Join the discussion: Ask Jordan questions on AI
Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
Connect with Jordan Wilson: LinkedIn Profile
Embracing the Untapped Potential of GenAI in Business
As the technical landscape evolves, businesses are challenged to adapt and explore new tools to fulfill their operational potential. One such tool currently on the horizon is *Generative AI* (GenAI), a technology that goes beyond mere automation to actively contribute to business processes and strategies.
Despite businesses prioritizing AI with 83% keen on exploring its potential, only 4% of them have fully integrated it. This mismatch reflects the daunting nature of implementing AI, given its complex nature and immense implications.
Unlocking the Benefits of GenAI: Five Step Approach
Adopting GenAI into business operations doesn't need to be an intimidating process. Here's a five-step approach that can help ease the transition, ensure ethical use of AI, and mitigate potential risks.
1. Gather Insights
Consider assembling a 'ground-up' committee to gather diverse insights and create organic buy-in. The knowledge and perspectives from different aspects of your organization will foster transparency and encourage broader cooperation.
2. Create Guidelines
Building on insights gathered, develop clear AI policies and guardrails that align with your business objectives and ethical considerations. Laws and guidelines from organizations such as EU AI Act, UNESCO's recommendation and the National Institute of Standards and Technology can serve as a useful benchmark.
3. Kickoff with a Measurable AI Project
Instead of launching an ambitious, gigantic AI model, start with a small, quantifiable project that reflects clear wins in terms of time and cost savings. This positive, discomfort-free start will build momentum for larger projects down the line.
4. Invest in Education
With GenAI being a technical subject, misunderstanding can cause hesitations and doubts. To build trust and awareness, invest in training and education. Align these classes with long-term goals to prepare employees for the AI-shaped future workplace.
5. Plan for GenAI’s Future Impact
GenAI will inevitably reshape the business landscape, potentially automating up to 70% of activities that currently consume employee's time. It's crucial to plan for job transition and transformation, ensuring employees are part of the future and not left behind by technological advances.
Guidelines, Guardrails and Ethical Considerations
In the context of GenAI, guidelines and guardrails play a crucial role in preventing misuses while aligning AI application with your business strategy. Remember to maintain a focus on ethical decision-making and caution with sensitive data. In this regard, regulations from reputable sources like the EU AI Act and the National Institute of Standards and Technology offer valuable guidance.
The Bottom-Up Approach to GenAI Implementation
For meaningful and sustained AI integration, a ground-up approach is recommended over a top-down model. This encourages adaptability and incorporates more data, as opposed to a top-down approach which can often be rigid and anecdotal. Remember: open and honest conversations, as well as transparency, are key components of this bottom-up approach.
GenAI: A Future-Proof Investment for Businesses
Deploying GenAI successfully requires careful planning, thorough grounding of guidelines and ethical boundaries, and committed employee education. It's not an overnight revolution, but a thoughtful evolution. Once accomplished, GenAI will not only streamline your business operations but also prepare your organization for a robust and resilient AI-powered future.
While the transition might appear challenging initially, it's worth remembering that technological adaptation has always been a cornerstone of business development and growth. The steps outlined above should help ease the integration process of GenAI into your business operations, bringing you one step closer to a more productive, efficient and Future-Ready business model.
Topics Covered in This Episode
1. AI in Business
2. Implementing AI
3. AI Guidelines and Guardrails
4. Practical Application of AI
Jordan Wilson [00:00:17]:
Implementing generative AI in your business today is one of the hottest topics, and it's something that just about everyone is trying to figure out. And I thought to myself a couple of weeks ago, wait. I've talked to more than A 120 experts, leaders in generative AI from across the globe working at some of Biggest companies and entrepreneurs, small business owners. And I said, I think we've got a pretty good blueprint here. So that's what we're gonna be going over today, the 5 simple steps to start using Gen AI in your business today. I'm saying this now, y'all. Like, we've hit almost 200 episodes here on everyday AI, and I think this Particular episode is probably going to be one of the most helpful. So, thank you for tuning in.
Jordan Wilson [00:01:09]:
If you're joining us, Welcome. For the 1st time, welcome. My name is Jordan Wilson. I'm the host of Everyday AI, and this is for you. Everyday AI is your daily livestream, podcast, and free daily newsletter to help you demystify generative AI and, to teach you how you can actually use it to grow your company and to grow your career. Alright. So if you're on the podcast, make sure to check out your show notes. We always keep, some some helpful information in there as well as related episodes.
Jordan Wilson [00:01:39]:
And if you're joining us live, like, we already have quite a few people in the house. Like, hey. Hey. What's going on? And doctor Harvey Castro and Brian and Mauricio, Tara, Brian, Joan, so many people. Thank you all for joining us. We're gonna get to the big topic here in a minute, the 5 simple steps to start using Gen AI in your business today. But before we do, Let's start as we always do by going over the AI news. And as a reminder, you can always go to your everyday AI.com To find out more about not just these news stories, but we always break down each day's, interview into great detail.
Jordan Wilson [00:02:17]:
Right? So, let's let's go ahead and and look at what's happening now in the world of AI news. So first, OpenAI and Microsoft are investing in humanoid robots. So Microsoft and OpenAI may be considering investing up to 500,000,000 in a humanoid robotics startup called Figure AI. So Microsoft and OpenAI are reportedly in talks according to Bloomberg reports to invest, to invest in the humanoid robotic start up Figure AI potentially valuing the company At just under $2,000,000,000. Figure AI, get this here, it's was just founded in 2022, but it does have a team of top roboticists in From Tesla and Boston Dynamics. So they've already secured a partnership with BMW, but it's looking like they're about to, NAB, 2 huge partners in OpenAI and Microsoft. I talked about this in the, you know, things to look for in 2024. I said Smart robotics in actual workplaces are going to be a thing, and they are.
Jordan Wilson [00:03:19]:
So I know it's weird, but What's even weirder than that is our, maybe, next piece of news is this isn't science fiction, but we are talking Neuralink. Yeah. So, Elon Musk Just talked a little bit more about recent breakthroughs in Neuralink after its 1st successful implant in a human brain. So Neuralink is a neurotechnology company founded by Elon Musk, and it has successfully well, it's reporting that it has successfully implemented It's telepathy chip into a human for the first time. So the chip allows individuals with paralysis to control external technologies using their mind. So the telepathy chip has the potential to greatly improve the lives of those with severe generative diseases such as ALS By enabling communication and interaction with technology using just neural signals from that chip implanted on the brain. So this clinical trial marks a significant step towards commercialization from Neuralink, but it obviously also raises some concerns about the long term effects and security of brain compute computer interfaces. I don't even think we need to talk about those.
Jordan Wilson [00:04:25]:
You can imagine having a Piece of AI chip on your brain. Alright. Speaking of being able to control, smart technology, GPT mentions have been rolled out To all ChatGPT users. So, if you are on the paid ChatGPT plus or Teams or enterprise accounts, you should have access, to this new GPT mentions feature now. So this essentially allows you to work, with multiple GPTs within the same chat. So, this feature was rolled out to a very select few last week, but a fast general rolled out to all paid users, just a couple of hours ago. So this is a baby step, I'd say, toward the concept of agents or, you know, working with multiple specialized GPTs working in the same chat. So we'll actually have more on this today on our YouTube channel here on LinkedIn, but we'll also be incorporating this into our, ongoing free prime prompt polish training, our PPV training.
Jordan Wilson [00:05:27]:
So, if If you wanna know more about mentions, we're gonna be going over the basics of this in our free PPP training. So you can always just hit me up and just say PPP, and I'll send you the information to sign up. Alright. That's a lot of news. But as a reminder, go to your everyday AI.com to get more information on these, stories by signing up for our newsletter. Also, it is legit, a free generative AI university on our website. You can go look at our different learning tracks. Let's say you care about education.
Jordan Wilson [00:05:54]:
We have a handful of, you know, podcasts with experts just on education. So no matter what your role is, no matter what you are trying to learn and leverage To grow your company, grow your career. We already have so many podcasts specifically for that. Alright. So let's get to it y'all. Let's get to the 5 simple steps to start using Gen AI in your business today. Alright. So I'm gonna hit rewind, and then I'm just gonna quickly tell you those 5 steps.
Jordan Wilson [00:06:20]:
I'm not gonna draw you along for another 20 minutes like I sometimes do when I'm by myself. But let me tell you this. We've been working with companies of all sizes, not just with, you know, GPT and AI consulting and and strategy, But even previously, before I even started Everyday AI, we essentially did digital strategy for companies of all sizes, and We've been able to grow companies of all sizes, so I want you to keep that in mind. Yes. A lot of what we do here at Everyday AI also draws on my background as being an and journalists and, you know, giving, you all the the actual news and the actual facts and breaking down how generative AI technology works and giving you and Actionable steps on how you can actually use it, but we've been growing companies for a while. And I noticed something, a couple of months ago. I said, I've talked to dozens of experts from, you know, 1,000,000,000 and $1,000,000,000,000 companies. You know? Companies like And multiple guests from NVIDIA and Microsoft and IBM and AWS.
Jordan Wilson [00:07:23]:
Right? So, all of these companies Building this technology, this generative AI technology that we're all using. And I I'm I'm always talking to people kinda behind the scenes, so people that aren't even on the show. And I've realized, wow, I have literally thousands of pages of show notes with so much great information and then drawing on things that we've and discovered ourself, and it always gets back to this question. People are always asking, okay. This generative AI sounds great, But how do I actually use it? And sometimes I I I I send people, you know, 3 or 4 shows, and I'm like, oh, there's great insights here great insights here. But this is, I think now going to be potentially the single most helpful podcast we've ever done. Yes. Out of 200
Jordan Wilson [00:08:12]:
or just about 200. The most helpful. Alright. So let's skip ahead right now and tell you those 5 steps.
Jordan Wilson [00:08:23]:
I'm not gonna drag you on here. Alright? But we're gonna dive deep into each of these 5 steps So you can understand them. Alright? So step 1, gather insights from a ground up committee. Step 2, create straightforward guidelines with guardrails. Step 3, Sprint toward your 1st measurable AI project. Step 4, invest heavily in education and training that align with long term business goals. In step 5, plan for a future of what happens when AI works. I am excited to dive into each of these, a little deeper.
Jordan Wilson [00:09:08]:
But I will let you know this. Even my show notes for this show are crazy long. Right? I'm gonna try not to make accidentally make this, you know, an hour long podcast. But go ahead. If this show is helpful for you, please, go repost This. If you're listening on LinkedIn or maybe, you know, you found this, post on Twitter, just repost this, and I will send you Literally all of my episode notes. I think I have, like, 10 or 15 pages. So there's so many specific insights even on just these 5 steps That I'm not gonna get it that I'm not going to be able to get to.
Jordan Wilson [00:09:47]:
Alright? And I'll tell you this, if you go higher we've had great even AI consultants on our show. If if you hire Someone like that or even higher companies like ourselves. It's oftentimes tens of 1,000 of dollars or more. So there is so much valuable and practical information literally just in my show notes that I won't be able to get to. So make sure, you repost this, or, you know, retweet this on Twitter or repost it here on LinkedIn, and I'll send you everything. Alright. And I'm actually curious as I as I sit here and take a sip, of my lukewarm coffee before we get into it. So, everyone joining us here live, like, hey.
Jordan Wilson [00:10:24]:
All these great PPP supporters too, like and Harvey and Brian and and Ted. What's going on, Ted? Another Chicago guy. But let me know right now. I wanna know, especially from our our livestream audience. Is your company actually using generative AI in your day to day? Let me know. You can just type in, like, 1, not yet. You can just type in 2, we're using Gen AI a little, or you can type in 3 and just say we're using Gen AI everywhere. I kinda wanted to do an unofficial, A poll of our livestream audience.
Jordan Wilson [00:10:54]:
And, hey, let me know also if you're, listening on the podcast. You can always just email me and let me know how even your company, is is using this because there's a lot of, studies out there. But I'm also wondering, hey. Our, you know, growing community of AI enthusiasts. I'm guessing maybe y'all are a little ahead, of everyone else, but maybe not. Maybe, you know, you're that load advocate, you know, in your company really pushing AI. I actually got a great, you know, message. I think it was all my days are blending together.
Jordan Wilson [00:11:26]:
I think it was last week someone said, hey. I got promoted to head of AI in my entire company, and they thanked me and the everyday AI, Crew for being a part of that. Right? So okay. Looking looking at our unofficial poll here, it it looks like most, most of us are in the the the the 1 or 2. So it looks like either most companies haven't yet, dove in, to generative AI Or maybe just using it just a little. We we we do have a couple, couple advanced people here like, like like Justin and, and Mabrit And Daniel who are using it everywhere, but it looks like most people are in the 1 or 2. So either not using it yet or, using generative AI just a little. And, you know, we did talk about this just a little bit yesterday in our episode.
Jordan Wilson [00:12:19]:
Very related episode on, education and Training, so make sure to go check that out. But I'm gonna I'm gonna recap just 2 or 3 stats that I think are, speak to exactly what we just talked about. How is your company using generative AI? Because a recent Forbes study said 83% of companies claim that using AI in their business strategy is a top priority. Yet. A tech dotco study found that only 4% of companies have implemented AI AI throughout their org. Let me say that again. If you're listening on the podcast because you can't see my screen right now, that, you know, I'm showing all of these different studies, but 83% of companies say generative AI is a top priority, yet only 4% Have implemented it throughout their organization. That is a huge problem.
Jordan Wilson [00:13:14]:
It's a huge problem. We talked about this yesterday. I think so many companies are just throwing money at the problem versus rolling up the sleeves, digging in deep, and getting this thing figured out. Alright. One other stat from Ernst and Young, So 73% of people are concerned about their organization Not offering sufficient training. Right? So not just that, but so many studies just say that, you know, employees, managers, directors Don't have full confidence in their leadership to be able to lead them forward in AI implementation.
Jordan Wilson [00:13:53]:
Alright. Let's start to solve that. Shall we? Alright. Here we go. This is
Jordan Wilson [00:14:02]:
a lot y'all, but get your you know, if you do have questions, try to get them in. I might not be able to get to them in real time, but I'll try to grab your questions and your comments. You know? Love hearing from you. Sometimes we, we mention our favorites, in the newsletter. So let's start with step 1. Ready? Again, this is from hundreds of hours of conversations With, you know, the top executives building AI, but also with small business owners, entrepreneurs, startups. Right? And also, hey. This is We've taught more than 2,000 business leaders proper prompt engineering with our free PPP course.
Jordan Wilson [00:14:43]:
Right? So This is a culmination of literally hundreds of hours on talking about AI implementation. It starts with step 1. Need to gather insights from a ground up committee.
Jordan Wilson [00:14:57]:
In every word that I chose here in these 5 rules is intentional. Because AI implementation is not top down. It is bottom up. One of the biggest mistakes.
Jordan Wilson [00:15:12]:
If you want AI to work for your company, this isn't a CEO directive. Right. Because so many times sorry, c suite people. So many times, c suite people c suite people are removed from knowledge work. Okay. Generative AI helps you win back time in knowledge work. You can't You can't make directives from the top of the mountain when everything's happening on the ground level. Alright.
Jordan Wilson [00:15:41]:
Also, a ground up committee Prioritizes transparency, safety, and alignment. So this bottom up approach is actually pretty similar to how even OpenAI and Google have developed their own AI invitation. Alright. You can go read about that, but there's plenty of research out there. Another huge benefit In a ground up approach is you get people from all levels of the company. Right. You get people who in theory are actually going to be using whatever generative AI systems that you will be deploying. You get a diverse group of perspective.
Jordan Wilson [00:16:18]:
Right? You get a diverse perspective. K. I tell people Who's actually going to be using this generative AI technology the most if and when it's successful? Because those are the people whose voices that you need to hear at The beginning. Again, this isn't for your leadership team to, to create something and then, you know, pseudo get feedback from people before it
Jordan Wilson [00:16:43]:
rolls out. No. You build it from the ground up and gather insights from the ground up committee.
Jordan Wilson [00:16:51]:
K. Here's another reason why that approach is preferable, and it will work better in the long run. Well, it because You can then incorporate more data and be more adaptable, whereas a top down approach, which is what almost everyone does, a top down approach is anecdotal. Right. Someone up there from the top of
Jordan Wilson [00:17:09]:
the mountain with binoculars. They're telling a story. They don't understand it. Top down is anecdotal, rigid, and often misplaced. Bottom up. It learns from actual data from the people who are actually doing it, and it becomes adaptable.
Jordan Wilson [00:17:27]:
Let me start with this. You notice how step 2 is guidelines and guardrails, not step 1. K. Step 1 is gathering insights, having open and honest conversations. You need to talk with people first. And here is the most important thing that you need to talk about in this committee. Why?
Jordan Wilson [00:17:56]:
You need to have a serious in transparent conversation about the why. I can go ahead and,
Jordan Wilson [00:18:04]:
in theory, answer that for you. Well, here's why. Talked about this once or twice before in the show, but a recent McKinsey and Company research shows that generative AI may automate work activities that absorb up to 70% of employees' time. Yeah. It's the future of work. It's generative AI from of your day to the end of the day, and it's working 247 for your
Jordan Wilson [00:18:27]:
company. Right? That's the thing. Generative AI doesn't sleep, Doesn't need to. Doesn't need a break. Doesn't need vacation. Doesn't need PTO. But you have to have the conversation.
Jordan Wilson [00:18:40]:
Why? Because one of the biggest disparities between that 83% of companies saying generative AI is the most important initiative and only 4% of, companies actually implementing it across their organization is friction. It's friction and a lack of transparency because, obviously, your your, quote, unquote, frontline workers, your coordinators, your entry level people
Jordan Wilson [00:19:08]:
are probably gonna be hesitant toward generative AI. Because
Jordan Wilson [00:19:13]:
the story of generative AI, we're gonna talk about this more here, pretty soon. Is that you cut jobs and don't replace them. Or maybe you cut a 1,000 jobs And you are left with 100 people working with AI. Right? That's what's happening. It's already been happening, widespread scale even so far in 2024. So you have to have an honest an honest and open conversation about why AI. Are you just trying to automate all of those tasks? Or are you trying to clear the mundane For your most important employees and allow them to focus on the meaningful. You know? And part of this and we'll get into this in part 5.
Jordan Wilson [00:20:00]:
But part of what you need to talk about in your ground up committee is
Jordan Wilson [00:20:05]:
talking not just about why, but what happens when it works. Alright? So more on that in part 5. So you might be asking, okay. This sounds like a pretty big ordeal.
Jordan Wilson [00:20:16]:
We need a ground up committee. You should be bringing in members from just about every organization. This isn't to kick the can. This should be, Yes. You should patiently take in insights from everyone, but you also need to move.
Jordan Wilson [00:20:33]:
This isn't one of those committees that meets quarterly And, you know, you're gonna kick the can for, 18 months. You will probably either go out of business or you are going to be bleeding. Okay. When I talk about a committee, this is a fast committee. You need to be patient in hearing your people out, But you have to be able to implement it with speed and prioritizing
Jordan Wilson [00:21:02]:
That generative AI implementation is crucial for the success sustainability of your business, Period. Said this yesterday. I've said this a 100 times. Think of how your company or companies in general Had a good 15 ish year period to adapt to the Internet. Alright? But hey. Now if you're not using the Internet, you can't do business. Right. If you're a knowledge worker, you can't.
Jordan Wilson [00:21:32]:
Period. Right? Your your Your HI your your your HR, your your marketing, your customer service. Everything's online. Okay? So think of that 15 to 20 year period where companies Had the safety net to adapt to the Internet. With generative AI, you have 15 to 20 months, and we're already midway through that. You have to act with a sense of urgency in this committee, but you also don't have to start from scratch. K? Look at other countries and other organizations For guidance. You know, you can follow the model of a large language model.
Jordan Wilson [00:22:08]:
You can just, Borrow ideas from those that have come before you and have put in the hard work. I'm not telling you to plagiarize. Don't do that, but see what other companies are doing. Other companies other countries other groups of countries are doing successfully when it comes to AI implementation in the workplace. Alright. Couple examples. The EU AI Act. Go read it.
Jordan Wilson [00:22:33]:
See what may apply to your company. The Hiroshima AI process, highly regarded as one of the most respected, kind of AI implementation Processes out there. It was even cited by the White House executive order on AI. Another, resource for your company is to look at the White House executive order on AI, but also the White House select committee on AI. Go Look at their work a little bit more on AI .gov. We're getting some preach Jordans. Alright. So So people are feeling this.
Jordan Wilson [00:23:09]:
This is good. Stick around. It's gonna get better. Don't worry. Alright. And, hey, keep keep Keep your comments coming. Keep your questions coming. I'm gonna try to tackle them at
Jordan Wilson [00:23:19]:
the end or as I go along. We'll see. Alright. Ready? Step 2, And notice,
Jordan Wilson [00:23:28]:
we don't start with guidelines and guardrails. That is step 2. If you are starting With guidelines and guardrails, you are just creating friction that tells your employees, right, Whether you have a team of 100 or 100,000. If the first time your company Or your employees hear about AI implementation. Your AI your generative AI implementation strategy is going over The guidelines and guardrails? Failure.
Jordan Wilson [00:24:01]:
You've already failed. You've lost the battle before it's begun. Don't start there. This is not like any other technical implementation. This isn't like bringing in
Jordan Wilson [00:24:11]:
a new CRM, you make the decision and train someone. This is changing the way we work. And people, understandably so, who don't understand generative AI technology are gonna be uneasy. So if you start with step 2, You're gonna lose people. You're gonna lose people. People are immediately gonna be scared of their jobs, and you're probably gonna your your your churn is gonna go through the roof. Right. If you don't get people's buy in and if you just roll this out, you're gonna fail,
Jordan Wilson [00:24:41]:
Period. That's why 83% say this is the highest priority, but only 4% have successfully implemented generative AI Throughout your organization. Alright.
Jordan Wilson [00:24:53]:
Let's talk about how and why you need to do step 2, which is creating straightforward Guidelines with guardrails. Alright. So creating AI policies and responsible use guidelines is probably one of the most important steps, but like we said,
Jordan Wilson [00:25:07]:
you don't Start there. And I get it. It's going to seem
Jordan Wilson [00:25:12]:
daunting. Right? Because you think, here is this brand new technology that hardly anyone in the organization even understands. So now we have to create guidelines and guardrails. But guess what? You probably already have a lot of that in place. Here's a mistake that people make when they're trying to create Generative AI guidelines and guardrails. Well, see what you already have in place, y'all. K. Because probably somewhere in your current employee guidelines, In your HR docs, in your hardware, software, email, Internet usage policy, etcetera, you probably already have some basics
Jordan Wilson [00:25:52]:
of how employees should and shouldn't be working with technology. Alright?
Jordan Wilson [00:25:57]:
So if you combine What you already have in place for different, technology, software, Internet, email, If you combine that with insights you gather from step 1 in your ground up committee and borrowing from best practices, like I said, from the EU AI Act, The Hiroshima AI process, the White House executive order on AI, the White House select committee on AI. When you start to combine those, Combine what you already have with what we talked about in step 1, with the insights that you've gained
Jordan Wilson [00:26:28]:
from, bringing in ground up employees.
Jordan Wilson [00:26:34]:
It's not as daunting then.
Jordan Wilson [00:26:36]:
Alright. So The guidelines make sense, but let's talk
Jordan Wilson [00:26:41]:
a little bit about guardrails. First of all, why do
Jordan Wilson [00:26:46]:
you need guardrails? Well, number 1, it's a great business decision. You know? And that's something that can't be overlooked here. All of these steps, They need to work hand in hand with your business goals. And setting guardrails is an extremely important business decision. This lets you know this is essentially when you think of guardrails, I think of them and
Jordan Wilson [00:27:13]:
Quite literally. Right? That's why they're called guardrails. Okay? Think. You you now, Think of it like this. You're whether it's a 100 or a 100,000 employees are going to be driving, but they're gonna be driving new vehicles that they've never used before. They don't know anything about it on a new type of road that they've never driven before. You don't have guardrails. You can imagine there's gonna be a lot of accidents, a lot of cars driving off the cliffs, a lot of insurance claims.
Jordan Wilson [00:27:43]:
Right? You get it. Guardrails are extremely important. That says, here's what's inbounds, here's what's out of bounds. And putting different safety measures in place. Right. We have to have
Jordan Wilson [00:28:00]:
data security, data protection, And
Jordan Wilson [00:28:05]:
we also have to act ethically. Alright. So number 1, guardrails are essentially a required business decision Because this is the new way that your company is gonna be working. Alright. And sometimes, what this means when we talk about that your Guidelines and and guardrails for generative AI. They need to work hand in hand with your business strategy. And sometimes and you're not gonna like this. You're not gonna like this, especially if you're, you know, chief marketing officer or, you know, if you're in growth for your company.
Jordan Wilson [00:28:39]:
Sometimes you have to scale back or adjust your actual business strategy or your KPIs or your intended business outcomes To better align with a generative AI policy. Alright. So it might seem like you are taking a step back, but you are Taking a literal step back with your feet in order to get on a jet.
Jordan Wilson [00:29:07]:
So you have to understand that. It might take 1 physical step backwards or a couple of realigning your actual business goals, your intended business outcomes in order to get the most out
Jordan Wilson [00:29:21]:
of generative AI. Right? Because everyone's talking. Oh, like the McKinsey study. How can we use AI to save employees 70% of their time? Right? That's a conservative estimate, by the way, as well. I've talked about I think it's actually 80 to 85% depending on your role. It's significant savings, so you might have to adjust your line of business a little bit. That might be uncomfortable for you, But you need your guidelines and guardrails to align with your business objectives. If they're going in different directions.
Jordan Wilson [00:29:56]:
Jordan Wilson [00:29:57]:
The old saying, one degree of misdirection after a while. Those 2 things aren't gonna know each other. They're gonna be 1,000 of miles apart. You have to align them closely. Alright. Another important thing when we're talking about creating straightforward guidelines and guardrails is making ethical decisions. Okay?
Jordan Wilson [00:30:25]:
Jordan Wilson [00:30:28]:
That's not just the the big picture of like, okay. What happens when we Start to replace employees. We're gonna talk about that in step 5. But, also, you
Jordan Wilson [00:30:40]:
need to act in a responsible and ethical way with your data. Right? One of the biggest hang ups with people in using large language models is data. You need to exercise caution with sensitive data And reflect that in your guidelines and guardrails. However, most people don't understand this. Give me give me your company. I guarantee you I will find more data on your company than you think is publicly available. Scrapers let me say this. Scrapers are better at finding information than humans.
Jordan Wilson [00:31:19]:
K. There's a great chance that whether we're talking about OpenAI's GPT bot or Perplexity's Perplexity bot Or Googlebot or whatever. All of these large language models, they've crawled every single page on your site. And there's probably dozens or hundreds or thousands of pages on your website that you maybe didn't know existed with a lot of data out there about your company. So this isn't 1 size fits all when it comes to data, but here's the thing. You probably have, especially if you're a large enterprise company, you have to release so much data about your company anyways. K. So a big part of this, and I can't just give you 1 bullet point of advice on what is the best guardrails To put in place for your company because it depends on what sector that you're you're operating in.
Jordan Wilson [00:32:11]:
It depends on different laws and regulations. It depends on if you're working with PII, PHI. Right? So So there's no one size fits all here, but I will tell you this. Your data is probably a lot more public than you think. Alright. So, again, I can't give you bullet point recommendations on what should be in your guardrail, but I will. Like I did with step number 1, is see the great resources that are already out there, that are great guidelines and guardrails already in place. So Already mentioned, you know, a couple multiple times, the EU AI Act, the Hiroshima AI process, the White House executive order.
Jordan Wilson [00:32:49]:
But Another great one specifically for guidelines and guardrails is, UNESCO's recommendation on the ethics of AI And also the National Institute of Standards and Technology. They have great guidelines, and they talk openly about and Different guardrails organizations should have in place when it comes to implementing generative AI. Tara says amen on a Wednesday. Saying let's put up guardrails. Comment coming in here. But don't forget to sprinkle in some rewards for those who stay on track. Yes. You have to stay on track.
Jordan Wilson [00:33:26]:
You absolutely have to. Alright. Speaking of, I should stay on track and
Jordan Wilson [00:33:31]:
Talk about step 3 here. Right? Alright. Let's get to step 3.
Jordan Wilson [00:33:37]:
Sprint toward your 1st measurable AI project. K. And here's the thing. Number 3 and number 4 could be interchangeable. It depends on your company. Right? So number 4 is invest heavily in education and training that align with long term business goals. But step 3, sprint toward your 1st measurable AI project. I think for most companies, this will be first.
Jordan Wilson [00:34:01]:
Another big mistake that I think companies are making Is they're trying to make a splash when it comes to
Jordan Wilson [00:34:07]:
generative AI. Let me tell you this. 99% of companies Do not need their own large language model. I am baffled by the amount of smart people that I talk to. And, you know, ask them like, oh, hey. What's your company doing?
Jordan Wilson [00:34:25]:
And they're like, well, you know, we're trying to, you know, create our own large language model. I don't know if that's Because it's like, oh, it's the cool, sexy thing to do, but, like, you probably do not need that. Right? So many smart business leaders are overcomplicating what generative AI even is and what it can do for their companies. Right? People just see OpenAI. Right? And they see, you know, Google Bard, and they see they they they see anthropic. And they think, well, yeah, we should have our own large language model. That makes sense. And there's obviously people out there Hounding big companies and saying, you need this.
Jordan Wilson [00:35:06]:
You need this. Well, I'm letting you know you probably don't. Like I said, 99% of the time, you do not need your own large language model. Right. You should be working with whatever model makes the most sense for you and then using RAG, Which is retrieval augmented generation. That's bringing your own data in, your own knowledge base, your own company documents In a way that is much more economical and obviously much more likely to be deployed in less than 50 years. Right? Good luck. If, Again, for the 99% of companies that it doesn't make sense, good luck creating your own large language model.
Jordan Wilson [00:35:43]:
It's not gonna work. It's incredibly expensive. You're not gonna be able to find the the the actual developers who are smart enough. I talk about it all the time. This is like Finding a
Jordan Wilson [00:35:54]:
a a good developer right now in in AI, specifically in generative AI. It's like, You know, the bowls of the nineties. There's so few of them. Good luck. Alright. So let's talk about why you Sprint toward
Jordan Wilson [00:36:08]:
a 1st measurable AI project and not taking on some unrealistic, huge, generative AI implementation. Well, sometimes before you even get to training and education, you need to focus on quick and measurable wins. Why? Well, focusing on a long term large scale project is risky. It might not even work. You might not even know what you're doing. You know? And you'll probably have to do back flips just to get stakeholder buy in to do something on a large scale. It's risky. Alright? So to get company wide implementation, don't do that.
Jordan Wilson [00:36:46]:
You need a low hanging fruit w. You gotta get the easy win. You need to not only be able to get an easy win, but you need to be able to say, to tell the story of it. Right. To simplify what generative AI AI is and what it can do across your organization. You need to be able to say, hey. Look at this generative AI thing. Look at how it helped us win and
Jordan Wilson [00:37:09]:
then tell the story. And that's how you get stakeholder
Jordan Wilson [00:37:13]:
buy in for that large project. That large company wide implementation. That's how you do it. You don't start there. Sorry. I think I'm still getting because I worked on this a lot on Tuesday, I'm getting some hot take Tuesday takes in in my head, but that's, yeah, that's a recipe for disaster.
Jordan Wilson [00:37:32]:
Don't do it that way. It's not the right way to do it. Smart people say that's the right it's not the right way to do it. Use common sense. No one understands generative AI technology.
Jordan Wilson [00:37:45]:
No one. You know? There's a reason why there explainability and black box is is such a big thing right now in generative AI. So when you sprint toward your 1st small measurable AI project, you need to only focus on areas with a measurable impact. You need to be able to translate that one sprint and tell the story of real world results. Time saved, money saved, etcetera. Project timelines moved. Customer success went up by by this percent. You need to have one very specific win that is quantifiable and that you can tell the story.
Jordan Wilson [00:38:26]:
And don't focus on 1 tool. Don't even focus on a main business goal. Don't do it that way. That's backwards. Find the most quantifiable lowest hanging win. Go after that. Focus on one outcome that is also transferable across departments or locations of your org. If you're only speaking your your language, let's say you're in sales, And you do something that is so niche for sales, but it's a low hanging fruit.
Jordan Wilson [00:38:51]:
And then you go try and tell that story, people are gonna be like, alright. Well, that doesn't matter. That's not applicable to our other 15 departments within our organization. Focus on winning back time in a manual, mundane knowledge work area that's transferable. Maybe even something that no one likes or is incredibly time consuming. 1 or a couple examples I always like to give. Document creation, microlearning, data analysis. Right? Those are 3 areas that are extremely transferable from department to department.
Jordan Wilson [00:39:29]:
And Easy wins that you can then replicate and save time, save money across the organization. Right? Document creation, microlearning, and data analysis. It's also an easy way to use public data. Alright. So you don't even have to jump through 50 hoops and, you know, Get some complicated, implementation technique. You can use public data, in that case, to win back time, To show that 1st sprint to show the win.
Jordan Wilson [00:40:01]:
Alright. Also, one last thing
Jordan Wilson [00:40:04]:
to think about. In going about it this way and going about it as sprinting toward your 1st small measurable AI project versus a large scale AI implementation is you're also minimizing the AI risk. Right? That's the thing that always causes holdup with stakeholders Is they don't understand the risk for a technology that so few people can understand. Minimize
Jordan Wilson [00:40:29]:
the risk. Make it short. Make a sprint. Tell the story. Go do it. That's the blueprint. Step 4. We're getting there, y'all.
Jordan Wilson [00:40:45]:
We're getting there. Alright.
Jordan Wilson [00:40:49]:
Tara says bring it. Tara's still with us. What are y'all thinking? What's been helpful so far? Let me know. Let's talk about 4. We're gonna go fast here because this one is obviously huge. Right? And, again, step 3 and step 4 could be interchangeable. And these even these, The order of the steps and these exact steps, I understand these are not going to be applicable to every single techno to every single company. I'm talking to the middle of the road company.
Jordan Wilson [00:41:15]:
Alright. But again, number 3 and number 4 can be interchangeable. But here's why You have to invest. Step 4, invest heavily in education and training that align with long term business goals. And this step 4 is an ongoing iterative process. Alright. It is cyclical. You are constantly doing step 4.
Jordan Wilson [00:41:36]:
K? Because this is now where you take the learnings From your short sprint, and you start to implement longer term goals and create training and education ongoing around them. And this is another reason why long term projects don't work. Right? You're gonna be talking about this for 2 quarters, and then you're gonna have a, You know, a year long pilot?
Jordan Wilson [00:41:59]:
No. The technology that you're talking about during the planning phase is gonna be antiquated By the time the 1 year pilot's over, you're wrong. It's not how you do it. Alright. So step 4, You actually proper
Jordan Wilson [00:42:17]:
this is crazy. Proper AI implementation, it actually requires unlearning decades of positive business habits. That one's worth repeating. Proper AI implementation requires unlearning decades of positive business habits. We're working in a new way. Alright. And, yeah, I did do, like, 40 minutes on this yesterday. So I'm gonna go I'm gonna go through quicker here.
Jordan Wilson [00:42:40]:
So before implementing any generative AI tool, you need to first deeply understand how it operates. Education is so important. And emphasize explainability across the board.
Jordan Wilson [00:42:51]:
Alright. So if you're not super technical, explainability is such a huge thing in generative AI. Let me illustrate what that means.
Jordan Wilson [00:43:00]:
Think of generative AI as a box. Alright? You put things into the box. There's inputs. And let's just say those are prompts. Right? Some might be a text prompt or an image or speech. Right? So you have all these text and speech model, photo to video, video to whatever. Right? But everything goes into a black box. That is the generative AI model.
Jordan Wilson [00:43:24]:
Okay. So explain a bill so everything goes in. And then on the back end, it magically turns into something 10, Fifty times more impactful. Right? That's what generative AI is. You put in something, You know, a couple bullet points and out comes a 50 page market plan with photos, videos, and voice overs, right, as an example. All of that happens in a black box. That is the concept of explainability. Because most people Have a lack of trust and understanding both in generative AI technologies, but also They don't trust the outputs because they don't understand the magic that's happening inside of that black box.
Jordan Wilson [00:44:09]:
That goes to explainability. K. So you need people in your org that can demystify the black box. You need to be able to explain what is actually going on With whatever generative AI or large language model tool that you're actually using, you need to break it down in an elementary way. Right? That's literally what we do in our free and Prime prompt polish PPP course. We go into explainability. We say this is how large language models work. They don't work.
Jordan Wilson [00:44:36]:
How you think they work? Right? Because the more that you understand something and the more that you educate and train yourself on what's happening inside of that black box, the more trust That is then within your organization, which means more people are getting on board, which means you're gonna have better and more usable outputs. Because the more that you understand, the more explainability there is, the better the outcomes are, the fewer hallucinations there are. Right.
Jordan Wilson [00:45:08]:
So here's another thing. After you can demystify the black box, You really need to emphasize training. K? So I tell people this, call
Jordan Wilson [00:45:17]:
in your vendors. They're busy right now, and, unfortunately, not even all of, You know, these large tech trillionaire companies are training all of their employees top to bottom, but what up whatever vendor that you're using You know, whether you're using Microsoft Copilot or, you know, any suite of Google's AI products or AWS Or, you know, q from Amazon, Azure, Salesforce, etcetera. Whatever product or vendor that you are using for your generated AI, you need to call on them for education. You need to take whatever. You know, most of them have pretty good free courses. I shared a lot of those in our newsletter yesterday, but you need to call on those vendors. You also should be bringing in outside experts that can explain one specific thing. Don't if if if you don't understand a certain aspect, you need to invest heavily in the education and training.
Jordan Wilson [00:46:10]:
Think. If you can actually save 70% of your employees' time, right, you should either appoint people In your organization to then carry the torch forward, and you need to bring in outside consultants, outside experts To train those people. Right? That's one of the things that we do at everyday AI is we we help people. Right? People, you know, hire us to Help them demystify chat g p t or help them learn other generative AI systems. You should be doing that as well. So what's the best way to do these things? What's the best way to properly, both invest in training, in education, but to also give your employees a safe way to do this? Right. Think of that, that that picture that we painted earlier. A brand new road, a brand new car, no one knows what they're doing.
Jordan Wilson [00:47:00]:
You need to give them Set up a playground in a safe place for employees to learn. Right? So literally as an example, you talk of OpenAI, OpenAI has a playground. It's a sandbox. Right. You can go in there and try different models and break things. Right? You should be doing that. You know, had a great, Great conversation with someone from Walmart a couple of months ago, and they talked about they have an entire custom playground for their Walmart's corporate employees to play with different generative AI tools. Alright.
Jordan Wilson [00:47:30]:
It's probably the best way to experiment isn't something that ultimately impacts a live product, a live service, a live offering. Need to have a place to practice first. Just like if you're building a new, you know, NBA team as an example, you You gotta do a lot of practicing first. You know? Just throw them out there
Jordan Wilson [00:47:47]:
on the court. They're gonna lose. They're gonna get embarrassed. Alright. And added tip here. Ready? Your AI abilities aren't just determined by your AI knowledge Because
Jordan Wilson [00:48:01]:
when we're talking about education and training, I want you to take a step back, and I want you to think That doesn't mean you have to become a tech person, a code person. It doesn't mean you need to become a machine learning, deep learning expert. No. Because when we're talking about generative AI, again, it's simple prompts going into this black box with great outputs coming out of it. You know what? One of the biggest Skills in skills is if you want to, train your employees, old school skills,
Jordan Wilson [00:48:33]:
Speaking, listening, typing, problem solving,
Jordan Wilson [00:48:41]:
Clear communication. Right? I see a huge resurgence in 2024 of going old school. Do you know what prompt engineering is y'all? Like, prompt engineers are out there getting paid, you know, professional athlete salaries.
Jordan Wilson [00:48:56]:
But, essentially, it's people who can communicate clearly with a large language model. It's not as technical As you
Jordan Wilson [00:49:03]:
might think, if we're talking about basic generative AI models that we can all use right now. You need specificity and clarity in your language. You need to be able to ask questions. One of the reasons why I think, personally, I get great results out of, You know, large language models and other generative AI systems is my background as a journalist.
Jordan Wilson [00:49:26]:
When I focus, I can ask very clear Questions. Right? I can go back and forth with a large language model. That's what you need to be doing.
Jordan Wilson [00:49:39]:
Alright. So you also last tidbit here on number 4, and then we're gonna wrap this up with number 5. You need to be able to explain AI project Implycations implications company wide before deploying them. That's another part of education and training. Alright. After you get your 1st big win, part of step 4, it's an iterative ongoing process. It's where you are also Integrating whatever your next big picture or medium picture AI implementation is, you need to be able to explain that company wide, but also train everyone on that company wide. So it's not just training on a skill set or on a specific tool.
Jordan Wilson [00:50:18]:
It is training on the big picture. It is reinstituting a new way that your company, your organization is gonna work. Alright. Hey. Nancy says more voice in 2024. Yeah. More clarity in your communication for sure. Love this, Liz.
Jordan Wilson [00:50:36]:
Liz says, embrace a culture of learning AI, gen AI. Yes. You need to have culture of learning. That's why we did an entire episode yesterday on education. Alright. Here we go. We're gonna wrap this up. Step 5, You need a plan for a future of what happens when AI works.
Jordan Wilson [00:50:55]:
So we reference this in step 1. Because in step 1, when you are having that ground up, right, that ground up committee to gather insights with your company, You need to say why we are doing this, but also what happens when it works. So you need
Jordan Wilson [00:51:12]:
to plan for this future. Right.
Jordan Wilson [00:51:16]:
And there's probably when you ask why you're using AI, you know, it's Filled with buzzwords. Right? Oh, we wanna increase automation, reduce overhead, doing more with less, etcetera. Right? So okay. It's probably going to work. If you go through this the right way, if you follow steps 1 through 4 closely. It's probably gonna work. So what happens then? What happens? No one wants to talk about this. I talk about this pretty openly.
Jordan Wilson [00:51:48]:
AI is going to replace more jobs than it will create. Alright. I'm not gonna end this on a sour note, but you need to have these conversations in step 1. But part of step 5 Is you need to plan and work toward that future of what happens when AI works. Right? You need to have a plan in place. As an example, let's look at that 70% statistic again from McKinsey that says generative AI May automate work activities that absorb up to 70% of employees' time. So as an example, if you have a 100 people in sales, Are you gonna lay 70 of them off? I don't know. You have to have that conversation.
Jordan Wilson [00:52:37]:
Are you gonna free up some of the more mundane tasks and have your salespeople work on something more meaningful To work on more, you know, more kind of on customer service, customer experience. That's a question you have to have. That's a conversation you have to have. What happens when AI works?
Jordan Wilson [00:52:56]:
Are you just gonna downsize? You're a public company? Are you just gonna focus on shareholders?
Jordan Wilson [00:53:05]:
You need to be transparent about it from the beginning. That's why it starts in step 1, and we're wrapping it up with step 5. Your goals of AI need to be transparent.
Jordan Wilson [00:53:15]:
Are you gonna move to a 4 day work week. As crazy as this as crazy as this sounds, literally. I'll I'll I'll find the study. I read it the other day that AI companies,
Jordan Wilson [00:53:30]:
you know, AI powered or AI first companies, Have already started to implement a 4 day work week. Paying their company you know, paying their employees the same. We're not paying them 80% of their pay. They're saying, hey. AI has been great for us. We're going to a 4 day work week.
Jordan Wilson [00:53:48]:
Is that something you're gonna do? Are you gonna create new roles? Are you gonna create new divisions in your company? Is your company gonna take on new lines of businesses? A business after AI works. How are you gonna get more human contact In all steps of your business, whether you're a product business, a service business, etcetera. One of the downsides of proper Gen AI implementation Is automation. Right? It saves time, but it also takes away a lot of that human contact. How are you gonna combat that?
Jordan Wilson [00:54:25]:
How are you gonna keep a happy and productive workforce of passionate people who feel purpose in their work after AI works. I don't have the answers. Right? Because that looks different across different organizations, across different companies, across different parts of the world.
Jordan Wilson [00:54:45]:
But you need to plan for that. You need to
Jordan Wilson [00:54:48]:
plan for that, and that is where ethical AI implementation comes into place. When we talk about ethical AI implementation. It doesn't just mean data and guardrails, etcetera. It means you have to also be ethically, Like acting ethically toward the humans that have made your company what it is today. Need to envision and work toward A hybrid approach. Right? Humans and generative AI systems working hand in hand, not against each other. But you also need to say, what is that more meaningful work? If we can get rid of the moan the the mundane, what is the most meaningful work? Something I always suggest people to to ask a question or to have a discussion around, and this is probably something to talk about in step 1 when you're gathering insights from a ground up committee, Is hey. Asking everyone in the organization, what would you do if there is 2 of you? Not, hey.
Jordan Wilson [00:55:43]:
I would do more of this. What would you do differently? That's what proper Gen AI implementation is. Right? The potential to free up 70% of your time. What would you do differently? What would you do more of if there were 2 of you that you can't do now?
Jordan Wilson [00:55:59]:
You need to plan for that future of what happens when AI works.
Jordan Wilson [00:56:07]:
Alright. Let's recap y'all. If you do have a question, get it in quick because I'm gonna wrap this one up. Alright. So here's the 5 simple steps to start using Gen AI in your business Today. Ready? Step 1, gather insights from a ground up committee. Step 2, create straightforward guidelines with guardrails. Step 3, sprint toward your 1st small measurable AI project.
Jordan Wilson [00:56:33]:
Step 4, invest heavily in education and training that align with long term business goals. And step 5, plan for a future of what happens when AI works. Alright. Like I said y'all, I had I don't even know how many pages of notes, but the majority of content that I put together that I spent Hours going through dozens of episodes. I have so many notes. Right? So if you want access to all of this, If this was helpful, people always ask all the time. Hey, Jordan. Everyday AI helped me get a promotion.
Jordan Wilson [00:57:10]:
Now I'm head of AI. What can I do to help? Share this with people. Share this episode with people. There's so much bad information out there. That's literally why I started Everyday AI. People think that Generative AI is just using prompts. It's not. This is step by step blueprint to revolutionize and transform the way that companies work.
Jordan Wilson [00:57:35]:
So please, if this was helpful, Please repost this. You know, if you're listening on LinkedIn or, you know, if you can go find this, on on our Twitter account, repost this. Let me know you reposted it, and I'll share all our notes. It's a lot. You might look at it and
Jordan Wilson [00:57:50]:
be like, oh my gosh, Jordan. This is more than I bargained for. Alright. So, couple couple quick questions that I think I saw here.
Jordan Wilson [00:57:58]:
I might be missing some, and sometimes our, The stream doesn't show everything, but, Mauricio, thoughts on an internal chief AI officer versus hiring a consultant firm to implement the strategy. The answer is yes. You should be doing both. Right? This obviously depends on the company, company size, etcetera. But I firmly believe that you need to the same way that I say a ground up approach when you are starting with step 1 of gathering insights. You shouldn't just be gathering insights from everyone internally, every department, Every layer of your organizational chart internally, but you should be leveraging people from the outside as well. Because here's the thing. So many times internally, you have a mindset of just doing things the way they've always been done.
Jordan Wilson [00:58:46]:
You should be hiring someone externally to poke holes and to help guide you. Right. Something we do for companies. You can always reach out to us, and we can let you know what that looks like. But, to answer the question, Mauricio, both. Rolando says, I would think that in step 5, companies need to think about the impact of successful Gen AI with their customers. And how do you communicate that? Yes. Absolutely.
Jordan Wilson [00:59:10]:
Absolutely. I agree. You know, the hope is that as you free up some of this more manual mundane time, of your employees that ultimately leads to better customer experience. Right? We talked about that and also measuring. Right. How you can get to a, a small measurable AI project. Sometimes it's time. Sometimes it's money.
Jordan Wilson [00:59:33]:
Sometimes it's increased Customer service scores. Right? Yes. You cannot lose fact of the human. Everything should be a hybrid approach, whether it's Your own humans internally in your company or the humans who are ultimately buying your product or service. When you free up time, You need to focus more on ways that you can engage with those humans and better serve them. Alright. I think there was 1 more question here. So, again, from Mauricio saying, are there tangible case studies for different departments of what AI solutions tools to implement and return on investment for this.
Jordan Wilson [01:00:11]:
Are there not, not across many different verticals. So, yeah, there are great studies, and we shared a lot of them yesterday. In our newsletter, there's great studies out there about, like, oh, in HR or, oh, in sales. And I'll try to pull a couple more for today as well. Alright. But That is it y'all. I hope you enjoyed this episode on the 5 simple steps to start using Gen AI in your business today. Like I talked about, This is one we've technically been planning this for months.
Jordan Wilson [01:00:42]:
This is the culmination of con hundreds of hours of of conversations with with experts building generative AI technology, with with, you know, leaders in the generative AI space through hundreds of hours of us teaching Thousands of others of of other people how to leverage generative AI. This is a blueprint. Alright? I want you to use this. That's the point. That's why we put in so much work here at Everyday AI. We want to Cut through the smoke and mirrors that are out there elsewhere in the generative AI space. We want to simplify this, And we want to be the resource that helps your that helps you leverage generative AI to grow your company and to grow your career. Alright.
Jordan Wilson [01:01:28]:
This newsletter is 1 you're gonna wanna sign up for, so make sure to go to your everyday ai.com. Sign up for that free daily newsletter. If you're listening on the podcast, all that information is in the show notes as well. We're gonna break down this newsletter and a lot more. So make sure to join us tomorrow. We're gonna be talking about MidJourney v six with Rory Flynn, which someone dubbed the bash one of the bash brothers of of mid journey, as well as Friday, maximizing the effectiveness of AI in health care, with, the president of the American Medical Association. So that's it. I appreciate y'all.
Jordan Wilson [01:02:00]:
Go to your everyday ai.com for more, but I hope You can now understand your blueprint forward to grow your company, to grow your career with generative AI with these 5 simple steps. Thanks y'all.