35.369 --> 00:17:39.170
And it showed some biased information out. And

00:17:39.170 --> 00:17:41.829
they had to peel back. and those technologies

00:17:41.829 --> 00:17:44.769
because they are major brands and they could

00:17:44.769 --> 00:17:48.630
not afford for any slip -up of sort to happen

00:17:48.630 --> 00:17:51.630
because they are public companies and one bad

00:17:51.630 --> 00:17:54.789
sentiment and the stock price is down 3 % and

00:17:54.789 --> 00:18:00.930
the market cap is down 50 billion. So you find

00:18:00.930 --> 00:18:03.730
that they missed out on it for that. Companies

00:18:03.730 --> 00:18:07.029
are cautious because of that. So therefore, proper

00:18:07.029 --> 00:18:09.230
guardrails are being done, which makes a lot

00:18:09.230 --> 00:18:13.609
of sense. Doing all different testing under different

00:18:13.609 --> 00:18:15.630
conditions just to ensure that whatever you put

00:18:15.630 --> 00:18:20.529
out there, it is safe and it is representative

00:18:20.529 --> 00:18:24.609
of your company's brand. Now, as you're building

00:18:24.609 --> 00:18:26.789
your business, we've talked about your vision

00:18:26.789 --> 00:18:29.569
for the people that you're serving. What is your

00:18:29.569 --> 00:18:31.730
vision for your actual business? Where do you

00:18:31.730 --> 00:18:36.690
want this to go? I want this business to continue

00:18:36.690 --> 00:18:40.839
to scale. i want my frameworks to be household

00:18:40.839 --> 00:18:44.460
names right i want i want when i talk about the

00:18:44.460 --> 00:18:47.880
abc framework or or when i hear about abc framework

00:18:47.880 --> 00:18:49.980
it not necessarily coming from anything i wrote

00:18:49.980 --> 00:18:52.859
so when someone is on your podcast for example

00:18:52.859 --> 00:18:54.799
they're talking about using the abc framework

00:18:54.799 --> 00:18:59.680
to implement ai in their business so that that

00:18:59.680 --> 00:19:02.000
is part of where i want to go i want the the

00:19:02.000 --> 00:19:04.519
systems that i've developed to become also names

00:19:04.519 --> 00:19:09.380
and by doing that then it will continue to build

00:19:09.380 --> 00:19:13.720
my business brand around what it has achieved

00:19:13.720 --> 00:19:17.700
for different companies. So I want to move, so

00:19:17.700 --> 00:19:19.039
you're talking about long -term vision. The long

00:19:19.039 --> 00:19:22.119
-term vision is that the effect I have on companies

00:19:22.119 --> 00:19:25.220
move from outside of the companies I've worked

00:19:25.220 --> 00:19:30.400
with directly to the point where it is from other

00:19:30.400 --> 00:19:34.039
companies using systems. Basically, I've trained

00:19:34.039 --> 00:19:36.640
people and they've read my book. And they're

00:19:36.640 --> 00:19:40.240
now using that in other industries and in other

00:19:40.240 --> 00:19:45.500
areas and people that I've never met. I like

00:19:45.500 --> 00:19:47.839
that. What do you imagine the greater ripple

00:19:47.839 --> 00:19:50.980
effect to be that all of this could cause as

00:19:50.980 --> 00:19:54.599
your vision starts to take shape? So what it

00:19:54.599 --> 00:19:59.140
will cause is a faster adoption of AI and in

00:19:59.140 --> 00:20:04.740
a safe and equitable manner. So what I want is

00:20:04.740 --> 00:20:10.869
that the people move from hype to action fast,

00:20:11.170 --> 00:20:14.910
right? So by having clarity about how AI can

00:20:14.910 --> 00:20:20.769
be used, we prevent many major public and private

00:20:20.769 --> 00:20:25.990
cases of AI being a flop and then having both

00:20:25.990 --> 00:20:28.349
individuals and companies turning their backs

00:20:28.349 --> 00:20:33.109
on what AI can do and then being caught. caught

00:20:33.109 --> 00:20:35.349
behind when they realized that those one -off

00:20:35.349 --> 00:20:38.150
incidents should not have been used to be turned

00:20:38.150 --> 00:20:41.769
off from the technology. So I've been doing education

00:20:41.769 --> 00:20:44.170
piece outside of just for the business because

00:20:44.170 --> 00:20:46.650
I want people to understand that changes are

00:20:46.650 --> 00:20:49.069
happening fast. And what you don't want to do

00:20:49.069 --> 00:20:51.069
is that when your company comes and sits ready

00:20:51.069 --> 00:20:54.930
to move to the next level, you have to upskill

00:20:54.930 --> 00:20:58.900
yourself to grow with that company. So part of

00:20:58.900 --> 00:21:01.160
my vision is also to help bring people along

00:21:01.160 --> 00:21:06.579
so that what I foresee is potentially without

00:21:06.579 --> 00:21:09.740
that, there will be a major displacement in the

00:21:09.740 --> 00:21:13.700
short run. And I want people to understand and

00:21:13.700 --> 00:21:16.579
companies to understand how they can scale so

00:21:16.579 --> 00:21:18.579
that when they use AI, they're not just thinking

00:21:18.579 --> 00:21:21.500
about cutting costs by people. They're thinking

00:21:21.500 --> 00:21:25.539
about how they can grow their business. So the

00:21:25.539 --> 00:21:28.859
vision is really to protect. the next five to

00:21:28.859 --> 00:21:32.660
10 years, which I believe is crucial in terms

00:21:32.660 --> 00:21:35.259
of how AI will affect our lives. Thank you for

00:21:35.259 --> 00:21:37.279
being here today. I'm really happy that you tuned

00:21:37.279 --> 00:21:39.559
in to Vision Pros Live. I'm looking forward to

00:21:39.559 --> 00:21:42.859
seeing your reactions as these episodes continue

00:21:42.859 --> 00:21:44.619
to move forward. This is going to get more and

00:21:44.619 --> 00:21:46.680
more fun. We'll have more and more engagement

00:21:46.680 --> 00:21:48.759
as well. We'll invite people to participate in

00:21:48.759 --> 00:21:50.920
the show. And thank you for giving us your time

00:21:50.920 --> 00:21:53.220
and attention. Have an excellent time building

00:21:53.220 --> 00:21:55.579
out your vision and becoming a Vision Pro yourself.
