Ep 126: Real Business Use Cases for AI

October 19, 2023


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Artificial Intelligence (AI) is no longer just a buzzword for tech enthusiasts; it has become a transformative force across industries, including finance, marketing, sales, and HR. Today, business owners and decision-makers need to be well-versed in AI's practical applications to leverage its potential for enhancing operations, streamlining processes, and driving growth. In this article, we delve into real business use cases for AI, exploring how it can deliver tangible benefits and sharing insights from industry experts.

Data Analysis - Unleashing Hidden Insights

One of AI's most powerful tools is data analysis. Imagine being able to extract actionable insights from vast volumes of financial reports, marketing data, or sales analytics. With AI-powered solutions like Chatuch PT's advanced data analysis module, businesses can now unlock crucial information that was previously difficult to obtain. By processing diverse data formats, such as PDFs, CSVs, and Excel files, AI tools analyze the data, providing businesses with valuable and timely insights previously hidden in the depths of spreadsheets.

Enhancing Marketing Efficiency

In marketing, data is often scattered across multiple platforms like Facebook, Google, LinkedIn, and various automation tools. Synchronizing and integrating this data can be highly time-consuming. However, by leveraging automation tools like Zapier or Maker, businesses can seamlessly combine data sources, creating a unified view of their marketing efforts. AI-driven solutions, such as ChatGPT's data analysis module, can then reveal powerful marketing insights, enabling businesses to optimize campaigns, identify target audiences, and achieve higher ROI.

Data Security and Best Practices

While the benefits of AI are undeniable, data security remains paramount. Business owners should exercise caution when sharing sensitive, confidential, or proprietary information with AI models. Implementing in-house, open-source models like llama 2 from Facebook Meta can provide an alternative solution that ensures data security while reaping the benefits of AI. However, it is crucial to weigh the additional IT work and efforts required for this approach.

The Role of Committee in AI Transformation

The wide range of AI tools and capabilities can be overwhelming for business leaders. However, establishing a committee comprised of individuals from different departments and levels—preferably those with a penchant for tinkering with AI—can help define the framework and boundaries of AI implementation within the company. The committee's ongoing role includes exploring new tools, experimenting with use cases, and providing education to the organization, bridging the gap between AI advancements and business needs.


With continuous advancements in AI and the integration of AI capabilities by major players, harnessing its power is critical for businesses looking to remain competitive in today's rapidly evolving landscape. By leveraging AI tools for data analysis, enhancing marketing efficiency, and establishing committees to govern AI implementation, business owners and decision-makers can unlock unprecedented potential for growth, efficiency, and innovation. Through careful consideration of data security, consulting industry experts, and driving immediate results with low risk, AI can transform businesses and pave the way for a brighter future.

Topics Covered in This Episode

1. Integrating AI into business organizations
2. Use cases of AI in data analysis
3. Role of the committee in exploring and implementing AI
4. Content creation and repurposing with AI tools
5. Consulting with experts and utilizing their content

Podcast Transcript

Jordan Wilson [00:00:17]:

One of the most common things that I think I hear about generative AI in the workplace is everyone's saying, alright, but how? You know, people hear, oh, you can, you know, use ChatGPT for this or you can use DALL E for this or, you know, all of these large language models, but how do they actually apply to my business. How can I actually put them to use and help grow my company? Well, if that's you, then today's show is for you. So welcome. My name is Jordan Wilson. I'm the host of Everyday AI. This is your daily livestream, podcast, and free daily newsletter, Helping everyday people like me and you make sense of what's going on in the world of AI, and not just make sense of it, but practical steps on how we can actually Use it. Alright. So if you are joining us from the podcast, thank you.

Jordan Wilson [00:01:06]:

Make sure to check out the show notes as always. We always leave a lot of great information in there. A link you can actually come back and join the conversation and, you you know, talk to myself and the guest, for today as well as sign up for the free daily newsletter. You gotta make sure you You sign up for the free daily newsletter. We always break down the conversation in insanely detailed way in on how you can actually make sense of everything that's going on. But, before we get into that, let's take a minute to talk about what's going on in the world of AI news. Alright. Let's get to it.

Daily AI news

Jordan Wilson [00:01:37]:

So, MidJourney's 1st mobile app is out, kind of. So the popular AI image generator is moving to apps now as well. So, MidJourney, I think by far, they are the leader in the AI image generation space, And they built a thriving community on Discord, but now they've expanded, their reach with its own mobile app. So in the in the mobile app, which is called Niji, people are a little confused because it's a normal app that is a little more, it's it's a normal style inside MidJourney that's normally a little more anime, but, you can actually download this app. It's in conjunction with another studio, and you can go in into the general, standard settings and switch, to v five. So a lot of people are confused, and they're like, oh, MidJourney has an app. That's amazing. What are these generations that are coming out? So, it's in there.

Jordan Wilson [00:02:24]:

You just gotta dig in the settings. Alright. Next piece of news. DeepMind is fighting climate change. So the new report shows that DeepMind, Google's AI arm is fighting climate change and, detailing some specific ways that we really didn't know about before. So, really, they're using AI in 3 major ways, to understand what's happening with climate change, to optimize current systems and infrastructure, and also accelerating breakthrough sciences. But, you know, there's obviously challenges with this, including access to data and collaboration with experts. So if you wanna know more about that, we're gonna have more in the newsletter as always.

Jordan Wilson [00:03:01]:

Last news story of the day. A news, a new study shows that the world's biggest AI models aren't very transparent. So a study from Stanford's human centered artificial intelligence, committee shows that, That these new AI models or or sorry. Not the new AI models, but the AI models that we all use every day, kind of ranked them. And it ranked the 10 most popular AI models Based on their transparency and guess what? All of them received pretty low marks. But kind of the Most transparent of the not very transparent large language models included, NADA's, llama 2, Bloomzy and OpenAI's GPT 4, those were the highest 3 scoring models, but none of them received particularly high marks. Again, that's not all the AI news. That's just the 3 that we picked.

About Isar and Multiplai

Jordan Wilson [00:03:51]:

So every day, we have more on those stories and a lot more. So, again, make sure you go to your everyday AI .com. Sign up for the free daily newsletter to learn more about those. But, you probably didn't come here to to talk into, you know, about the AI news. Maybe you did, but you probably wanna know Some real business use cases for AI. So, I'm excited, to have on our show, and please help me welcome To the stage, we have, Isar Matis, the CEO of Multiply. Isar, thank you for joining us.

Isar Meitis [00:04:22]:

Been waiting for this for a while, so I'm excited to be here.

Jordan Wilson [00:04:25]:

Oh, absolutely. Absolutely. Iso, first, maybe tell us just a little bit about, you know, what multiply is and and what you do.

Isar Meitis [00:04:35]:

So in in my background, I was a tech startup kind of guy. I was a CEO of several different tech startups. Some did better than others. 1 got to a $100,000,000 in in size and got sold. Others crashed and burned. So I've I've seen the good, the bad, and the ugly of running businesses. And, in this past year, I've been really obsessed with AI and its impact on business, and really what Multiplies goal is is to educate business people on how to leverage AI in the most impactful way because it's the most Transformative cycle of technology that we've ever seen, and people, most business people are very far behind where they need to be. And so I really, my goal is to to help business people whether for themselves, for their career, as well as People leadership to transform their businesses in order to be more successful with AI.

Jordan Wilson [00:05:26]:

Yeah. And and just just as a reminder for those joining us live, Cecilia saying thankful. Thoughtful Thursday, Jordan, and the Everyday AI family can't wait for your insights. Yeah. What what do you wanna know from Isar? So he just told you some of his background. He's he's helping companies leverage AI and has used AI in in big ways. So what do you wanna know? You know? That's, I like to say that this is the the realest show in AI. We go live, so get your questions in, so we can, we can pick Isar's brain.

How to implement AI in a business

Jordan Wilson [00:05:53]:

But, you you know, one thing that I I wanna know, Esar, is, it's you know, I kinda started the show with this is, you you know, people, I think always hear about all of these, you know, new developments and all of these tools. But it's it's actually, I think, Can be a struggle for some companies to actually start using generative AI, on a day to day basis. How can companies actually do that and and get these great, tools and techniques, you know, actually In their departments, in their company, how can that happen?

Isar Meitis [00:06:26]:

So the the number one thing, and it's it's true now, but it's gonna be true moving forward, is continuous education and exploration. And what that means is if you think about it and, you know, you and I do this day to day, like we I have my own podcast called Leveraging AI. I consult to businesses, so I sit with them and help with them. I teach courses. I read news, I see the news, I follow stuff, I experiment. That's what you and I do for a living. People who run businesses, well, they run their business As much as they wanna be interested in in immersed in the AI stuff, they still have a business to run. And whether they're at the top of the pyramid or somewhere within the pyramid, They have other stuff they need to do in their day, meaning they don't have 3, 4, 5, 6 hours a day to check what's going on, to download new tools, to experiment with them.

Isar Meitis [00:07:16]:

They just don't have that. So on the other hand, this thing is moving so so fast that every week, There are new capabilities and new tools either that you don't know of that could have helped you or even features within systems you're using today. So if we look at All the big players, whether it's Microsoft 365, Google with G Suite, Salesforce, HubSpot, Etcetera. All of these are bringing AI features into the platforms you're already using. So the question becomes, as a business leader, How do you keep up with all of this as a business, not for individuals within the company? And the way to do this is to put together a committee, And the committee needs to be built or assembled from people from different departments in different levels, Preferably somewhat geeks like me that enjoy actually tinkering with these kind of things. And the committee's role is, first and foremost, To define the framework, the guardrails, the box within people, within the business are allowed to operate when it comes to AI. Because it's very, very easy to do things with AI that are way beyond what a company wants to accept, whether it's sharing data that should be shared through platforms that ad Use your data or sharing your customers' data through platforms that use your use the data, or just Things that do not align well with company's core values because I'll I'll give an example. Let's say you're a salesperson, most salespeople gets Compensated based on results.

Isar Meitis [00:08:51]:

Well, you can do things today that are deep into the gray area with AI, and it can help you get more sales, Which means you'll get a higher compensation. Is that something as a company you're willing to accept? Probably not. So defining The guardrails defining the box within everybody in the company is allowed and even encouraged to ad Use AI is the first step of the committee, but the ongoing role of the committee is to really explore, experiment, Provide education to everybody else in the company who are like, okay, somebody brought to us, and it could be anybody in the company, this idea for this tool, for this process, for this use case. We've tested it. Here's what we found. Here's how we are going to use this and implement this within and Business processes. So the new the old process was this, the new process with AI is that, and run education and training sessions to everybody in the company, a, on the ongoing pro progress of AI and new ethical issues and so on, and b, on actual use cases that are being implemented, Like I said, either through third party tools that you're not currently using or through the platforms that you're using today that just have new features.

Roadblocks for companies adopting AI

Jordan Wilson [00:10:06]:

Yeah. Isar, what would you say is maybe one of the main reasons? And even in my personal experience, you know, I've I've talked to Hundreds of, you you know, professionals who are trying to get AI into their companies, but maybe can't. What would you say are some of the reasons why, You know, companies haven't done this so far, why they haven't, you you know, created these committees and set up these, you know, guardrails and talked about these ethical guidelines. Is it an education piece. Is it a a timepiece? What would you say is maybe one of the main reasons or the main roadblocks, for companies that they haven't been able to do this yet?

Isar Meitis [00:10:38]:

So I think it's a combination of several different things. You know, the first thing is change. Change is hard. Any change is hard. And the bigger the organization is, the bigger is to drive change. And I've I've you know, the largest company I worked for Was not huge, but it was, you know, 10,000 people, €7,000,000,000, so a decent sized company, And it's impossible to change in these organizations. Now if you're a company of 5 people, it's a lot easier to change and the chances you'll be able to and Enjoy AI very, very quickly are significantly higher. So I think driving change to a large organization is problem number 1.

Isar Meitis [00:11:18]:

Problem number 2 is I think despite everything you hear and everything in the news and the stuff you and I are involved in daily, It's not common yet. So you and I live in the AI world for a year now, Tinkering with it daily, working with people daily, listening to the news, and we assume, and a lot of people are like that, assume that everybody's already ahead and everybody's doing stuff. The reality is I work with multiple companies. Most of the people are either clueless or just scratching the surface of what these things can do so they don't fully understand the benefits and the risks on the other side that exist If you either implement or don't implement this fast in the right way.

Jordan Wilson [00:12:06]:

Sure. You you know, you kind of talked about how Anyone, like, in theory, can can be on this committee or in this community of people driving Gen AI forward within an organization. But Should the should the onus or should the responsibility fall on, you know, a certain group or a certain department? Like, as an example, is it ultimately the CEO that should be pushing in or someone from the c suite. Is it HR? You know, that that that should be driving this initiative saying, hey. This this is something that falls under a process and procedure. Should it be marketing? Right? Like like, is there maybe, you know, 1 person or a a a department out there that should, in theory, take The lead on this because I feel sometimes if it's like, oh, let's all get this and, you know, go together, it might not move anywhere.

Isar Meitis [00:12:50]:

So great question. I think it's a combination of of top down and grassroots, and I'll explain what I mean. I think the leadership team CEO and the c suite have to be involved. And at least 1 of them must be on the committee. Why? Because it, a, shows that there's Interest in the leadership to move this thing, and b, you want the community to be able to make decisions and make changes happen without having to go through 3 cycles of approval after they decided on something. So you want somebody, CEO, or somebody else in the c suite to drive this. As far as the different departments that you mentioned, You want people from each department. And the reason is there's different needs, different limitations, different issues With every department when it from every department when it comes to implementing AI.

Isar Meitis [00:13:40]:

They will have different benefits. They will have different needs. They have different issues that AI can solve. So you want 1 person from each department in the committee helping to define what the company needs, defining priorities between different departments, and Yeah. So oh, sorry. But I mentioned the grassroots part of it. If you are in any role in the business and you're passionate about AI and you're reading about and playing with this, and you see use cases in your business and nobody's actually top down doing anything, Raise your voice. Come up with an actual business case.

Isar Meitis [00:14:15]:

Don't come up with a cool idea. Come up with a business case. Here's in my department. We can do 1, 2, and 3, which will achieve a, b, and c, and I wanna experiment with this. Take it to your boss. Take it to the Whatever leadership committee there is and say, hey. Here's what's happening in the world. Here's what I can see that we can do right now.

Isar Meitis [00:14:36]:

I wanna test it. Here's what I need from resources perspective. Here's what I think the outcome can be, an actual business case. And you could become the leader of AI in your business overnight by just taking initiative doing that. So I think it works both ways, And it works the best when you have both things, when you have people on the bottom passionate about this, as well as people on top are saying, yes. We understand the Livelihood of our business in the next few years depends on us doing this change.

Using AI for data analysis

Jordan Wilson [00:15:03]:

Yeah. Yeah. It's that's so true. And I think, you know, I think we sometimes don't wanna say that part out loud that, You know, if if we as as business leaders, as, you know, small small business CEOs, you know, marketers, whatever, If we're not using this technology, we are putting the bottom line at risk, and I I I don't think people fully realize that. But But, actually, Isar, let's just go ahead and fast forward. So let's say we've got a committee together. Things are good to go. Maybe what's one of the first, You know, kind of like real business use cases for once you kinda get the green light for Gen AI in an organization.

Isar Meitis [00:15:41]:

So I think it very much depends on the organization. Right? At the end of the day, you wanna go through a process, and that's something I work with all the companies that I work for is what are the low hanging fruits? In How you can get immediate results without too much effort, without too much risk, and to to prove the point. Right? And one of the things that are immediate Or the 2 things that are usually get the most amount of results very, very quickly. 1 is things that require, data analysis And preferably that are repetitive. And we do these things all the time in almost every department in the business, whether you're in finance or in marketing or in sales. So let's let's take example in these 3, right, or or or in HR. Right? So if you're in finance, well, you look at financial reports and And you try to analyze the results. Well, today, you can take that data and push it to even a tool in ChatchiPT, so don't go to anything fancy.

Isar Meitis [00:16:32]:

And Chatuch PT today has a module called advanced data analysis, and it can you can upload any kind of data whether it's PDF formats or CSVs or Excel files and so on, and it knows how to read them. So you can upload 12, trailing months of financial data, and it can give you insights that you yourself cannot find. And it helps you do analysis that normal tools cannot do because it's just like having a business intelligence team in your back pocket for $20 a month. So that's for, you know, finance. If you're in marketing, well, all your marketing data. And one of the huge problems the marketers have is that the data is scattered across Fifteen different things. Right? So you have data in Facebook for your Facebook ads and in Google for your Google ads, and in LinkedIn for the stuff you do on LinkedIn, and And in your marketing email, automation tool, whatever you're using, every one of those is a silo that has some of the data, and it's very, very hard to connect them together. Well, today, you can build automations very, very easily using automation tools like either Zapier or Maker or NA ten, one of those tools that Push this data into a tool that will then send it to, let's say, again, the same tool I just mentioned, like ChatGPT advanced data analysis, and And can combine all these things and give you insights that were on the verge of impossible before.

Isar Meitis [00:17:55]:

So literally in every department, You have historical data proposals that you've written. So take the last 50 proposals that you've written, load them to ChatChippity and say, okay. These won, these lost. Can you try to help me analyze what's the difference between the winning proposals and the losing proposals? It's really easy to do, and it's stuff that we didn't do before because it's hugely time consuming. And so you need to have 3 people spending 4 months to go through what I just said, taking proposals of the last 3 years and trying to compare them. We're now in Chatuchipiti. You can do it in, I don't know, 20 minutes. And so with 1 person.

Isar Meitis [00:18:29]:

So the ability to analyze data to get real insights That can drive more business or more efficiency within the business is stuff we just never had

Jordan Wilson [00:18:40]:

before. Yeah. And, you know, I do wanna follow-up on that, but but first, just as a reminder, you know, Josh saying, you know, good morning. I had no idea ISAR gonna be on. This is great. Yeah. This is absolutely great. We do this every day.

Jordan Wilson [00:18:51]:

We bring on, guest. Josh was on the show earlier this week. You know, so get your questions in if if if you want, if you you wanna know some real business use cases for AI, let's get those questions in and have Isar tackle them head on.

Data security guidelines for AI

But 1 question that I have, Isar, and this is something, you know, We just, you you just mentioned, you know, ChatGPT's, advanced data and, analytics, which used to be called code interpreter. You know, they're always changing the name out there, but, you know, something, I I I see is a very common misconception with people as they say, oh, well, You know, I can't upload any data inside of this because, you know, it's it's my company's, you you know, financial information. And people sometimes think that, You know, by uploading this, you're essentially publishing it, on the Internet, which isn't exactly the case. What is your, you know, kind of best practice guidelines For how people can handle their data, especially if they're not, you you know, because, you know, you have the enterprise versions of these coming out, the ChatGPT enterprise, The the Bing chat enterprise. But maybe for those that are just using the standard, you know, commercial $20 a month ChatGPT plus, What advice or best practice can you give them on, data security?

Isar Meitis [00:20:01]:

Great question. Number 1, and Continuously have somebody review their terms and conditions because they keep on changing it. So whatever I tell you now might not be true tomorrow. So that's number 1. Number 2, their API. So if you use any of the API tools, presumably, again, assuming you believe them, Does not use the data to train anything. It just used to provide responses. 3, specifically advanced data analysis forgets the data you upload to it at the end of the session.

Isar Meitis [00:20:31]:

So it's good and bad. It's good because there's no data security issues because it evaporates literally as soon as the session is over. It's bad because if you leave for a meeting that you have and you didn't finish doing what you wanted to finish, you have to start all over again because it forgets the data that you uploaded originally. So That being said, I would still be cautious with uploading really sensitive data. So What I mean by really sensitive data, if you're in any regulated industry, yeah, big no no. For those, I say, Get a local or a cloud version of an open source model like llama 2 from, ad Facebook meta and and run on that, and then you don't have to worry about is ChatGPT because you're literally hosting it. You know which data is coming in, which data is coming out. That requires some IT work, that requires some additional efforts.

Isar Meitis [00:21:23]:

But for stuff even like financial data of a company, If if it expires at the end of the session, how bad can it be? Or even even, let's go to the worst case scenario. Let's say they are Training on this data. That doesn't mean that somebody can go and run a search like in Google and say, oh, I wanna see companies a, b, c's. The it's not the way it works. So even if you load your company's financial information, which is like a big secret, right, or your list of clients, It's not something that somebody can search. Mhmm. It just becomes a part of a huge database of all the data on the freaking Internet As another point of reference for that model to work. So my point of view of this is anything that's not crazy sensitive, Like the secret sauce that your client is using in order to drive all the revenue that you're driving.

Isar Meitis [00:22:15]:

If you're using the API or if you're using Uploading files to advanced data analysis, you should be fine Mhmm. And you're taking a reasonable risk, especially considering the Benefits that you're getting on the other end.

Jordan Wilson [00:22:29]:

Oh, absolutely. And, you know, even, Kevin, thank you for the comment here. So saying, from a data analytics standpoint, I think the most significant holdback has been the fear of publishing private data to OpenAI, hasn't it? Yes. But, you know, kind of like, Isar just said, you know, if if If he uploads, you know, his, you know, his, you know, his, books essentially, you know, for multiply and and puts in all of their financial information. If I then go and say, you know, what is multiplies, you know, top top line revenue? It that that that's not how it works. Right? Yeah. There is no publishing. It is just to train the models, but, yeah, you definitely have to, you know, be, be smart about what you do upload and and not because, yeah, anything sensitive, Confidential, proprietary, probably not the best thing, but that's also why you need to have kind of like what Isar said, a community, or a committee to talk about what information should be uploaded to large language models or not.

Using Gen AI for content creation

Jordan Wilson [00:23:25]:

You know, and I think, you know, kind of once you can bring it up local, I think that helps as well. Maybe, Isar, let's let's, kind of steer away from that because, I think what so many people, the easiest, maybe the lowest hanging fruit for so many companies and leveraging Gen AI is creating Content. Right? So for your your marketing, your advertising, your comms, whatever it is, what are some what are some ways, and Just very practical ways that have a great return on time invested that people can use Gen AI, in those ways.

Isar Meitis [00:24:00]:

Wow. So I'll start with the first thing. So a lot of people again fall into this trap of like, oh, let's create content because it's really good at creating and which is true. I would say step 1, it's incredible in ideation. So if you need ideas on what content to create in order to, attract the right audience. I would start there. Help it. Have it help you.

Isar Meitis [00:24:22]:

Have Gen AI tools help you Identify the exact pain points of your audience. And then from there, start defining which content pieces in what formats and and so on. So that would be my number one thing. Like, it's incredible in ideation. The second thing is, okay, now that you know what content you wanna create, ad The best way to create a lot of content is what we're doing right now, right, is recording video. Now not a it's not for everyone, but the benefit of recording video is that now you can repurpose it in any other kind of content. And the beauty of and that was true before, but now with Gen AI, you can take this video and transcribe it so you have a piece of content that you can put, maybe not very user friendly, but it still provides you some SEO value if you put it on the back end of something. You can have all these tools and some tools are built exactly for that, like Jasper and like Writer and all these tools that know how to take this transcription And turn it into an actual blog post.

Isar Meitis [00:25:22]:

So now you can have a blog post. You can take and use ChatcipT. I use, ChatcipT and Claude to To create, the initial draft of my LinkedIn posts for Everything that I do. So I take the recording of my podcast and I put it through cloud 2 with preexisting, prompts that I've created, and it gives me ideas down to bullet point level of what I wanna publish In the already in the format. So all I have to go in is go and kind of make it a little more my voice and my own, and I'm ready to publish it. So I can have from this 1 podcast that I recorded, 20 pieces of content investing 10 minutes of my time in some editing of stuff that I don't like. It's insane. It's something we never had before.

Isar Meitis [00:26:12]:

So this is one example of content repurposing. And think about all the content your business generates on other stuff and how you can repurpose it Just using these AI tools, using ChachipT or Claude, like stuff that is free. Mhmm. You don't have to pay for anything fancy. And even the fancy stuff, you know, it's another $20 a month. It's not, a crazy investment. So this is number 1 is how can you repurpose content that you're already creating using these AI tools, using, and I mentioned it in a in in a word, but Having your prompt library where you know it's already working, now it's like, oh, this I've perfected how to take this long form thing and intern it into posts, use it again and again and again. So now, again, you can build automations around this thing because using the same prompt every time.

Isar Meitis [00:26:54]:

So this is One thing is repurposing. The other thing that I find extremely useful is creating images for everything that I need. So whether it's post on social media, presentations. So I do a lot of, and Speaking, like public speaking on different, either in companies that invite me to speak for the company or on stages and conferences and so on. So I create presentations for those. So you need images. I stopped using the stock photo images stuff. I literally create everything and now with DALL E 2, DALL E 3.

Isar Meitis [00:27:24]:

And I'll say something about DALL E that, you know, it's brand new, like it came out last week and, It's incredible. I'm absolutely loving it. And the reason I'm absolutely loving it is that it's a chat ad Platform. So if I have to compare Midjourney and DALL E, Midjourney still gives me better quality images when it comes to photo realistic Stuff. Like if I want something to look like an image that I took with my camera, I go to MidJourney.

Jordan Wilson [00:27:53]:


Isar Meitis [00:27:53]:

But if I want graphics for anything that I'm doing, I find that right now, DALL E gives me better results faster because I explain to it in simple terms what I'm trying to do. And I'll give you an example that I'm doing right now. I'm going in into a conference on Monday, and I'm finalizing the thing, and the last thing I do is create the graphics for the presentation. And I literally share with it, this is the kind of Conference I'm going to be. This is the audience. These are the things I'm gonna talk about. On slide 1, I'm talking about this thing. Give me 3 ideas ad- For what should be the graphics on the slide, and it comes up with amazing ideas.

Isar Meitis [00:28:30]:

And they're like, okay, I really like the second one. Can you create that image? And it creates an image. Yeah. You're like, oh, I like it, but I would like to change this thing in it. And then you continue the conversation, and in Either the 1st, the 2nd, or the 3rd iteration, you'll get something that is incredible, that is tailored to a specific slide For a specific audience, and this true again, I now talk about presentation, but you can use this for a sales presentation. You can use this for your and Next blog post. You can use this in your next social media post. You can use, like, literally anything on your website.

Isar Meitis [00:29:04]:

Any Content you need from a graphics perspective, it's an incredible process. And again, the reason I love it is because it's iterative and because it really understands, Just like Chachipity does, what you're trying to achieve. So in Midjourney, you have to be really good at prompting Midjourney to get what you want because With very limited words, you have to explain your idea. In DALL E, you can go 5 pages explaining your idea in order to get exactly what you want.

Ideation with LLMs

Jordan Wilson [00:29:30]:

Yeah. It's and, you you know, one thing speaking of DALL E, one thing that I like and that it does, I think, very, very well better than mid journey is when you do give it a prompt, you can give it something very basic. Intuitive 4 words, and it'll give you 4 variations, and it'll expand on that prompt. It'll, you know, turn your simple, and Straightforward prompt into something that is is very intricate, actually. You know, Isar, I I do wanna unpack something there because right Right in that one answer right there, we we we just got a whole, like, history lesson of of AI content creation. Right? Like, dropped a couple names of tools. We talked about ideation, content creation, preparing for presentations, all of those things, but I wanna actually start at the beginning, because, you know, Mike Mike here had a a a question Like, hey. What method is used to create that moment? And I think for so many people, that moment can be ideation, and it's something that we skip over So frequently.

Jordan Wilson [00:30:22]:

You you know, I even go back to think. You know, I used to be all the time, I would work on large partnerships and activations with Nike and Jordan Brand. And we would have, You know, 10, 12, 15 people in a room for hours talking and coming up with ideas and strategizing and ideating. Is that maybe, the ideation aspect of large language models in Gen AI? Is that being overlooked just because the thing is, you know, so tangible. Right? It's like, oh, I need 10 blog posts and 10 this. It's tangible, but maybe we're not Measuring the amount of time that we're, you know, brainstorming, ideating, strategizing. Like, what's your thought? Is that the moment here?

Isar Meitis [00:31:04]:

It's a big Like, it's, I think the ability to ask the brightest people on the planet Any question you want based on content that they have already shared with the world, either on Twitter or in books that they've written. So you can build, and that's something, again, I I share on on with, like, with people that I work with. You can build A committee, an advisory board based on specific people that you follow, that you think are the most brilliant on a specific topic or based on a specific book and say, based on this book or based on this person or based on these 5 people with these 5 books, I would like to create a new x. Marketing plan, HR plan, training plan, like whatever whatever thing that you're trying to do, You can consult not with AI. You can consult with specific people based on and Specific content that they have shared that you think is the way you want to go. This think about it. You can pick The 5 leading people in the world on a topic that have written 20 books each, that are best selling, that and on stages that probably charge $50,000 an hour, and you can ask them questions about the plan you're trying to put together. That's insane.

Isar Meitis [00:32:28]:

That's something that never and is it as good as talking to the person? I don't know, but it's way better than just me talking to myself. And so bouncing ideas against or through the lens of other people because they're well known and they've shared a lot of their stuff is an incredible capability, so it's all about figuring out not how am I gonna use Chatipity, How am I gonna use person x that I've written books 1, 2, and 3 that I really, really like, and I wanna know what that person, through the content of these books, would give me as advice for the thing that I'm trying to tackle. And you can do this with several different people. And now you have a committee. And now that each and every one of those quote, unquote people gives you an answer, you can combine it all together and say, okay. Now you are a CEO of a company. These are the people that are your chief of marketing, chief of this, chief of that, which are really known people. This is what they said.

Isar Meitis [00:33:26]:

In What do you think is the best way to combine all of these together? Like, the combination of things you can do with it in order to get incredible insights for things you're trying to do are unparalleled with anything we ever had before, and it's free. So it's like it's insane. It's really, really amazing.

Isar's advice to start using AI

Jordan Wilson [00:33:45]:

Isar, we've gone over so much. We've gone over, you know, how to actually get Gen AI up and going with a committee and Or community in your company. We've talked a little bit on the time savings of of data analysis and summarizing, and then we talked about how you can use AI to, you know, ideate and and to create content. But maybe if if if someone is a little more excited than they were before, you know, listening to this show, what is the 1 step kind of kind of as we wrap? What's that 1 step that you would recommend people take to actually get, that real business use case going for, AI in their company.

Isar Meitis [00:34:24]:

Wow. Overcome fear. Like, just try stuff. Like, take ChatGPT, it's free, or pay the freaking $20, it's worth every cent, And try stuff and follow people like you, right, or like me. Like, listen to podcasts and get ideas in From either blogs that people share or newsletters that people share or podcasts or live shows, get ideas and say, oh, this could work for me and just try. Just try stuff out because people are like, oh, I I I don't know what's gonna happen. Like, I'm gonna use like, I'm gonna take this data and put it out there. I'm like, What's the worst that can happen? So, again, start with data that is not sensitive, that you feel that is like nothing.

Isar Meitis [00:35:06]:

Even if it goes on the front Page of CNN tomorrow, nothing bad will happen, and and just try it out and see because the results that you'll get, if you'll follow A process that somebody has already charted, and, again, it's it's out there. Like, people like you and me share that stuff. I don't hide anything that I do. I I immediately when I Learn something new. I put it out there. And there's thousands of people like you and me.

Jordan Wilson [00:35:30]:


Isar Meitis [00:35:30]:

And like, oh, this could work for me. Just try it out. That will be my number one tip.

Jordan Wilson [00:35:34]:

I love that. Just try it. So many people on the fence. You get analysis paralysis. You have, you know, 500 prompts saved, you know, 300 new tools. Just Take Isar's advice. Go out there and try it. Isar, thank you again so much for sharing your insights.

Jordan Wilson [00:35:49]:

So many good practical steps For people looking to get AI in their business, thank you for joining the Everyday AI Show.

Isar Meitis [00:35:57]:

Thank you. This was awesome. I really enjoyed myself.

Jordan Wilson [00:36:00]:

Alright. And, hey, just as a reminder, there was a lot going on there, like so much good information. If you miss it all, Don't worry. We're gonna break it all down for you. So go to your everyday ai.com. Sign up for that free daily newsletter, and we'll have So much of what Izar was talking about and a lot more. So thank you for joining us, and we hope to see you back for another episode soon. Thanks.

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