306 The Executive Playbook for Mastering Generative AI: A Guide to Transforming Performance by Leveraging Cutting-Edge Capabilities with Jordan Wilson, Founder of Everyday AI | Partnering Leadership Global Thought Leader

[00:00:00] Mahan Tavakoli: Jordan Wilson, welcome to Partnering  Leadership. I'm thrilled to have you in this conversation with me. 

[00:00:05] Jordan Wilson: Thank you so much for having me. I appreciate this. Excited to talk.

[00:00:09] Mahan Tavakoli: Jordan. I'm excited. I've been learning so much from you and your everyday AI podcast and your newsletter, so can't wait to get some of your thoughts and insights on where AI is headed, most specifically how executives can apply AI in their workflows.

But before we get to that, we'd love to know whereabouts you grew up and how your upbringing impacted who you've become Jordan. 

[00:00:32] Jordan Wilson: Yeah, fantastic question. So I grew up in a small little town called Freeport, Illinois. So it's about two hours west of where I now reside in Chicago. And my background, I'd say, was very interesting.

So I started working as a full time journalist while I was still in high school. So at age 17, I was literally working. 37 and a half hours a week, whatever it was back then writing for my daily newspaper in the town where I grew up. And that kind of led me to, at the time, pursue a career in journalism.

So I really was a multimedia journalist for about seven or eight years. Most recently at the Chicago Sun Times. I did fairly well. I accomplished what I set out to accomplish. I won ACP story of the year. I was a Pulitzer fellow. So at that point I was like frustrated with how newspapers were a little slow to adapt to technology. I've always been a tech geek my whole life. 

So I launched into a new career which started out in non-profit marketing which eventually led into leadership at this non-profit. But the organization we eventually just became an activation agency for Nike and Jordan brand so I spent about 10 years and the majority of my job was really just working on these very large, highly visible community engagements with Nike and Jordan brand.

And after that, doing that for about 10 years, that kind of led me to start my own agency. And from there, created a kind of our AI media company called Everyday AI. 

[00:02:01] Mahan Tavakoli: That's fascinating that you've had such an award winning and successful career as a journalist, and then in nonprofit as well, ending up with AI. 

So we'd love to get your thoughts and perspectives. Number one, why have you gone into it? And what do you see as the implications of AI on organizations in general? 

[00:02:24] Jordan Wilson: Yeah, that's a fantastic question. I actually have to rewind five years or more to answer that question. My main company is called Accelerant Agency.

So we're a digital strategy company based here in Chicago. So even when I was writing my business plan in 2017 I wrote down that I was really only going to be investing on the traditional, digital strategy and marketing side for maybe five years. Because I felt at the time that something was going to significantly change in the marketing and advertising world. 

I wasn't sure but I literally wrote that in my business plan and probably about 2020 which is when we started on the agency side, using a lot of different tools that had AI in them specifically I think it was late 2020 or early 2021 we started using the GPT technology. Everyone knows chat GPT, which came out in November of 2022, but most people don't realize that about two years before that, their technology at that time, it was GPT3, was available in a lot of other platforms. 

As soon as our team started using that pretty routinely for ourselves and clients, I said, Hey, when I wrote my business plan years ago, and I saw that there was going to be some sort of seismic shift happening in the world, I knew at that point, that was it. So over the course of the last like year and a half, we've been dialing things back on the agency side as we've started to invest.

On the AI media company side, the podcast, the newsletter, and, getting into doing some strategic consulting for companies as well.

[00:03:53] Mahan Tavakoli: I think that's really smart and I truly believe that this is transformative technology.

Now, one of the things I enjoy about your podcast and the way you approach it is that you have a very practical perspective on AI application for executives. So I want to get some of your thoughts around generative AI.

First of all, what is generative AI and how can executives think about using it in their workflows?

[00:04:21] Jordan Wilson: Yeah. It's important to first even know the definition, right? Because artificial intelligence is not new, it's been used in many different sectors and industries in the U.S. for decades, even going back to the 60s and 70s. 

So artificial intelligence is not new. Generative AI, or at least the definition of what constitutes Generative AI is a little newer. So the simplest way to describe what Generative AI is the ability to input a prompt that generates something else on the backends.

I mentioned chat GPT, that primarily is a text input, text output, it can obviously do other things with inputs and outputs, but that's what it's primarily known as. And then you have other platforms or programs such as Mid Journey, as an example. That's a Generative AI system where you input a text and on the output, there is photos. And then you also have a lot of newer Generative AI systems that are multimodal and that's the future of Generative AI and large language models as well. As an example, Google's newest updates to Bard allow you to input multiple things, photos, text, even your speech, and it can output in those formats as well.

So that's what Generative AI is in its simplest form is when artificial intelligence takes simple prompt inputs in various formats and then creates something that wasn't there before based on machine learning, deep learning, all of those things. So with that in mind, with kind of a definition so to speak of what Generative AI is, how can executives use it?

I could talk for many hours on that. But I would say this, like the best piece of advice that I can give to an executive, is don't listen to me. Don't listen to you. Don't listen to anyone because you have people saying oh, do this, do that. Don't. Like the only thing that you need to do is understand where your team is spending the most manual time, because it's so easy to just try to emulate what someone else is doing. You get this shiny feature syndrome and you're trying to chase around all these new tools and techniques. Don't do that. That's the worst thing you can do because as soon as you do that, as soon as you go down the tool route, there's going to be a newer, shinier tool. 

And you're going to get distracted. My best piece of advice , in this case, an executive, maybe 10 people on their team is to start to systematically break down the type of work that they do in categories. 

So are you spending most of your time on meetings? Are you spending your time reading and researching? Are you spending your time creating? It's really first measuring and categorizing where your team is spending the most manual. time, because that's where you can start to then find the correct solution that can provide a quantifiable return within that generative AI system.

[00:07:03] Mahan Tavakoli: What an outstanding perspective Jordan, because the people that I've seen that have been frustrated with their use of Generative AI in most instances, it has been cases where people have looked at it, as you said, as a tool, and it can just become an addition to what it is they're doing, rather than focusing on the business issues they're having, business processes, and then incorporating Generative AI to facilitate that process. 

So in looking at the business, what are the places where Generative AI can have the easiest wins or gets the most potential traction when an executive is looking at the workflow for themselves or their team? What are the first places you typically tell people to start looking for use of generative AI?

[00:07:53] Jordan Wilson: So there is no one size fits all in Generative AI implementation. But I'd say for the most part, if you're a knowledge worker, so that's those of us that, sit in front of a desk, quote unquote 9 to 5 or 9 to 9, if you have a work problem, one of the easiest wins, in my opinion, is in learning. I think Generative AI is going to change how we learn, because I'd say, regardless of what industry that you are in, you are constantly needing to learn new things because how we do business is changing, 

It's changing because of technology. It's changing because of even how we work. We work in hybrid and remote scenarios now where pre-pandemic. We really didn't do that. So it's really looking at those specific areas of work. I'd say some of the lowest hanging fruit is learning new things.

As an example, you can go inside of chat GPT and enable different plugins. And, maybe you always spend, let's just say, three to five hours a week learning a new subject, maybe you're in sales and you need to sell something. And it's an industry or the person that you're selling to is changing all the time.

So maybe you're always reading white papers, demographic reports, emails, from a company that helps advise you on your target demographic. Being able to cut through the fluff with something like ChatGPT with plugins and to be able to insert a link PDF in there and being able to do some basic training within a chat inside ChatGPT to train it.

Hey, here's what I care about. Here's who I am. Here's what my company does in this chat. Here's the role that you're playing. You should be helping me pull out a B and C out of these long documents. That's one of the fastest ways that I think you can get a positive return on your investment for generative AI is just being able to read through long documents, long web pages.

It's something I even personally do myself because it is so impactful and again, it's one of the fastest ways that you can get your time back. 

[00:09:49] Mahan Tavakoli:  Its applications in learning can be really beneficial and I love the way you put it. There's a level of individual agency in interacting with chat GPT in developing your own learning and learning approach.

Now, I wonder on the flip side of the learning issue, what have you seen as best practices or what do you recommend for executives to think about In learning about use of Generative AI, whether for themselves or for their teams. 

So besides just subscribing to chat GPT+ and playing around with it, are there practices that they should think about in enabling themselves and their teams to more effectively use Generative AI, including using it for learning in their team?

[00:10:34] Jordan Wilson:  That's part of a never ending conversation on Generative AI best practices, right? And even as we speak today, it's changed so much in the last two weeks. Because as an example, now what you see is something very timely is the New York Times is suing OpenAI and Microsoft,   saying that OpenAI's large language model is GPT 4 and GPT 3.5 was trained on data or information that is copywritten by The New York Times. So even when you are talking about what are the best practices to think about? 

How could my team use chat GPT? Or how could my team use Microsoft being copilot? You always have to keep that in mind is where is the data coming from. Even your own internal data, because it's also important to know that even though nothing that you share with a large language model is technically public.

However, it is no longer private because anything that you enter into ChatGPT is technically used to train its models. That's another important thing to keep in mind. It's something that I think businesses are continuing to wrestle with because I think there's this urgency.

Wow. We have to start using Generative AI. We have to start using large language models because all of our competitors are because you see them share these things or come out with these new products or features or services that are clearly leveraging Generative AI. So you feel this rush that you have to do it as well, but you really first have to have governance in order at your company, you have to say, Hey, these types of documents here, these are internal. 

So you should never be uploading sensitive or proprietary documents into any Generative AI system. When you talk about practices and how to use Generative AI, even with learning, it's okay if you want to even take your company's, maybe, internal training documents. Maybe they're very long. Maybe it's PDFs. Maybe it's private video training that you have within an intranet, something like that. You even have to look at that and say, okay what pieces of this are confidential?

What parts are sensitive? What parts are proprietary? Because there might be things that you shouldn't be uploading into a large language model. So governance first and foremost. Has to be on every business executive's mind here in 2024. I mean having that governance in mind I would say there has to be a balance on it.

[00:12:43] Mahan Tavakoli: I remember Jordan when iPhones came out and our company initially didn't allow us to use iPhones. That wasn't approved. We were as executives using it anyway. And the company policy changed when the CEO himself fell in love with the iPhone and got our I.T. system to adjust accordingly. 

Right now, I know, there are companies that have policies of no Generative AI use, including government agencies. But the employees are using it anyway. So that's where the question is, how do you balance having governance, but governance that people are willing to stick to, rather than binary governance that says, don't use any of it until at some date in the future, we decide what to do with it.

[00:13:34] Jordan Wilson: Yeah, it's such a great question. I actually created a term that I'm using now all the time called second computer AI because that's what's happening, like you mentioned it some companies, because they don't maybe fully understand it or they just don't have a way to get proper governance in place.

They're just banning it, which is probably the worst thing you can do because then what's happening, like we just talked about, people are using their own second computer as I call it, or maybe they're putting it on their phone and then they're copying and pasting it, from their phone into an email draft or something like that.

So if you are a decision maker right now, your company and your thought is to ban generative AI, you need to rethink that because your employees, regardless of what you think, if they haven't already been using it for months, they're going to be using it anyways. It is much safer even in the long run to implement a generative AI policy now and adapt it later.

So to get to okay, how can you create a governance policy? Dicks. I'd say don't do it top down. Don't do it top down. Talk to those people in your organization that are already using generative AI, talk to the people that maybe are doing the quote unquote second computer AI and say, okay number one, why are you using it?

Number two, how are you using it? What benefits are you getting out of using it? Because. If business leaders don't already have a generative AI plan, you are going to run into, I'd say, a lot of issues with growing or sustaining your business. Again, that's a very broad statement.

I understand. But regardless, I don't think there's many industries. Where generative AI is not going to make a profound impact. So with governance, it's not top down. You have to involve the people that are actually either already using the generative AI systems or will be using it.

Get feedback from them and get buy-in from them as well. You should be creating a fair, equitable governance system around generative AI, and it is much more likely to stick and not be a one way street. If you get buy-in from people using it every day. 

[00:15:38] Mahan Tavakoli: What a great perspective it's getting input and engagement from the people who are using it. To create some of those boundaries, governance, guardrails, rather than top down, which is an approach that I've seen some organizations try to take and people find ways to circumvent those. So a big challenge that I'm sure you're also seeing Jordan.

In incorporating generative AI in organizations and bringing it in, it's a change management challenge and I find that some of the people who are using it the most are the ones that are most terrified about its potential impact on their jobs. So what are some of your thoughts with respect to the change management that it takes for effective use of generative AI in the team?

[00:16:26] Jordan Wilson: Yeah, I'm usually one who has a cup a little half empty versus half full. I wouldn't say I have a pessimistic viewpoint. I would say it's a realistic viewpoint. I think unfortunately, on the Internet or social media, there's certain kinds of sayings that pick up popularity and business leaders adjust their decision making based on common trains of thought. \

The common train of thought that's been out there for the last year or so is AI won't take your job. Someone using AI will which is patently terrible that is so false. And so misleading that I wish I could just hit delete and just delete that from the entire internet.

Here's why. Is it true? Yes, someone using AI will take your job if you're the one not using ai, but it's not a one-to-one, it is not a one-to-one replacement, because depending on, the type of work that you're doing with a generative AI system, it is anywhere from a two to one to a 20 to one replacement.

You, that is such a. misleading and If I'm being honest, such a disheartening sentiment that people are building up around AI and they say, okay hey, as long as my employees have no generative AI, our department is going to be good or our company is going to be good.

That's not really how it works. And even if you are worried about your own job security and, looking at change management it's really not enough to just, oh, okay. I have chat GPT or, I've used Google's, search generative experience or whatever.

So I'm familiar with AI. I think it really takes re imagining how certain departments or certain companies. Do work or what does work even mean anymore? Because part of the conversation around governance and ethical, haven't even touched on the ethical part of it as well.

But before you implement generative AI at a large scale, you have to have the conversation of. What happens if it works, right? What happens if it works? So many studies, McKinsey had a popular one that said, I believe up to 60 percent of, tasks that most of us do can be supplemented with generative AI or, generative AI systems will be able to do that.

Okay, what happens if 50 to 60 percent of all of your employees work can be managed properly by generative AI systems once you get it. But what do you do then? What new area of business can you focus on? If you're serving humans in the end with a product or service, how can you take some of that gained time or some of that time you went back and provide a more personable and a more human interaction for your end client, for your end users.

Yeah there's a whole lot, but in general. It's going to be disruptive, whether people want to admit it or not. I know no one wants to talk about it. It's the giant elephant that is now bigger than the room, but it is going to be extremely disruptive when it comes to job displacement the economic impact as well.

I think it's going to be much more impactful than most people want to 

[00:19:19] Mahan Tavakoli: talk about, that's why it's important for us as leaders of organizations and executives to Constantly learn and grow I couldn't agree with you more, Jordan. In my understanding and going in depth on AI, I also absolutely dislike that meme of you won't lose your job to AI, you will lose it to someone use using AI.

People who say things like that don't understand that Microsoft now has 80 plus percent of the coding that is done by AI. So yes, there are coders that are using the AI, but a heck of a lot fewer coders that are able to code a lot more. So it is not a one to one. It's not to say We need to only be afraid at the same time.

We can't also be oblivious to the impact that it has, which is why we need to keep reinventing ourselves and learning at a faster pace. So for executives, , how can they stay at. The cutting edge. The treadmill is going faster and faster,

[00:20:31] Jordan Wilson: it's so important because like you mentioned if it's not clearly defined, it does just feel like running on a treadmill that is increasingly going faster and faster. And that's what it will be if you don't have goals and objectives clearly defined

a recommendation that I would make is to have short bursts, so when you're talking about, especially if it's for the first time, if you're implementing generative AI into your business, don't think of like your traditional route when you're adapting to new technologies, you go through RFPs and, you go through Oh, we're going to have a one year.

Trial of this and that. You can't do that. That's not how generative AI implementation works. You need to be able to work in short sprints. You need to say, Hey, we're not going to, go through and, test, 10 different systems over the course of six months.

And then choose one over a three month period and then sign an 18 month engagement you can't do that. You have to find first easy wins find the low hanging fruit on how you can win your time back, then go through a very quick process. And one of the two or three reputable and the keyword there is reputable generative AI services that can help us win time back in those areas.

And you set a goal, something like 30 days. And you say, we're only working on this one Generative A. I. Engagement or this one implementation. Here is the intended output over the course of 30 days. Here's how we're going to train our team on it. Here's how we're going to measure. You have to be able to get quick wins because here's the thing.

Something like Chachapiti might not be for everyone, something like, a text to video, maybe you want to revamp your marketing or your advertising. You're like, Oh, we've never done video. Look at all these great tools like Runway and Pika that now we can create video. Okay.

Doesn't mean you should. So what you need to do. I always say don't try to add new lines of business in your first generative AI implementation. When your time back on where you're spending the most manual time, have a very short period, a way to measure it and go 30 days, go all in, go 30 days. Measure it.

It obviously needs to be something quantifiable, whether that's growing revenue or reducing operating costs. Probably through the measuring factor of employees time, but you need to set very clear defined goals and it needs to be a short span.

[00:22:50] Mahan Tavakoli: I love that perspective.

It's much more of an agile perspective of experimentation rather than going. Fully in with a longer project cycle, which a lot of larger organizations, especially some of the more conservative organizations have been looking at that gets them in trouble. Now, Jordan, you have been in creative business yourself.

You do have the podcast, the newsletter would love to know how is a content creator like you incorporating generative AI and how do you see generative AI used most effectively in that space? 

[00:23:28] Jordan Wilson: Yeah, generative AI in the creative space, it's been around for a very long time.

It's almost like old news, like I said, I think our team, it was either late 2020 or early 2021 that we started using the GPT technology other offerings or other generative AI technologies have been around for a long time, especially around content creation. I would say, if you look at all the different departments within a large organization, I'd say your marketing, advertising, your communications departments are probably the ones.

If you've had no rules, they've already been using generative AI tools for multiple years now. I'll say even some of our examples, like I use chat GPT almost every day to learn about AI, it's something people always ask me as they're like, Oh, Jordan, it seems like you keep up with generative AI.

How do you do all this? I use AI to keep up with AI, like I teach different chats within chat GPT, what I care about. What I don't care about and I have different chats as an example that I built that can take a 50 page PDF maybe a very technical study that it might take me two to three hours and I might You know spend that two or three hours and read it and maybe only comprehend 50 of it but by training a chat within chat gpt as an example, I can go through that in two to three minutes and it'll create a little podcast summary for me.

It'll highlight the main points and it'll tell it to me in a way that I taught it like, Hey, I learned like this. This is how I learned. This is what I care about. This is what I don't care about. And here's the format or the medium that helps me learn best. So that's even a way I'm using generative AI like that.

All the time, like we have a daily live stream and podcast. So we have different generative AI tools that as content creators help us very quickly, take a 20, 30, 40 minute conversation and to be able to create multiple pieces of content around that in different formats. So yeah for content creation, that fruit's already on the ground, 

that's not even low hanging fruit. That's fruit that already fell off the tree a while ago, but It's so easy. And there's so many tools, I think, especially, in 2022, 2023, so many of the generative AI tools were aimed, obviously, at content creators, given that the first kind of quote unquote mainstream generative AI or large language model was ChatGBT, which was mainly, focused on at the time.

Creating content, especially written content. 

[00:25:46] Mahan Tavakoli: One of the things I find Jordan is that when you use generative AI for understanding and learning, as you mentioned, and for content creation, you start seeing the potential applications of it in other parts of the organization as well. Now, , Jordan, you have a lot of great content that you're producing on a daily basis. How can the audience 

[00:26:10] Jordan Wilson: follow your work? Yeah, thanks for that. I appreciate that. The easiest way is just to go to your everyday AI dot com. Like you already mentioned, we put out a free daily newsletter.

We have the podcast, I'll throw out the live stream. I think the live stream is great because a lot of times we bring on guests. We've had people from, big companies like IBM and NVIDIA and Microsoft, but then also people small business owners and entrepreneurs and to be able to as a consumer to be able to listen live and ask questions, 

because that's our format is, we'll take people's questions live. So it's like, where else could talk to a senior director at Microsoft about how to best implement, 365 copilot into your business. I actually think the live stream is super underrated in a great way for people to actually learn and leverage AI because, learning is fine, but it's all about, okay, now that I've learned some things, it's okay, the treadmill is going fast and I keep learning more and more, and there's new things every day.

So it's all about how you make it practical. And actionable as well. That's really what we also focus on in the newsletter is, breaking down the conversation and saying, Hey, here's how to go apply this to grow your business or to grow your career today. That's 

[00:27:21] Mahan Tavakoli: actually what I really appreciate about your content, Jordan. Because it's not AI for AI. And there's a lot of content out there introducing lots of different tools. There are hundreds of new tools that come out every day that can be shiny objects that people can run after what you do through your questioning and through your content.

Is help people understand the business value and application and where it's relevant for them, which is why I really appreciate your content, really appreciate this conversation and all the great work you're doing, Jordan. and thank you so much for sharing some of your thoughts with the partnering leadership community.

[00:27:58] Jordan Wilson: Thank you. I appreciate you having me on.