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Leveraging Generative AI to Win Back Time and Boost Business Productivity
In a rapidly evolving digital landscape, businesses are constantly seeking ways to optimize productivity and reclaim valuable time lost to manual knowledge work. The rise of generative AI technology presents a significant opportunity for organizations to streamline operations and enhance efficiency in the knowledge work domain. This article delves into the pivotal insights shared on today's episode of the Everyday AI podcast, shedding light on how businesses can harness generative AI to transform their approach to knowledge work and achieve a substantial return on investment.
Revolutionizing Knowledge Work with Generative AI
The podcast highlights the transformative potential of generative AI in revolutionizing traditional knowledge work processes. From processing information and responding to emails to staying informed through online research and learning, generative AI offers a strategic solution to tackle the time-consuming nature of these tasks. By incorporating generative AI into daily workflows, businesses can effectively streamline operations, allowing employees to focus on higher-value activities while harnessing the full potential of AI-driven automation.
Embracing the Economic Potential of Generative AI
A key highlight in the podcast episode pertains to the economic impact of generative AI, as outlined in a McKinsey study. It is emphasized that generative AI, along with other technologies, could potentially automate a significant portion of employees' time. This presents a compelling case for businesses to leverage generative AI as a catalyst for driving operational efficiencies and unlocking substantial time savings across various functions. By embracing the economic potential of generative AI, organizations can position themselves at the forefront of innovation and productivity enhancement.
Navigating the Information Overload Dilemma
In today's digital age, knowledge workers grapple with the challenges of information overload, leading to significant time investments in staying informed and processing vast amounts of data. The podcast underscores the role of generative AI in addressing this dilemma, citing practical applications such as using AI to summarize lengthy articles effectively and streamline the consumption of information. By deploying generative AI tools strategically, businesses can empower their workforce to navigate information overload more efficiently, enabling them to stay agile and focused on driving business outcomes.
Strategic Implementation and Future Outlook
An essential takeaway from the episode is the emphasis on strategic implementation of generative AI in specific areas where manual knowledge work dominates. By analyzing and categorizing work activities to identify key areas for AI integration, businesses can strategically leverage generative AI to reclaim valuable time and elevate productivity. The podcast also previews a discussion on three different ways to win back time on knowledge work, providing valuable insights for businesses seeking to harness the full potential of generative AI.
Connecting with Industry Experts
The podcast invites business owners and decision-makers to explore the possibilities of leveraging generative AI in their organizations, fostering a connection with industry experts and thought leaders. By engaging with the content shared in the episode and exploring avenues for integrating generative AI into their business strategies, organizations can pave the way for a future where AI-driven automation and efficiency are seamlessly intertwined with knowledge work practices.
In conclusion, the insights presented in this podcast episode underscore the transformative impact of generative AI on knowledge work and productivity in the business landscape. By embracing generative AI as a strategic tool for reclaiming time and optimizing workflows, businesses can position themselves for sustained growth and competitive advantage in a rapidly evolving digital ecosystem. It is evident that the intersection of generative AI and knowledge work holds immense potential for organizations seeking to drive operational excellence and propel their business into the future.
Topics Covered in This Episode
1. Leveraging Generative AI to Win Back Time
2. Impact of generative AI on knowledge work in business
3. Practical Applications of Generative AI
4. Challenges of Information Overload and Time Management
5. Impact of LLMs and and Internet Usability
Jordan Wilson [00:00:16]:
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 gonna be talking about today. I feel we've kinda got it solved, so we're gonna be unwrapping that today and more on Everyday AI. Welcome. If you're new here, My name is Jordan Wilson. I'm the host in everyday AI. It's for you.
Jordan Wilson [00:00:52]:
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. Alright. So if you're new here, thanks. Make sure to go to your everyday AI .com. Sign up for the free daily newsletter. Yes. This is a podcast.
Jordan Wilson [00:01:13]:
It's a livestream. 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 a 180 episodes. I say it is literally a free generative AI university. Whatever you wanna learn, you can go on and, you know, 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.
Jordan Wilson [00:01:49]:
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 r one device. So Rabbit has released its pocket sized a one device. You know, they announced it about a week and a half ago at CES. So the r one, and it acts as a universal controller for apps. Alright. So Rabbit has just announced that their r one hardware will be powered by Perplexity AI, one of our favorite, AI tools, for its large language model search with a free 1 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.
Jordan Wilson [00:02:36]:
Alright. 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 things to unpack here. We're gonna 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.
Jordan Wilson [00:02:59]:
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 1,000,000,000 of dollars, billions with a b, 1,000,000,000 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 gonna 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 OpenAI.
Jordan Wilson [00:03:51]:
Alright. 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, little different than large language models. So Kind of it's also known as generative AI, but that's led to a rapid adoption in health care applications, which can provide clinical notes, diagnose, and treat patients, etcetera. Right? 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 a 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. Alright.
Jordan Wilson [00:05:03]:
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 7 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 gonna drag y'all on. So the one biggest return on investment or generative AI is winning back your time on manual knowledge work.
Jordan Wilson [00:05:43]:
Alright? 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 you know, Getting these 50 different programs, it is literally just winning back your time on manual knowledge work. Alright. We're gonna unwrap this, but I also hey. Before we do, I gotta give a shout out to everyone joining us.
Jordan Wilson [00:06:05]:
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 you know, Daniel and and Thomas, everyone joining, Or Kansas City, our woozy Rogers, or Caron. Let me know. Have you won back your time yet? And if so, how? Might might shout 1 or 2 out, but also let me know if you do have any questions about how the best way is to win back your manual time. Like, what's the best way to go about that? We're gonna be going through 3 different ways at the end. Alright? And like I said, go go listen to that, the 7 ways Episode, the 7 ways to use, AI in your business. Y'all, that was I'm not gonna lie.
Jordan Wilson [00:06:48]:
That was a banger. That was one of our best episodes we've ever done. Alright. But let's let's talk a little bit more about winning back your time on knowledge work. Alright. 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 gonna be hearing it a lot. Right? Especially, you you know, we talk about even the World Economic forum.
Jordan Wilson [00:07:09]:
That's that that 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 our, you know, collective business toes in all these different generative AI applications across the business spectrum, It was more about discovery. It was more about learning. And 2024 is going to be the year of action.
Jordan Wilson [00:07:39]:
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. K? Let's think pre Internet. Right.
Jordan Wilson [00:08:15]:
Knowledge work was at a premium at that point. Because if you knew a certain skill set that could move the the 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. Alright? Post Internet. You know, the last 25 years or so that 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.
Jordan Wilson [00:09:07]:
But this is where generative AI changes things. Alright? And, you know, let's I'm gonna hit pause on that, and then I wanna 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 probably heard me talk about this before, like what we do in business. Okay? Because what we do in business, if you are a knowledge worker, again, that is Essentially, anyone that sits in front of a computer and uses the Internet, you know, 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 5 categories. So it's either in meetings, the actual time in meetings, or the proper follow-up that comes with it. Learning, that's a big one. So reading, note taking, etcetera.
Jordan Wilson [00:10:05]:
Right? Processing information. Writing, Which is emails, you know, writing e writing and responding to emails. You know, that's also reading, creating internal documents, analyzing. So that could be actually analyzing that information or, you know, creating spreadsheets, charts, etcetera, or presentations. Right? So maybe sales calls, pitching something whether internally or externally, training, you know, training people on your team. Alright. So here's the thing. These are all examples of knowledge work.
Jordan Wilson [00:10:35]:
Alright? And this is literally what we do in business. Alright. I get what you're saying, Jordan. Probably like, alright. 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, we'll we'll we'll link it, in the show notes for the podcast, and we'll throw it in the comments, in the LinkedIn stream.
Jordan Wilson [00:11:04]:
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 I wanna 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% of employees' time today. I'm gonna go ahead and say something. I'm gonna make a not so bold claim.
Jordan Wilson [00:11:37]:
I know it's not hot take Tuesday, But I'll just give you a bold claim. This study is wrong. It's wrong. 60 to 70% is an understatement. Right? A previous version of this exact same study said 50%. And then they acknowledge 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.
Jordan Wilson [00:12:01]:
That's wrong. 60 to 70%, 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 gonna 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%. 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.
Jordan Wilson [00:12:43]:
Right? But y'all, are you getting this yet? Right? This is one of the reasons I I freaking started a podcast livestream newsletter. I've seen the writing on the wall for this for for for years. Right? That's why I started everyday AI because I think everyone needs a guide to 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 the mid to late nineties. Right. I started I guess, I I wasn't a desk worker until, you know, like, 2002 or something like that, but, you know, people have been using the Internet, you know, for at least, you know, 8 to 10 years by that point. But Employees and companies at the advent of the Internet had time.
Jordan Wilson [00:13:48]:
Right? I've talked about this on the show all the time. You easily had whether you were employee, Maybe you just didn't wanna 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 ahead 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.
Jordan Wilson [00:14:26]:
I don't care what anyone says. Right. Yo. I've I've talked to the leading experts. I've spent 1,000, 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. They and it's a 3 it's a 3 part step.
Jordan Wilson [00:14:57]:
Right? You read or analyze or you read something. K. You analyze it in your head, and then you apply something or you do something on the back end. K. So the Internet really only changed the 1st part or 2. 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.
Jordan Wilson [00:15:25]:
It is not like the Internet. It's as far from the Internet as possible, which is why, you know, I almost vomit in my mouth I hear other people talking about, oh, you know, look at the Internet. Look at what it did. It's that's no. That's not how generative AI works. It creates intelligence. I will argue with anyone on that. Alright.
Jordan Wilson [00:15:45]:
And according to McKinsey, 60 to 70% of employees' time. Alright. So here's what we're gonna talk about for the rest of the show. We're gonna win back time today. The biggest return on investment is winning back your time on 1 area, processing information. Okay? It is that 3 part step that I just laid out. It is understanding it and then it's applying and do something with that knowledge. Hey.
Jordan Wilson [00:16:55]:
Everyone's prompting wrong, and the PPP course fixes that. If you want access, go to podpp.com. Again, that's podpp.com. Sign up for the free course and start putting ChatGPT to work for you. So let's let's talk about it. Let's talk about it. I'm gonna take take a sip here. Shout out some of our super smart, AI experts here in the comments.
Jordan Wilson [00:17:27]:
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 gonna have a whole another 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.
Jordan Wilson [00:17:47]:
Thank you for this. Daniel is saying knowledge work is commonplace. Subject matter expertise, applied to context is valuable and where humans retain their value. Yeah. I agree. Right? But we're gonna be talking about you know, we're not gonna 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 construct instructions.
Jordan Wilson [00:18:25]:
The same thing. I think we're gonna 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.
Jordan Wilson [00:18:46]:
That's where we're gonna see this this boom in the the the personalized GPTs, which we're already seeing. That's where we're gonna be talking about. You know, retrieval, augmented. I don't know why y'all. Like like, rag 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 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.
Jordan Wilson [00:19:21]:
And I'll tell you this. It is a hot mess. It is a hot mess. In so much of our manual time, when we talk about getting a return on investment on on generative AI, So much of every single knowledge worker's 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 other industries for examples. But So much of our time is spent reading things on the Internet. And I talked about this in my predictions for 2024, But I said the Internet is going to become unusable as as if this screen here that I'm sharing.
Jordan Wilson [00:20:05]:
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 2 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, OpenAI case, versus New York Times. The New York Times is suing, OpenAI for 1,000,000,000 of dollars for, using 1,000,000 of their articles, without, you know, essentially paying or citing them or, etcetera. 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 New York Times or, you know, maybe as an example, the screenshot I'm sharing here is at Yahoo Finance.
Jordan Wilson [00:21:04]:
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, happy. They're getting their, You know, 1,000 or millions of viewers a day, and and they're getting their their ad revenue. And it's 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, 8 different, you know, articles on this on this new technique that you're trying to reach your team or 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.
Jordan Wilson [00:21:59]:
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're prob you probably experienced 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 let's talk about what that looks like. So I'm sharing on my screen here an example of doing this.
Jordan Wilson [00:22:32]:
Right? So let's just say, hey. You're Eight different articles that you need to read to, you know, analyze them, to take notes on a new program that you're launching within one of your, 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 ChatGPT with plug ins. Right? And instead of going to those 8 different articles and wasting all of your time, You can just jump in and do it.
Jordan Wilson [00:23:05]:
You know what? I don't do this a lot. I'm actually gonna try to do this do this live. Shout out 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. Alright. So, whoever that was, here you go. I'm gonna hit enter, and I'm gonna explain what's what's going on here. Hopefully, it works.
Jordan Wilson [00:23:26]:
Alright. So here's a way to win back time. Alright. So I am in chat GPT with plug ins. OpenAI, please don't take plug ins away. Please. You don't understand what you're doing. Alright.
Jordan Wilson [00:23:40]:
Sorry. So I'm in chat GPT mode with plug ins. So, if you have chat GPT, To use plug ins, you need a plus account, which is $20 a month. Okay? And then you can go into plug ins mode, and you can install different plug ins. So some of my favorite plug ins, And, yes, I'm talking about plug ins on a show about ROI on Gen AI 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 plug ins. Okay? So in this example, I'm using a web reader plug in. That's the name of it. So I just hit enter on this prompt.
Jordan Wilson [00:24:14]:
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 plug in. 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, not not the advent, but the Resurgence of, you know, 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 gonna get all these clicks and get all these users.
Jordan Wilson [00:24:48]:
But here's the thing. 80% or more of what's on articles is fluff. You are wasting your time. Right? You're gonna read a super long article, spend, you know, 12 to 15 minutes on it, and then you're like, alright. Well, out of that 12 to 15 minutes, 1 minute was useful. I just wasted all this time on a bunch of fluff. Right? It's 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 gotta find it. You gotta search and hunt for it.
Jordan Wilson [00:25:15]:
So by using a large language model, by using chat GPT with plug ins, 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 plug in all of these articles all at once, And I'm saying, be be my knowledge worker. If I read these you know, I think on this example here, I have, like, 5 articles. Right? If I read those 5 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.
Jordan Wilson [00:25:44]:
So I just won back 59 minutes. Right? Well, I probably still gotta read the read the summaries here, so maybe 2 minutes. But I just won 50 plus minutes. I just won back 90% of the time on that 1 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 plug in to go in, read it all for me, And here's here's all the summaries. And I told it, here's what I care about as well.
Jordan Wilson [00:26:20]:
Right? So so that way, the 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. Alright. So that's one way. Yeah.
Jordan Wilson [00:26:47]:
Tara 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 any you know, understand anything on the Internet. Alright. Here's another example. And you know what? I'm gonna say something nice about Google bard. Oh, shocker. Shocker.
Jordan Wilson [00:27:06]:
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.
Jordan Wilson [00:27:57]:
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 Bart, Right? And and use their their tool here. So this is a 47 minute video on what just happens. At the World Economic Forum, there was a panel discussion on AI. Right? And there's probably a a lot of these things. Right? Think about your industry. Think about your niche. Think about your job.
Jordan Wilson [00:28:26]:
Right? If you're, Let's say you're in marketing. Marketing's always changing. It's hard. Marketing is hard. You know? Mike, 4 g, local local marketing specialists here in the comments can probably tell you. It is nearly impossible with with how much The world in marketing, advertising, communication is saying to stay up to date on on marketing things. Right? So you probably spend a lot of time reading articles, Watching YouTube videos, tutorials, etcetera. Think of all this that you do as a manual knowledge worker.
Jordan Wilson [00:28:55]:
Instead, you can use Google Bar. Yes. Google Bar is actually great on this. Google Bar is free. Okay. The first the the first example I showed you, you need a paid Chattopet account. This, you can do with a free GoogleBARD account. Okay? You you first need to go enable, extensions.
Jordan Wilson [00:29:10]:
So there's a little you know, if you do log in to 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 Barred using the YouTube extension goes through In in a second not a second. It's probably, like, 10 seconds. Gives me a review.
Jordan Wilson [00:29:41]:
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 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.
Jordan Wilson [00:30:16]:
Right? Because maybe I only care about 1 or 2 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 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. Alright. I got 1 more. I got 1 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.
Jordan Wilson [00:30:48]:
This isn't gonna be one of those solo shows where I accidentally go 50 minutes. Alright. The last 1, As a knowledge worker, another way to get a big return on investment to 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 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 some research on this. Right. Like, I don't wanna respond right away. You know, I gotta look this up, etcetera.
Jordan Wilson [00:31:33]:
There are so many great tools. Right? So when we talk about, you know, as an example, Microsoft, 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, Copilot Pro, which is for literally anyone. Right? Yeah. It's 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.
Jordan Wilson [00:32:04]:
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 not a decade, like 7 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 or with tact or, you know, how can I bring a little humor? Right? Use AI.
Jordan Wilson [00:32:51]:
Use generative AI. With how much time you spend reading or responding to emails, use generative AI. That's why in that, you know, 7 ways, to use AI in your business, I went through 5 different ways that, no. Probably, I think 7 different ways that just that you can use Generative AI AI to help you read, respond, analyze emails better and faster. Alright? So, y'all, as we wrap up, I wanna say this. Easily. And I know technically this is return on time invested. Right? That that didn't that didn't ring as well.
Jordan Wilson [00:33:31]:
Gen AI, you know, the biggest ROI for Gen AI 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 it's it's weird, and it's 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 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 to generative AI. So I know it sounds weird because you're probably thinking, oh, no.
Jordan Wilson [00:34:22]:
AI can't Read and analyze like me. It can't put together a pitch like me. It can't process and and and critically, create like me? My skills got me here. Guess what? It's your Gen I skill Gen AI 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 on investment and your time in generative AI. Y'all because What I always say is start where you spend. People always ask, oh, how do I start using gen 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 those 3 different, examples, but maybe it's something else.
Jordan Wilson [00:35:21]:
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, oh, 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.
Jordan Wilson [00:35:49]:
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. Alright? 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. Alright, y'all. Thank you for joining us. I hope this show was helpful.
Jordan Wilson [00:36:18]:
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 y'all know if 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.
Jordan Wilson [00:36:39]: