Everyday AI Podcast – An AI and ChatGPT Podcast - EP 139: How To Transition to an AI-First World

Episode Date: November 7, 2023

When will our work lives become infused with AI and we find AI everywhere we go? How can we transition to that AI-first world? Tina Yazdi, Founder and Host of The AI-First Business Podcast, joins us to discuss how you can transition your business and career to an AI-first world. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Tina and Jordan questions about an AI-first worldUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: [e-mail] with Jordan on LinkedInTimestamps:[00:01:20] Daily AI news[00:04:15] About Tina and AI-First Business Podcast[00:06:17] Challenges business face adding AI[00:08:55] How long until AI is everywhere?[00:12:40] Businesses transitioning to AI-first[00:17:45] Will AI help balance competition?[00:22:25] AI benefits for enterprises[00:25:25] Tina's final adviceTopics Covered in This Episode:1. Challenges businesses face in implementing AI2. The importance of data quality and collection3. Essential steps in AI implementation4. Business results and productivity opportunities with AIKeywords:AI, work lives, infused with AI, AI first world, transition, decade away, couple years, months, AI news, livestream, podcast, daily newsletter, OpenAI developers day, GPT 4 turbo, ChatGPT, developers, outside documents, modalities, DALL E 3, vision, upload documents, cheaper, copyright shield, enterprise, API customers, legal protection, price, default mode, memory, hallucinations, custom GPTs, data stack, narratives, organizations, data availability, data pipelines, data quality.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Start Here ▶️Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com Also, here's a link to the entire series on a Spotify playlist. 

This is the Everyday AI Show, the Everyday Podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business, and everyday life. Meet Firefly AI Assistant, now live and Adobe Firefly, the All In One Creative AI Studio. Just describe what you want to create and the assistant handles the rest, orchestrating multi-step workflows across Photoshop, Premiere Express, and more in one conversational interface. You direct the outcome. The assistant accelerates execution. When will the time come when our work lives are just infused with AI?

And it's everywhere we go in our work, in our business, and our companies. Are we a decade away, maybe a couple of years, months? And then how do we transition to that AI first world? We're going to be talking about that today and a lot more on everyday AI. Welcome. My name's Jordan. I'm the host and I guess you're your guide to learning and leveraging AI. So I'm extremely excited to talk to our guest today about how we can transition to that

AI first world. But before we do, as always, we're going to go over the AI news for the day. And hey, if you're joining us on the live stream, thank you. Let me know where are you joining us from. I always like to see that and to engage with our live audience. If you're listening on the podcast, thank you as well. Make sure to check out your show notes. We always leave a link to go sign up for our free daily newsletter as well as other relevant episodes on today's topic.

So make sure you check that out. All right. So normally we run down a whole list of things in AI news, but pretty big news yesterday. So we're just going to focus on actually one thing. So if you want to get the rest of the news, we got it. Don't worry. Just go to your everyday AI.com and sign up for it. But yesterday, big news.

So let's recap it. We had the open AI. Developers Day and a ton of news when it comes to OpenAI and chat GPT for developers. But I'm going to break it down real quick in this little quick news segment on what it means for everyday people because it's not just for developers. But high level, here's what happened at the Open AI Developer Conference. So they announced GPT4 Turbo, which is their newest and kind of most refreshed model, which is supposed to be much stronger and a way longer context.

A couple other things is being able to, for developers to have better knowledge. So being able to bring in outside documents by default in their products that they build, as well as new modalities, which we've seen these kind of already. So, you know, Dolly 3, Vision, the ability to upload documents and to be able to work with those and chat with those. So, you know, now chat GPT developers or GPT developers have that ability to bring that kind of functionality to the products that they built. So a couple of things, that is going to affect just about any GPT related product that you use. So get ready for a lot of changes there, but a couple other, I'd say three, actually two big ones for everyone else. So we have Copyright Shield. And that's going to be

mainly for enterprise and API customers. But Open AI is following suit for other companies like Adobe who are offering some of that copyright protection. So if someone gets sued for using their product, they will offer a sort of legal protection with the copyright shield. And then we have as well, it's going to be cheaper, right? That's the other thing, about two to three times cheaper. So maybe those products that you use that are very expensive might come down in price. And then last but not least, chat GBT, some big updates. So yes, the default mode for GPT4 will be turbo.

So faster, better, and a much wider range of memory for chat GPD. so hopefully fewer hallucinations, as well as GPTs, which are custom GPs that you can build without code, being able to upload documents, train it to respond a certain way. So very exciting news out of the Developer Day. And again, more on that and a lot more on what's happening in the rest of the AI news world. Go to your Everyday AI.com. But you didn't come here to hear me rant about ChatGPT and Developer Days. you came to learn how to transition.

You're listening because you want to know how to transition your company or even yourself to an AI First World. So I'm very excited to bring on our guests for today. And please, if I can get it right here, help me welcome to the stage. There we go. We got her. Tina Yazdi is the founder and host of the AI First Business podcast. Tina, thank you for joining the show. Hi, Jordan.

Thanks so much for having me on. I appreciate you. It's always fun to have another podcaster on the show. I've done it two or three times. It makes for fun conversation because we like just chat about AI all day. So tell me maybe a little bit, Tina, about the AI first business podcast and what kind of your focus is there. Yeah, for sure. So the AI first business podcast came about as a conjunction of a few points in my background.

One is that I have a philosophy degree specialized in AI. I also worked for a number of years selling a product that implemented into the data stack of startups and big tech companies. And that gave me a combination of exposure to some AI hygiene and also some real field experience on what the data stack actually looks like behind the scenes of these companies that we put on pedestals. And in the last year, those two things kind of collided together

where I was witnessing a lot of narratives around the upside down inevitability of the impact of AI on our world. And I don't agree with that. I think there's a slightly different narrative that I think might be a bit more pragmatic and closer to reality, which is that the transition is going to be fast but slow. And organizations are going to need a lot of time and a lot of unsexy admin work to be in a position to truly implement an AI-first habit into organizations. Tina, you bring up a great point because I think people think of AI as something sexy.

They're like, oh, yes, look at this. It's the balance of whistles. It's going to make everything great. But to get there as an organization, it takes unsexy work. You got to do the admin, updating your governance, your legal. So talk a little bit about challenges that you see businesses are facing on getting to that point where you can actually start implementing it. Yeah, absolutely. So my background is working with enterprise and large multinational groups in general.

So this is kind of more the angle that I'm coming from regarding this. I think the first thing is just having the data available at all. At this moment, I can pretty confidently say that most organizations don't have the quantity of data to run AI algorithms with any level of reliability. They're doing it more as a game of novelty, which if that's the introduction to get your team comfortable with having it available in your organization, there is some merit to that. But in terms of bringing an output that you can actually make decisions on or improve your cogs, like I don't think that's quite what's going to be the outcome of that. The danger of that is also it kind of will already start to erode trust in something that has shaky trust foundations among executives anyways. And I think the other thing is the true load of work, like kind of in combination with that is like the data quality and the data collection. That takes a lot of like data pipeline building, a lot of unifying your data warehouses.

And this means hours and hours spent by data engineers doing work that isn't actually AI yet. And I think those are some of the things that I don't really hear talked about. And I think you can't really skip those steps and have, you know, any, like, business results coming from AI. So I think one of the dangers of the cycle is that, one, it creates a situation that kind of will lead to an outcome where executives are like, ah, I told you we can't trust AI or I told you this was useless. And it kind of, like, you know, creates a cycle of despair. And the other is that it leaves such a big opportunity on the table where you can't trust AI or I told you. can have more productive teams. You can have people working on things that they love to do and do less of like the grunty work that they don't like to do. But without the foundation,

that transition won't happen. I don't think. Yeah, I think we're all looking forward to less grunt work and more meaningful or more exciting work. And hey, everyone joining life. Thank you. You know, Shannon said, good morning. AI curious world. And I'd like to know also, like get your questions in for Tina. What do you want to know about kind of this AI first world? and, you know, becoming an AI first organization. And maybe let's start there. I'm going to rewind. And, you know, how I start at the top of the show is talking about when, right?

So when will our business lives? And I'm sure it depends on, you know, where you live, right, whether you're in the U.S. or Europe or elsewhere, you know, how your business may be transitions to this. But from your vantage point, with your background, Tina, what are you seeing? Are you seeing it's very far away until AI is infused in every point? part of our business day to day, or do you think maybe it's coming faster than some might think? It is really scary to answer that question

because I need to draw a line in the sand for myself as well. I think I'm going to be, I'm going to stick to that I think will be fast but slow. I think the conversation around AI is unavoidable and everyone's talking about it. And thank you, Mike. He just mentioned that you can't really skip those ups. I'm kind of drawing a little my experience,

rolling out other types of data updates to organizations, And given how those processes go, I'm going to make some assumptions that it's going to be similar with AI transitions. Because AI, an AI transition is ultimately a data, it's a subset of your overall data strategy and data, like a vision. What I'm seeing happening is that there is interest

in like level one AI tooling. And in fact, level one AI tooling has been around for years. I work in SaaS sales and we have a number of AI style tools that have been forced upon us like starting 2016, already, I can safely say. So that's nothing new actually. And these are things that analyze your recorded calls and give you suggestions on how to improve them.

They scrape the data that you have internally on customers and help you make better like either categories or decisions about how to manage those, things like that. Those are becoming a little bit more advanced and those are the things that are being rolled out right now. There's already some blockers there. We just talked about this before the show, which is that the security and legal teams

will probably be the number one stumbling block to that. which is very much their job. Their job is to maintain a level of conservative, sober analysis on bringing new technologies into the organization. But on the other hand, I don't see them being very well prepared to do something as simple as sign a master cloud agreement with an AI service, because it just has variables in it that they've never had to deal with before. And there's no preexisting examples that they can like,

cost, you know, copycat to, to have confidence that they're making the right decisions. And so I feel like there's a little bit of a cat and mouse game there. And I think that's going to prevent companies rolling out these technologies, even at the level one stage, to keep up with productivity. I think younger companies and tech startups and particularly companies in the U.S. versus Europe are better positioned to move fast and get that competitive edge. But I think that's for like larger organizations is for sure going to be a blocker. And I think the other one is kind of like, I think companies might underestimate the resources required and the maintenance to get your data and have the right team in place to build like sustainable long-term algorithms that provide business value for years to come. Like that will require a lot of foundational work that I don't know if it's in the fiscal budget, if it's in the headcount, if there's leadership, they can put together a team on like a three-year plan.

And I don't know if there's an appetite to have a long-term vision, which you cannot avoid to roll these things out. It's just going to have to be a long-term game. So I think those are some of the factors that will influence the speed to market of AI-first habits in organizations today. Yeah. And Tina, I love what you said. And I completely agree the fast but slow, you know, kind of piece to this because generative AI has been on the scene for a long time, right? But it's been kind of quote unquote mainstream for a year now, right, since chat GPT was released last November. This kind of opened up a lot of company's eyes to the power of generative AI.

So what kind of pieces do you see have to fall into place for this fast but slow kind of transition to an AI first world to take place, right? Because we talk like, okay, legal team. There's there's data. There's governance. What are kind of some of those key pieces that if someone listening to this podcast is maybe a small business owner or they're a decision maker and a larger company, and they're not there? Like, what are those pieces that they have to get moving together to get to the place where they can be ready when they're going to need the power of generative AI? So in terms of the fast and slow, I talked about the slow. Let me talk a little bit about the fast, which is bottom up.

And I'll talk a little bit more about the slow, which is top down. What I think will drive the speed here is that your employees are users in the real world and they are users of technologies. They are like obviously also the same people who are using chat GDP. I think one of the things that is forcing the hand for organizations to figure things out quicker and is also providing the firepower behind things like, you know, IBM's Watson and Salesforce's Einstein is that whether you like it or not, your employees are going to try to. to do things in the most productive way possible. And that means they're already using generated by AI that's in the wild right now. And that is causing serious enterprise gap, security gaps and concerns. And I think that kind of forces you to like smart, smart prepared enterprises will have to

acknowledge that they're going to be using it. So you might as well create a guardrail for them to use it within the like liability framework that you're comfortable with, which means like you need to figure out a way to find agreements to like either purchase this and bring it internally or create some kind of guidelines to operate by. So I think that's going to be where the fast comes from. Like it's happening. Whether you like it or not, it's up to you whether you adapt or not or just like put your head in the sand and you know, I don't think that has historically worked well for organizations. In terms of what I what I've seen the best in class organizations get into place to have a working

movement towards AI first. One is you need a dedicated team for AI that has both a short-term ROI scope and a long-term ROI scope. An example of this could be like, for example, gaming companies. And what I mean by that is, you know, transitioning your data and your algorithms to take advantage of AI has an element of like an element of ambiguity to it. So it is totally, of course, appropriate that you have some short-term ROI that you put the team against that you need to see in the next year or so, but unless they also have a bit of a scope to play around and build longer-term systems to have RIs like three years from now, maybe not immediately in the next year, it might be a little bit hard to see the true potential of AI unleashed for where

you're heading as a business. I love that point. And there's such a disparate. there because I feel like for, for, you know, medium-sized businesses especially, planning for long-term ROI is is the norm. But, you know, preparing for short-term ROI. If I'm being honest, yeah, I've been a, you know, a digital dork now for 20 years. I've been working in different, you know, marketing and tech and comms roles professionally for 20 years. And I haven't seen anything, not even the internet, that can provide such a short-term

ROI. It's hard to measure, I feel. Like, Tina, like, and I know this is a tough question, right? It's the trillion dollar question. But, I mean, what are ways that companies can kind of even gauge that, like, short-term ROI from generative AI because it's so fast and we don't have really a roadmap to follow necessarily? Adobe just introduced an entirely new way to create, bringing the power and precision of its creative suite into one conversational experience. Meet Firefly AI assistant. now live in the Adobe Firefly app, the all-in-one creative AI studio.

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See it today at firefly.adop.com. Yeah, I would say like I think one of the classic use cases or business cases for AI is just the automation one where you can just take this goes back to like the grunt work, right? So there's like something that has a lot of grunt work or a lot of manual lift from particularly your developers and technical team. And can you do something with AI that increases the accuracy of the of the results that you're making decisions on and reduces the hours spent? And then the ROI is like pretty basic. It's like the hour like the cost per hour for the employees in question and like reducing that. That's a really simple calculation that you can do. But also I'm not thinking a little bit like in the cybersecurity space.

Like if there's for example a certain service that you run to audit something for your cybersecurity clients, right? Improving the accuracy like 1% or 2% like what is the business value to your client? Like what kind of risk does that reduce? What is the cost of that risk? those, if you break it down into its components, those are some ways you can help and hold AI teams accountable to short-term ROI. And, you know, some actually fantastic questions here. Hope we can get to a couple.

So Michael here with a great question. Thanks for your question, Michael. So he said, how do you see this disrupting the digital divide? So saying with everyone having access to chat GPT and pro versions for pretty cheap, do you think it will empower the low end? Or do you see it empowering the big guys to do? dominate and drive up costs in the divide increases. That's a great question.

Tina, what's your thought of this? Is this going to, you know, going to this AI-first business world? Is that going to drive that divide or help close it? I think a little bit of both. I think what's really funny about this. I have some real examples, but I will not name any names, is that AI tools like Chat GDP and the pro versions as well can be lumped under the general category of productivity tools like Asana, right?

And in this sense, when you look at it in this way, which some organizations do, they become a commodity. They become a very low value thing that is actually really hard. Again, I have a sales background, so I'm looking at this from a sales perspective. It's actually really hard to command budget from it. And in fact, the way that you can actually influence organizations to invest in tools like that at a leadership level

is simply by pointing out the, and kind of exploiting a little bit the danger of using open source tools to the organization and the liability that that costs and the chance that your information leaks into the internet. So that's actually one of the only ways at the moment you can like get budget for stuff like that. In terms of empowering, like I think that it improves personal productivity and productivity per employee and I think that's really powerful. The way the different organizations value that ranges quite a lot. So I think it depends a little bit on the organization.

I think nimble, fast moving organizations, tech companies, series A to D types of companies, they really will understand the point here. I think maybe some more traditional larger organizations will need some time to see the value that that can bring and feel like they're falling behind competition by not making the right investments here. I'm curious, by the way, what you think about this question. I'm sure you have some observations also. Yeah.

Oh, thank you. Yeah, normally people don't turn the tables on me because I might go on a rant. I'd say I don't think necessarily that business leaders are looking at chat GPT as a productivity tool. I think originally they were. But I think as you see this push toward enterprise and then when you see, you know, which we haven't even talked about much on this show, when you see Mike. Microsoft co-pilot. I think the smart forward thinking business leaders are looking at generative AI as less of a productivity tool and more as an essential in a new way to do business.

But that's a very common, I think, you know, not not argument, but yeah, people think, okay, is this just something that's going to increase efficiency, you know, productivity? Or is this the new way that we do work in general? And I think that's probably, you know, what we're going to find out over the next couple of months, you know, as Microsoft co-pilot is starting to roll out here over the last week. And I think it's going to take a couple of months. But I mean, yeah, what do you even think about that? What do you kind of think about my take on that? We'll go back and forth here.

I think I think both are true. I think this is not an or, but it's more of an end. I totally agree with you. And again, like coming back to the sales perspective, like I think professionally, my, what I find really fun to do is figuring out, like, how do you, take something like this and pull out like the core narrative that fits like the particular, you know, organization that you're speaking to. And even if both our points are right, you have to figure out, but which one is going to resonate in this situation? And I think that's where, where things get really interesting. Yeah. Yeah. Yeah. And I think this is like moving in real time, right? I don't

think organizations, like, there's no answer or playbook on how people are thinking about this. I think it's being formed through, you know, listening to podcasts like this one, through everything you're reading every day through conversations with your colleagues. And it is not in any way concrete. It's very much water still. So that's how cool. Yeah. As soon as you feel, you know, as a business leader, maybe an entrepreneur, small, you know, business owner is, I feel as soon as you feel you, you have it. Like you haven't understood massive updates like with what happened yesterday with opening eyes developer day. That shakes up that that long term plan at times as well. So maybe we'll focus on this.

Something, a great question from Mike here. Mike, thanks for your question. Thanks for joining us. So Mike saying, Tina, please share AI benefits in enterprise that are low hanging, right? Because sometimes when you think of that long term and you see all these new tools and advancements and this and that, it's like, oh, my gosh, how are we going to implement this? But maybe for those in enterprise that are maybe looking for that shorter ROI, what are maybe some tools, tips, or processes that can address more of that low-hanging fruit that you

can really start to measure? For sure. And again, like I'm not saying this is the answer. This is just an example that comes to mind. And in a year from now, I might look back and be like, that was a terrible answer. But what I have for you right now is that I think bringing in something as simple as a generative AI co-pilot into your organization today is pretty digestible. It's not super risky. And it also do risks the reality that your employees are using generated by tools, whether or not they are honest about it in the wilds anyways. And I'm not, I think because it's kind of like a like most people are like kind of able to get their head around generated by I may have tried it themselves. It's digestible enough that it's a good sandbox to give that first pass of how are you going to get it through the door. So it's a good like maybe target practice. If you can maybe look at it in this way on how will your legal team look at this?

How will your security team look at this? How will your employees accept this? Like I think the other thing that I don't see acknowledged explicitly enough is that people don't trust AI at all. It causes mass anxiety. There is big feelings about it. And I think it's important to acknowledge that and understand why. Is it because people are scared to spend it take their jobs? Are they, they just don't get it and they're suspicious of engaging with it because it's like the end is nigh. There's a lot of big feelings about it. I don't know what it is for each individual. But I think it's important to acknowledge how your employees feel about it

because you might make this huge investment and see like the reason it's implemented, it got approval, you got budget, all of it looks good. It's been rolled out. through the entire infrastructure of your organization, and like no one uses it. They completely just refuse to engage with it. Like those are things you can't really predict per organization. And I think like to summarize, like bringing in a pretty like simple generative AI co-pilot that's built on your internal systems and seeing what happens is a good low-hanging, safe-ish way to test what it might look like for your organization and where the gaps are for

for your group. Yeah. I think there's going to be a lot of co-piloting, right? whether companies after using Microsoft copilot or bringing, you know, someone on in a role that can just help them from top to bottom is so important to transition to this, this AI first world, right? Because if you just throw this responsibility onto someone that's probably already overwhelmed, it may not, it may not turn out very well.

So, so, so Tina, we've talked about a lot in today's show so far. So everything from approval and budgeting for generative AI to the unsetable. sexy work of implementing it, you know, measuring the long term for short term ROI. But maybe if there's one, you know, as we wrap up today's show, maybe if there's one takeaway that you really want people to be able to, you know, take that and to be able to use it and to help them really transition into this new AI first business world. What is that kind of one major takeaway that you want people to have? Yeah, I think as an individual in regards to your career, like be curious and just try stuff, like get the free version, time box 30 minutes, and just try it.

Because even if it's scary for you or you're suspicious of it, just having more of a playful mindset in a way that's maybe not at work, but something at home like chat GDP, is worth the investment because these tools are not going to go anywhere anytime soon. And if you are a business leader, maybe I would say like there needs to be a little bit more conversation between technical teams and leadership about what it, what's needed from bottom up and top down to, you know, if like bottom up your engineering team, for example, is upset with you that you're like not understanding the need for like this amazing algorithm that they built, like, maybe having an honest conversation about like, what is the executive point of view and what is

the trust gap that's like blocking the final like headcount approval that they need from you? And in terms of the other way, like, you know, what do the executive team need to be aware of to make the right investments to have a long term ROI from AI, like, you know, sitting down with your technical team and being like, you know, let's get real. Like how many months do you need to get our data cleaned up? Like how many months of data collection are we missing to be able to run an algorithm with any value? I think those are some conversations I see only starting to take place very slowly. But I think they're the hygiene that might be missing to make any real transition. Well, I think whatever the case, the transition is coming fast, I think, right? Slow,

slow but fast. I love kind of that we've been able to talk about that multiple times. But Tina, thank you. Thank you so much for joining the Everyday AI show. Really appreciate your time and your insights. Thank you for coming on. Thanks for having me, Jordan. It was great to connect with you. All right. And hey, as a reminder, there's always more in the newsletter. We're going to break down a lot more on today's conversation. You can check a little bit more of Tina's work as well. So make sure you go to Your EverydayaI.com. Sign it for that free daily newsletter.

And we hope that you can join us back again tomorrow and every day for more everyday AI. Thanks, y'all. Thank you. Bye-bye. Meet Firefly AI Assistant. Now live in Adobe Firefly, the Allman One Creative AI Studio. Just describe what you want to create in your own words and the assistant handles the rest, orchestrating multi-step workflows across Adobe Creative Cloud apps, including Photoshop, Premiere Express,

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