March 31, 2026
The AI Agency: How Bold Leaders Build Scalable, Human-Centered AI-Without Losing Their Soul
The AI Agency cuts through AI hype to show leaders how to move from endless pilots to real business impact. Inspired by Divya Parekh’s work, it focuses on turning AI into a strategic partner, building scalable systems, and leading with clarity and ethics. With practical frameworks and real-world insights, it’s a playbook for integrating AI effectively—without losing culture, people, or purpose.
Beyond Confidence is broadcast live Tuesdays at 10AM ET on W4WN Radio - Women 4 Women Network (www.w4wn.com) part of Talk 4 Radio (www.talk4radio.com) on the Talk 4 Media Network (www.talk4media.com). Beyond Confidence TV Show is viewed on Talk 4 TV (www.talk4tv.com).
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WEBVTT
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The topics and opinions expressed on the following show are
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solely those of the hosts and their guests and not
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This is Beyond Confidence with your host, DV Park. Do
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you want to live a more fulfilling life? Do you
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want to live your legacy and achieve your personal, professional,
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and financial goals?
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Well?
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Coming up on ZVO parks Beyond Confidence, you will hear
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real stories of leaders, entrepreneurs, and achievers who have steps
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into discomfort, shattered their status quo, and are living the
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life they want. You will learn how relationships are the
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key to achieving your aspirations and financial goals. Moving your
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career business forward does not have to happen at the
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expense of your personal or family life or vice versa.
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Learn more at www dot Gvpark dot com and you
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can connect with v ants contact dance gvpark dot com.
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This is beyond confidence and now here's your host, giv Park.
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Good morning listeners, It's Tuesday. I'm so thrilled to be
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here with you all. So today we are going to
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be talking about how we can scale with AI. How
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can leaders bring in AI into the organizations. If you're
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an entrepreneurial, how can you bring AI into your lives?
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How can you dance with AI without losing your soul?
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Because the key thing to remember is that at the
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intersection of AI and business, it is very important to
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have humans at the home because without humans, without us,
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AI is not anything. So as you scale or as
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you adopt, really crucial to have that in mind. So
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first of all, let's tackle and talk about the feelings
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and emotions that nobody talks about. Because when you're going
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for a adoption, people are going to be thinking yay,
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especially early adopters. There's a lot of excitement, enthusiasm, what
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more can be done? This could change everything? Then there
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could be curiosity what's possible here? Because in twenty twenty
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two when open AI came in, people were just kind
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of getting to know and like thinking, h this is
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something new. But I want you to travel back a
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few years back. You know, we did not have GPS.
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We had those maps, and I still remember taking those
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big maps and going on trips and having fun. And
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then came GPS, then came email, then came automated voice messages.
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So EI has been around, just not so much in
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the face. So the first thing is to take a
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step back and look at AI for what it is,
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coming to learn about AI, checking it out with curiosity
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what's possible here while knowing that it is not perfect.
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That is the critical piece to remember. And then sometimes
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what happens, especially if you're just kind of getting to
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know AI, or if you're a small organization, or even
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if you're a big organization, you bring in AI and
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then you have started tool, you're doing pilot, and while
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you're uploading some features, you are developing training programs. Every
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twenty seconds, there is that change, there is that oh mom,
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And then what happens is okay. The first question could
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be where do I even start? Another could be I've
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already started, I've already implied, and now there's hold this upgrade.
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What am I going to do? And as a result,
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of that, it can create that uncertainty, that feeling of
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doubt as to am I behind And that's always going
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to be the case. What's going to happen is that
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there's always going to be new things. So regardless, if
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you're feeling all of that, it's okay because that's where
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you are supposed to be. And now the key things
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is it's important recognize the feelings because whether you are
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bringing in AF just for yourself, or whether you're bringing
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in AF for the organization, or you're bringing in for
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your business, or you are helping somebody else adopt AI,
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these are the questions to ask. And I just kind
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of tell a story. So one of my clients was
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leading a whole AI department in a very big, reputable company.
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Thought his job was secure, his team was secure because
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they were the ones who had launched it. But what
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happened was and the reality is that they had made
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it so well that they could be eliminated. So he
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and his whole team was just let go. Who would
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have thought that an expert in artificial eelligence, that expert
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who had built the whole structure for the company, he
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and his team would be gone. So yes, they were
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laid off and guess what, because there were new updates,
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there were new changes. What happened was other people didn't
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know and then started crashing. So that is just one story.
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And some companies they are bringing an AI without looking
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at the process. In some companies they have built it
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to a very good extent, but have taken the humans
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out of the equation. And that's where these are just
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a couple of examples. Their problems happened an AI adoption failed.
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I mean some parts were successful, some parts were failing.
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And then when my client came to me and said, Tavia,
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what do I do over here? He felt so disappointed.
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He felt disillusioned and just that feeling of emptiness and
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he was saying to me, I feel like I'm looking
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into abyss. I was so excited about it. So the
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key is knowing how to deal with AI. And that's
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where not only my disclient let's call him John, but
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a lot of my other clients where I've helped them
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work through the era of AI to make themselves future proof,
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to make the A adoption, integration and governance in such
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a way that it is our partner, not something that
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can take away jobs. That's why I wrote my book
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The AI Agency, and the thing is that what happens
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is I want us to kind of look at some
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of these failures that I talked about. Companies are chasing
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tools instead of outcomes, that too many disconnected pilots. There's
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no clear ownership and there's no definition of success. So
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it's not about what AI can we used, it's not
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about which tool we can use. It's important that we
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stop talking about it over there. The key is what
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problem is words solving. And even before we go into
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what problem we are solving, it's important to talk about
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the AI governance. And when we talk about AI governance,
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is that what it's going to look like. Who's going
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to own the decisions? And Yes, there's so much to
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talk about that today. We're not going to go into
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all that details, but these are the things to remember,
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so think about it. Let's we talk about, like, Okay,
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which is the problem I want to solve. Whether you're
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in an individual entrepreneur, individual leader, or an organization, that's
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like the first thing we talk about. So let's say
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one of the problems is I'm just going to share
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a story where there's this team who had to do
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a lot of testing, and because they were testing the
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same thing, a lot of Q testing is involved. It
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is an iterative process, it is mechanical, and it was
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taking people's motivation away. So what they did, and this
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is just one piece of the product I'm talking about.
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So as I was helping this team, what we did
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was we took all the processes that they had and
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out of that we narrowed down what was the most
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painful process for them. And from there, the painful process
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was where there was a lot of grind every day,
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day to day mechanical work, where people were not being challenged,
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there was no growth opportunities, no meaning, no satisfaction. And
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then we broke it down into chunk And when you
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take this process and break it down into chunks, then
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you take a look at it. You sit down and
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you assess how much time does it take for a
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human being to do it? Where will the automation help.
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And then the key is starting out with a small
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pilot where it is a focused use case. Another important
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thing to remember is having clear metrics. And when you
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start out with a small use case, work through the problem,
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fix one thing, and you find that the results are good,
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then you move to the next space. And of course
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you can do multiple things at the same time too,
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but then you need to have multiple teams doing small pilots.
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And the reason, the key thing is that one thing
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that I want to introduce in this is a business
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technology ethics framework. I call about the three things to
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work on business. Why does it matter that we are
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working on this problem? Super important? Okay, here was like
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you know, not only it's taking going back to that process.
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Not only it was taking them fifty hours, white matters
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if you take a look at it, it was using
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a lot of men power, and of course when it
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uses a lot of menpower, it impacts the profitability too.
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So that was the business size. Now we look at
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the second piece of the framework technology, What enables it?
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Do we need to automate, do we need to create workflows,
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do we need to have agentic AI? What is it
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that we want to include. So then we took that
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part of the process and what they did was they
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took only painful pieces of the process to automate it.
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They built in a lot of humans in the loop. Yes,
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that's exactly what I mean. Because artificial intelligence will hallucinate,
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it has the confidence of the person of a person
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who may be wrong, but things that they're good. So yes,
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artificial intelligence can make mistakes, whether it's CHGPT claud if
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wich isnthropic, or even if if you have open Claw,
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or if you have a Gemini, or if you have
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the cowork which has been released from Claude for doing
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agentic work. You can have any of that and it
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can still make mistakes. So that is the key to remember.
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So ethics is what protects the data, what protects the process,
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and what protects the people. So these are the key
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things to remember because remember if you don't have ethics,
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like when I'm talking about this framework business technology and ethics,
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if you don't have it, the risk can be your
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employees can get impacted. And I'm going to go back
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to that story. So that is from Sean and Chantel.
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I'm just going to share about these two people, you know,
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Sean and Chantell other characters in my book, and one
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time they are doing this pilot and what they're doing
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is that every step wherever there's a quality assurance testing,
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they're putting in a developers check where they're making sure
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that the AI is checking upon themselves and also humans
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are checking at certain levels and why human check is important.
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So let's say if a decision comes in that is wrong,
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which AI may have hallucinated or skipped over a step,
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then a human being, let's say Sean had really good
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experience in the quality insurance testing. He knows he knows
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it in and out, and when something is wrong he
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can put a finger on it. He'll be able to
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identify it. And when he's able to identify it, guess
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what's going to happen. They are going to be able
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to fix it. Otherwise it can keep on looping and
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churning out wrang outcomes and wrong results. So going back
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to that process, what we did was they had put
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in a lot of checks and they ran the pilot
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for a quick twenty days, moved through a lot of failures,
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remove a lot of kings, but at the same time
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they reduced the human checks. So initially the human checks
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were let's sit ten at ten checkpoints. They kept it
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now at three pain points. But knowing that working with
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AI is iterative, you make it and then you find
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that where is it not doing it right? Where it
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can do better, just like any human beings. So think
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about it like you know, as a if you were
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a human resource professional or a human resource leader or
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a chief people officer, you are going to invest that training.
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You are going to invest in those employees, in your
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succession planning, in your emerging leaders. You are going to
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allow them. You are going to give them the space
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to grow, to make mistakes. So same thing. Artificial intelligence
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is no different. So the key is like having those
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three elements because when you bring in ethics, when you
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bring in that governance, that Okay, how are we going
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to deploy how are we going to make sure that
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we keep our employees because their experience matters, the experience
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that sitting in people's heart and brain, the knowledge that's
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not on the web. So remember, yeah, it does not
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have access to everything. And when you are bringing in ethics,
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the risk to your employees, your top talent leaving your company,
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or your customers getting unhappy, or your brand getting stigmatized
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or your brand getting a bad name goes significantly low
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because you've tested it, you've tried it. The key thing
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to remember with artificial intelligence is that there will be
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at certain points, certain segments which you have tested, where
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you will trust it because there's still automation in the
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whole world. Yes, developers are doing the testing and all that,
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so it's no different than artificial intelligence doing it. So
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when you apply the same principles what had gone in before,
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