Everyday AI Podcast – An AI and ChatGPT Podcast - EP 189: The One Biggest ROI of GenAI

Episode Date: January 19, 2024

How do you win back your time with generative AI? So many people ask us this question and we thought we'd answer it. We've figured out the biggest ROI of GenAI and we're breaking it down for you!Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode pageJoin the discussion: Ask Jordan questions on AIUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: [e-mail] with Jordan on LinkedInTimestamps:01:50 Daily AI news05:00 The biggest ROI for GenAI09:07 Generative AI revolutionizes knowledge work in business.13:48 Internet revolutionized knowledge sharing; Generative AI creates.20:05 Internet usability declining due to excessive ads. Lawsuits.21:04 Publishers losing money as large language models index.27:06 YouTube videos are better for learning skills.30:48 Knowledge workers benefit from generative AI usage.32:04 Use AI to query, read, respond, analyze emails.35:21 Categorize manual work to find time spent.Topics Covered in This Episode:1. Leveraging Generative AI to Win Back Time2. Impact of generative AI on knowledge work in business3. Practical Applications of Generative AI4. Challenges of Information Overload and Time Management5. Impact of LLMs and Internet UsabilityKeywords:Generative AI, Rabbit, Perplexity, Meta, Artificial General Intelligence, AGI, World Health Organization, ethical guidelines, healthcare, knowledge work, McKinsey study, economic potential, Internet, retrieval augmented generation, large language models, Google Bard, YouTube, productivity, GPTs, web reader plug-in, summarization, work processes, email, learning, information overload, AI skills, professional success, web researchSend 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 in 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. How do you win back your time using generative AI?

It's one of the most popular questions that people always ask us is not just how do I use this, but how do I get a good return on using generative AI? How can I get time back? That's what we want. Luckily for you, that's what we're going to be talking about today. I feel we've kind of got it solved. So we're going to be unwrapping that today and more on Everyday AI. Welcome, if you're new here.

My name's Jordan Wilson. I'm the host and Everyday AI. It's for you. It's for us. It's helping everyday people not just learn generative AI, but how we can all actually leverage it, practical guides to actually make it work for us. All right.

So if you're new here, thanks. Make sure to go to your EverydayAI.com. Sign up for the free daily newsletter. this is a podcast, it's a live stream. But to be honest, the newsletter, that's where you actually put all of this into action. It's nice to listen and to interact and to learn new things. But the newsletter gives you the guide. It lets you know exactly how it's done.

And also on our website, if you didn't know, we have a backlog now of 180 episodes. I say it is literally a free generative AI university. Whatever you want to learn, you can go on and click sales and, You know, you can listen to all of our different sales interviews or, you know, go back and read all of our different back newsletters as well. So make sure you do that. But before we get into the topic, let's first go over what's happening in the world of AI news. So Rabbit is teaming up with perplexity for its new R1 device. So Rabbit has released its pocket-sized A1 device.

You know, they announced it about a week and a half ago at CES. So the R1 and it acts as a universal controller for apps. All right. So Rabbit has just announced that they're. our one hardware will be powered by perplexity AI, one of our favorite AI tools for its large language model search with a free one-year subscription for the first 100,000 buyers, which I thought was pretty cool. So this advanced service offers file upload support, a daily quota of 300 plus queries, and the ability to switch between AI models. All right, meta. Meta is making some moves over the last

couple of hours. And now they are publicly now focusing on artificial general intelligence or AGI. So a couple of things to unpack here. We're going to go through them quick. So META is shifting its AI research team fair to sit under its product organization with a focus on building AGI. It's an important shift. Make sure to read about more on that in the newsletter. But this move is streamlining their AI research and development while also navigating the legal policy and brand landscape in the increasingly scrutinized space. So Zuckerberg is, Like I said, he's going all in on his interest in building AGI now and is openly discussing the company's efforts in acquiring talent and the computer compute power needed to reach AGI. Zuckerberg also announced in an Instagram post that meta is investing billions of dollars, billions with a B, billions of dollars in Nvidia chips for its artificial intelligence research and projects with a focus on achieving AGI.

Yeah, interesting. Go go go look at Nvidia stock, you know, later today. I'm sure it's going to react accordingly. Also, meta's focus on open sourcing their models kind of sets them apart from their other competitors who may opt for more close source approaches to AGI, such as Open A.I. All right. Next, the World Health Organization is warning medical AI could actually be dangerous for poorer nations. So the World Health Organization has issued new guidelines for the ethical use of generative AI in

health care, citing concerns over the potential dangers and inequities in lower income countries. The rise of, get it here, large multimodal models, LMMs, a little different than large language models. So kind of, it's also known as gendered of AI, but that's led to a rapid adoption in healthcare applications, which can provide clinical notes, diagnosed and treat patients, etc. But the WHO stressed the need for governments to lead efforts in regulating and overseeing the development and use of AI technologies and for civil society groups and individuals receiving health care to play a role in this process. So, you know, it's actually a pretty important, I think, a conversation to be had about how, you know, countries that have more access, you know,

to these large language models in generative AI or, you know, kind of the large multimodal models, it does give us such great benefits that we don't even know that we're reaping that other countries don't have. So I think it's an important conversation to have. All right, but the important conversation that we're having today is on how you can actually win back your time, right? That one biggest investment of, you know, the biggest ROI on Gen AI. And I do have to mention a great related episode to go back and listen to. It's in the show notes is the seven ways to use AI in your business, which I think a lot of people miss because we, you know, we released it right, you know, after New Year's.

So don't sleep on that one. Make sure you go back and listen. But let's just get to the end. I'm not going to drag y'all on. the one biggest return on investment for generative AI is winning back your time on manual knowledge work. All right. Let me say that again.

It's not a tool, right? Yeah, you accomplish this a lot of times through different tools. It's not, oh, you know, getting these 50 different programs. It is literally just winning back your time on manual knowledge work. All right. We're going to unwrap this. But I also, hey, before we do, I got to do. I got to give a shout out to everyone joining us.

So Josh joining us from Dallas. Thank you. Tara joining us, Megan and Cecilia. Michelle, love, love y'all joining. But let me know, you know, Daniel and Thomas, everyone joining or Kansas City are Woozy Rogers or Quran. Let me know, have you won back your time yet? And if so, how?

Might shout one or two out. But also, let me know if you do have any questions about how the best ways to win back your manual time. Like, what's the best way to go about that? We're going to be going through three different ways at the end. All right. And like I said, go, go listen to that, the seven ways episode, the seven ways to use AI in your business. Y'all, that was, I'm not going to lie, that was a banger. That was one of our best episodes we've ever done. All right, but let's talk a little bit more about winning back your time on knowledge work. All right. So what we first have to do is talk about knowledge work. What is it? Well, if you haven't been hearing,

it, you're going to be hearing it a lot, right? Especially, you know, we talk about even the World Economic Forum that's happening, you know, right now, I believe it's in Switzerland, right? One of the biggest things that they're talking about, you know, the world leaders and, you know, not just world leaders from a political standpoint, but also from a technology and an AI standpoint, you know, they are talking about how this year is going to be a shift toward action, right? 2023, when we are first, you know, dipping our, you know, collective business toes and all these different generative AI applications across the business spectrum. It was more about discovery.

It was more about learning. In 2024 is going to be the year of action. So you are going to hear references to manual knowledge work all the time. So manual knowledge work is essentially just the handling and processing of information. Okay. So it's the process of which we create value for a company with our expertise, comprehension skills, and critical thinking. Now, as weird as this sounds,

knowledge work is not as valuable as it used to be, right? Think, let's hit rewind here, okay? Let's think pre-internet, right? Knowledge work was at a premium at that point. Because if you knew a certain skill set that could move the lever that could push a business forward, that skill was beyond invaluable, right? Because there's, before the internet, it was extremely difficult. to obtain knowledge, all right?

Post-internet, you know, the last 25 years or so that we've all been, you know, probably a little more than 25 years. But, you know, for the most part, all businesses across the world and their workers have been using the internet for their knowledge work over the last 25 years, right? But it still requires pre-generative AI. It has still required a smart and capable human to decipher that knowledge work and to put it into action. But this is where generative AI changes things.

All right. And, you know, let's, I'm going to hit pause on that. And then I want to talk about the different areas of our work where we use not much work, right? If you've taken our free prompting course, prime prompt polish, you've probably heard me talk about this before, like what we do in business, okay? Because what we do in business, if you are at, knowledge worker. Again, that is essentially anyone that sits in front of a computer and uses the internet for the majority of your day. So we're not talking about manual labor, but if you're sitting

in front of a computer, like I think a lot of us are and you're using the internet and using your brain presumably, right? Most of our work falls under one of these five categories. So it's either in meetings, the actual time in meetings or the prep or the follow up that comes with it. Learning, that's a big one. So reading, note taking, et cetera, right? Processing information. Writing, which is emails, you know, writing and responding to emails. That's also reading, creating internal documents. Analyzing. So that could be actually analyzing that information or, you know, creating spreadsheets, charts, et cetera. Or presentations, right? So maybe sales calls, pitching something, whether internally or externally, training, you know, training people on your team.

All right. So here's the thing. These are all examples of knowledge work. All right. And this is literally what we do in business. All right. I get what you're saying, Jordan, probably like, all right, why? Why the big wind up here? What does this mean? Well, let me tell you what it means. People smarter than me have already been diving into this. So let's talk about a recent McKinsey study. So this McKinsey study will link it in the show notes for the podcast. And we'll throw it in the comments. in the LinkedIn stream. So yeah, if you're listening on the podcast, we always put a link to the LinkedIn stream. You can come back and, you know, talk to all these smart people and network with them. But this, this study from McKinsey, it was called the economic potential of generative AI, the next productivity frontier. So something I want to pull out there. So it says current, and this is a quote from the study, you ready? Current generative AI and other technologies have the potential to automate work activities that absorb 60 to 70 percent of employees' time today.

I'm going to go ahead and say something. I'm going to make a not-so bold claim. I know it's not hot tape Tuesday, but I'll just give you a bold claim. This study's wrong. It's wrong. 60 to 70% is an understatement, right? A previous version of this exact same study said 50%. And then they acknowledged in the study, oh, yep, it's actually a lot more than we thought.

And even when that came out and they said 50%, I'm like, nope, that's wrong. 60 to 70 percent, nope, that's wrong. Conservatively, generative AI. If you know how to use it and the emphasis is if, right? And that is, I think, in 2024, what is going to separate the businesses that rise versus the businesses that fall or get gobbled up because it is the year, 2024 is the year of action using generative AI. Okay.

But 60 to 70 percent, right? Generative AI and other technologies have the potential to automate work activities that absorb 60 to 70% of employees time. I think it's 75 to 80 conservatively. But y'all, are you getting this yet? Right. This is one of the reasons I frigging started a daily podcast live stream newsletter. I've seen the writing on the wall for this for years, right? That's why I started everyday AI because I think everyone needs a guide to help.

help them understand this because even if we hit, you know, hit rewind on what I was just kind of talking about, about how knowledge work has changed since the internet, right? When the internet came out, right? And when it was first started to be, you know, become widely used, you know, in business activities, I would guess that's, you know, somewhere around the mid to late 90s, right? I started, I guess, I wasn't a desk worker until, you know, you know, like 2002 or something like that. But, you know, people have been using the internet, you know, for at least, you know, eight to 10 years by that point.

But employees and companies at the advent of the internet had time, right? I've talked about this on the show all the time. You easily had whether you were employee, maybe you just didn't want to learn to use the internet or if you were a company and you were like, ah, we don't really need a website. We don't need to put our products and services up there, right? I'd say easily you had 10 years, probably more in some cases and in some industries, right? Easily.

It's not the same for generative AI because here's the difference. The internet changed how we shared intelligence. Generative AI creates intelligence. I don't care what anyone says, right? Y'all, I've talked to the leading experts. I've spent thousands, thousands of hours over the years using AI technology. It does create intelligence, right? In the same way that a knowledge worker can look at something, can read a document,

can process it, think about it critically and analytically and create something of value on the back end, right? That's what a knowledge worker does. They read or process something. And it's a three part step, right? you read or analyze or you read something. Okay. You analyze it in your head.

And then you apply something or you do something on the back end. Okay. So the internet really only changed the first part or two. It didn't do anything on the back end. It couldn't apply, you know, a strategy or write something or create something on the back end. That's why generative AI, generative AI changes things. It is not like the internet. is as far from the internet as possible, which is why, you know, I almost vomit in my mouth

when I hear other people talking about, oh, you know, look at the internet. Look at what it did. It's, no, that's not how generative AI works. It creates intelligence. I will argue with anyone on that. All right. And according to McKinsey, 60 to 70% of employees time. All right.

So here's what we're going to talk about for the rest of the show. We're going to win back time today. The biggest return on investment is winning back your time on one area, processing information. Okay. It is that three-part step that I just laid out. It is understanding it and then is applying and do something with that knowledge. 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.

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including Photoshop, Illustrator, Premiere, Lightroom Express, and more to help bring your ideas to life. You can also get started with creative skills, a growing library of pre-built workflows for common creative tasks, like batch editing photos, creating mood boards, portrait retouching, and creating social variations. Every step the assistant takes is visible, so you can refine, redirect, or take over at any time.

You stay in the driver's seat as the creative director. Adobe Firefly AI assistant now in public beta. See it today at firefly.adobie.com. So let's talk about it. Let's talk about it. I'm going to take a sip here. Shout out some of our super smart AI experts here in the comments. Yeah, yeah, Woozy says that you can't automate the 30% of time that workers actually aren't doing anything.

Yeah. You know, I'm going to have a whole other episode at some point about what it feels like to be overly productive with generative AI. It's weird. It's weird. Right? Daniel, Daniel, thank you for this. Daniel's saying knowledge work is commonplace. Subject matter expertise applied to context is valuable in where humans retain their value.

Yeah, I agree. Right. But we're going to be talking about, you know, we're not going to get too dorky into this, but, you know, the future of, you know, like rag. Right. Retrieval augmented generation. Right. So kind of the concept where you can kind of, you know, fine tune or personalize a

a GPT, you know, by uploading, you know, documents and putting in your, you know, configuration instructions. The same thing. I think we're going to be talking about RAG a lot, retrieval augmented generation for large language models, right? Kind of similar process where, yes, a large language model can comprehend, right? So it can analyze, it can comprehend. But everyone says, oh, well, it can't properly, you know, automate what comes after comprehension. Absolutely it can. That's where we're going to see this, this, this, in the personalized GPTs, which we're already seeing, that's where we're going to be talking about. You know, retrieval augmented.

I don't know why, y'all, like rag models are hard for me to say, retrieval augmented generation, right, where you kind of insert your data, you know, kind of before and after when that large language model is doing work. But let's just jump back into this. So if you're listening on the podcast, I'm sharing on my screen right now. what it looks like to use the internet now. And I'll tell you this, it is a hot mess. It is a hot mess.

And so much of our manual time, when we talk about getting a return on investment on generative AI, so much of every single knowledge workers manual time is going on the internet, reading, researching, doing competitive analysis, right? you know, maybe you're trying to create a guide for your team and you're looking at, you know, other other industries for examples. But so much of our time is spent reading things on the internet. And I talked about this and my predictions for 2024. But I said the internet is going to become unusable as, as is this screen here that I'm sharing, right?

This is an article that I was reading this morning. And literally now it is to the point when you are reading. an article online, so whether on your phone or on your desktop, where two-thirds or more of the screen is covered by ads, the internet is getting unusable. And that's because of AI. Here's what's happening, right? So you have the, you know, we talked a little bit about open AI case versus New York Times. The New York Times is suing open AI for billions of dollars for using millions of their articles without, you know, essentially paying or citing them or etc, right? But what's happening is so many large publishing companies over, you know,

the latter part of 2022 and especially in 2023, they've seen a huge reduction in visits to their website. And for so many companies, like a New York Times or, you know, maybe as an example, the screenshot I'm sharing here is a Yahoo finance, they make so much of their money by display ads, right? And before large language models started eating all of this information up, it was fine. Because if we wanted this information, we had to visit the website, right? So all the big publishing companies are happy. They're getting their, you know, thousands or millions of viewers a day. And they're getting their ad revenue. And it's a model that works, right? So what happens then when large language models just gobble all

this up and we no longer have to go read, you know, 10 different pages when we're putting together that new policy, right? We don't have to read, you know, eight different, you know, articles on this, on this new technique that you're trying to reach your team or that you're trying to teach your team. So this is what happens now, is an unusable internet, right? Where publishers, because they're losing money, largely to large language models, right? There's been so many studies that are showing it. That's the correlation. So now they're plastering their sites. So, Still, if you're a knowledge worker out there, you probably experience this, right?

The internet's becoming unusable, which means you're wasting time. You are wasting time if you're not doing this first part of, you know, analyzing and processing information via a large language model. So let's talk about what that looks like. So I'm sharing on my screen here, an example of doing this, right? So let's just say, hey, you're eight different articles that you need to read. to analyze them to take notes on a new program that you're launching within one of your departments, right? So you're reading all these articles, you're taking notes and you're

building something similar for yourself. So you're seeing who's done it before. You're following the blueprint, right? Instead, you can use a large language model. You can use chat GPT with plugins, right? And instead of going to those eight different articles and wasting all of your time, you can just jump in and do it. You know what? I don't do this a lot. I don't do this a lot. I'm actually going to try to do this, do this live. Shout up to someone said, you know, someone out there, one of our listeners said, you know what, Jordan, I liked when you did things live. And now you just do these, you know, screenshots.

You know, I don't like those. All right. So whoever that was, here you go. I'm going to hit enter and I'm going to explain what's going on here. Hopefully it works. All right. So here's a way to win back time. All right.

So I am in chat, GPT with plugins. Open AI. Please don't take plugins away. please, you don't understand what you're doing. All right. Sorry. So I'm in chat GPT mode with plugins. So if you have chat GPT, to use plugins, you need a plus account, which is $20 a month.

Okay. And then you can go into plugins mode and you can install different plugins. So some of my favorite plugins, and yes, I'm talking about plugins on a show about R.O. I on Gen. Because I honestly think that's still one of the best ways to win back the most manual time for any knowledge worker is by using internet connected plugins. Okay? So in this example, I'm using a web reader plugin. That's the name of it. So I just hit enter on this prompt. So this is all happening live. I'm letting it process below.

So I'm saying, please give me a brief summary of each of these articles using the web reader plugin. Okay. And then I'm giving it some directions on keeping it succinct, you know, how to complete the task. And also a little bit about what I care about as well. Because the other thing that makes the internet unusable and very hard for knowledge workers is kind of the advent of the advent of, of not the advent, but the resurgence of SEO over the last 10 years. You know, so what a lot of people found is, hey, the more information I put on my website, the more words, the more likely it is I'm going to get all these clicks and get all these users.

But here's the thing, 80% or more of what's on articles is fluff. You are wasting your time, right? You're going to read a super long article, spend, you know, 12 to 15 minutes on it. And then you're like, all right, well, out of that 12 to 15 minutes, one minute was useful. I just wasted all this time on a bunch of fluff, right? Like if you ever are looking for a recipe and it's like, why is this like, why is this 50,000 words for a recipe, right? And you got to find it. You got to search and hunt for it.

So by using a large language model, by using chat GPT with plugins, we can take that 12 minutes to find that piece of information into 12 seconds by using a prompt like this. And what I'm doing is I'm giving the web reader plugin all of these articles all at once. And I'm saying be my knowledge worker. If I read these, you know, I think on this example here, I have like five articles, right? If I read those five articles, if they're 12 minutes each, that's an hour. That's a lot of time, right? This is already done. It probably finished in a minute.

So I just won back 59 minutes, right? Well, I probably still got to read the summaries here, so maybe two minutes. But I just won 50 plus minutes. I just won back 90% of the time on that one manual task that so many of us do, just by using generative AI strategically at the right time. the right place, the right process. Right. So if you're listening on the podcast, I literally just dumped in all of these links.

I told this plugin to go in, read it all for me. And here's all the summaries. And I told it, here's what I care about as well, right? So that way, all the summaries are geared toward me. So here's, here's all the summaries. And I asked it for some more information, at least in this case, is, you know, the impact on everyday people in business, right? Just like that.

We're already winning back time. And we still got more. We still got more. All right. So that's one way. Yeah, Tara says so much noise, right? Yeah, there's literally so much noise for the average knowledge worker, which is so many of us, just trying to, trying to read or understand anything on the internet.

All right. Here's another example. And you know what? I'm going to say something nice about good. Google BARD. Oh, shocker. Shocker. If you've heard me talk on the show before, I'm sometimes a little hard on Google.

But, okay, another thing that so many knowledge workers do, and hopefully you're doing this for actual purposes, right? But when you're learning new things, I honestly think if you can find a good YouTube video, it is so much better than the 10 best articles, right? for that very reason, right, where all these articles have so much fluff. If you can find a good YouTube video, I think it's a good way to learn new skills, right? Obviously, it needs to be from a reputable source. Okay, but in this information here, what I have on the screen is, you know, there was a 40,

what is it there, 47 minute video that just came out, right? People always ask me, Jordan, how do you stay up on everything that's going on in AI? Well, I'm showing you right here. I just showed you one example. That's one way that I, you know, kind of read high-level recaps. of sometimes dozens of different news pieces a day using AI, or I might go into Google Bard and use their tool here. So this is a 47-minute video on what just happened at the World Economic Forum.

There was a panel discussion on AI, right? And there's probably a lot of these things, right? Think about your industry, think about your niche, think about your job, right? If you're, let's say you're in marketing, marketing is always changing. It's hard. Marketing is hard, you know. Mike Forgey, local marketing specialists here in the comments can probably tell you. It is nearly impossible with how much the world in marketing, advertising, communication is saying to stay up to date on marketing things, right?

So you probably spend a lot of time reading articles, watching YouTube videos, tutorials, et cetera. Think of all this that you do as a manual knowledge worker. Instead, you can use Google Bard. Yes, Google Bard's actually great on this. Google Bard is free. Okay. The first example I showed you, you need a page chatypte account.

This you can do with a free Google Bard account. Okay. You first need to go enable extensions. So there's a little, you know, if you do log into Google Bard, you should see a little puzzle piece icon at the top. And you need to enable the YouTube extension. But then then I can say this, what I just said here. I said, please use the YouTube extension and give me a recap of the video.

Please make the recap bullet, you know, just bullet points. Tell me what happened. Right. And then I leave the URL and then Google Bard using the YouTube extension goes through in a second. Not a second. It's probably like 10 seconds. Gives me a review. So here's a high level recap.

You know, it says, hey, here's what, you know, the panel discussed deep fakes and they discussed the potential for AI to be used in warfare and spread misinformation. Right. Cool. Okay. Well, then, then guess what? Then you can have a conversation. Right. And I said, please give me more information about what they said about deep fakes.

Right. So maybe there's only certain things I care about. But this is a new way to learn in an interactive way, to not just save time as a knowledge worker, but to actually get, I think, more out of it, to get more depth out of it, right? Because maybe I only care about one or two things in this 47 minute panel. But then I can ask a large language model, right? Give me more information about that. So they can both look it up in the context of the video.

but then they you know, Google Bart is connected to the internet. So it can also query the internet and bring in other relevant information in a succinct way, right? We're winning back time here, y'all. All right. I got one more. I got one more. And hey, if you do have a question, I might have missed it.

Get it in now because we're wrapping this baby up. This isn't going to be one of those solo shows where I accidentally go 50 minutes. All right. The last one as a knowledge worker, another way to get a big return on investment in generative AI, y'all, is so many people spend so much time reading and responding to emails, right? Think of that, those long email threads. And it's like, why did Bill in accounting just send me a 5,000 word email?

Bill, why? Right? How much of that pertains to me? But just think of how much time we all spend reading emails, analyzing them. maybe doing some research on this, right? Like, I don't want to respond right away. You know, I got to look this up, et cetera. There are so many great tools, right? So when we talk about, you know, as an example, Microsoft 365 copilot, right, AI on your desktop. It can read and analyze everything. And then you have, you know, that's more for enterprise companies, but then you

also have the new co-pilot pro, which is for literally anyone, right? Yeah, it's a subscription and it requires you obviously use Microsoft apps on your desktop, but still. At that point, it can read your outlook, right? You can be in the edge browser and, you know, think, oh, man, what was that in my email? And then you can just query it and have it, you know, pull up information from your email or have it read, respond, analyze to the content in your email or do additional research that's needed right then and there as well. Right. So here's an example. I just have a screenshot, right?

I have a couple Chrome extensions that I use to read and respond to my emails when they're long. or maybe if I'm stuck on a word, because here's the thing. Y'all, how much time have you, I'm a journalist. I won a bunch of writing awards way back in the day, but I spent almost a, not a decade, like seven years as a professional writer. And even I sometimes get like tongue-tied or how do I say this? Or how do I say this, you know, politely or with tact or, you know, how can I bring a little humor, right?

Use A.I. Use generative AI with how much time you spend reading and responding to emails. use generative AI. That's why in that, you know, seven ways to use AI in your business, I went through five different ways that, no, probably I think seven different ways, just that you can use generative AI AI to help you read, respond, analyze emails better and faster. All right.

So y'all, as we wrap up, I want to say this, easily. And I know technically this is return on time invested, right? That didn't ring as well. Gen A.I. You know, the biggest ROI for Gen A.I had a nice ring to it. But the biggest return on your investment is winning your time back on manual knowledge work. Okay. This isn't the pre-internet days.

This isn't even the post-internet days. And I know it's weird and it's a process, right? Because part of it is a lot of maybe why we're in the position that we're in, why we're, you know, working for the company or, you know, how we achieved our title of, you know, director of this department maybe came from those skill sets, the critical thinking, the analysis, right, that now you should be handing off degenerative AI. So I know it sounds weird because you're probably thinking, oh, no, AI can't read and analyze like me.

It can't put together a pitch like me. It can't process and critically create like me. My skills got me here. Guess what? It's your Gen. A.I. skills that are going to keep you there or to keep you rising. Because if you are not already using generative AI to win back your time, you are missing out on the biggest, the easiest, lowest hanging fruit on getting a return

an investment in your time and generative AI. Y'all, because what I always say is start where you spend. People always ask, oh, how do I start using, you know, how do I start using AI? You start where you spend your most manual time. That's why I just went over those three different examples, but maybe it's something else. But you start where you use where you spend the most manual time. Don't start with the best tool or, you know, with something you saw on Twitter or, you know, there's this new type of AI. Let me see how it can work for me. No, that's doing it wrong.

Categorize all your work. How do you spend each minute of each hour, each hour of each day, each day of each week? How do you spend it? Categorize it into buckets of manual knowledge work. Find out where you spend your most time. Maybe it's emails like we talked about. Maybe it's learning like we showcased. Maybe it's analyzing information like we also talked about in this show. Find that one area where you spend the most manual work. All right. As a knowledge worker, apply generative AI to it in the right way, the right place, at the right time, and you're already winning your time back. All right, y'all.

Thank you for joining us. I hope this show was helpful. If so, go to your everyday AI.com. Check out the show notes. I leave my email in there, my LinkedIn. Just drop me a message. Most of you all know if you're joining here on the live stream, I love connecting with you. I love just helping people learn and leverage AI, helping companies grow with AI.

That's what we're all about. So I hope to see you back for another episode of Everyday AI. Thanks, y'all. 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, and more in one conversational interface.

You direct the outcome while the assistant accelerates execution. Stay in control with the ability to step in and refine at any time. See it today at firefly.adobie.com. And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going. For a little more AI magic, visit Your EverydayAI.com

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