EP 170: AI Business Strategy - Are you ready for 2024?

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2024 is weeks away and guess what? Your AI strategy is definitely not not ready. So we're going to be talking about that today and more on Everyday AI. This is your daily live stream, podcast and free daily newsletter helping everyday people like you and me not just learn what's going on in the world of generative AI, but how we can all actually use it to grow our companies and to grow our careers. So if you're new here, thanks for joining. I'm extremely excited to talk today about AI business strategy and how business leaders can get ready to for 2024. If you're listening on the podcast, thank you. Always check your show notes. We have related shows, other great resources, access to our free prompting course all there in the show notes if you're joining us live. Thank you as well. I always want to hear from our audience. What are your questions for our guest today, which we're going to be getting to in a minute, about how to best get your business ready to take advantage of everything that AI has to offer while building your business strategy for 2024. All right, before we get to that, as we do every single day, let's do a quick recap of what's going on in the AI news. So Samsung is claiming that its newest chip is far more efficient than Nvidia's. So Samsung and AI company Navir have teamed up and are collaborating to develop a cutting edge semiconductor solution for large scale AI systems. So the company's first solution that they just announced is reportedly eight times more efficient than Nvidia's AI GPUs. And obviously we talk about these GPUs a lot on the Everyday AI show. And I get it. You might not be a dork like me, but whether you want, whether you know it or not, these GPUs that are powering all of these generative AI systems are also powering the American economy whether you realize it or not. All right, next piece of news. There's potential holdups in the White House's AI regulation plans. So US President Joe Biden's plan for regulating AI may face difficulties due to to a lack of resources and concerns about bias and transparency. So the White House executive order that was signed a couple of months ago calls on or it AI calls for new standards for stress testing AI systems, but the agency has been tasked with these settings, which is the NIST lacks the budget and expertise to complete this work independently. So some members of Congress are concerned that, that the NIST will rely heavily on AI expertise from private companies with varied interests. Y', all, I said this right when the executive order came out. I said, this has a lot of bite, no teeth, it's not really going to work. It is largely just, you know, some, some dressing, nothing of substance. All right, last piece of AI news, the big one. We saved the last, like the best for last, I'd say. Mid journey version 6 is out. It is live. It's been out for just a couple of hours. So the very popular AI Image Generating upgraded its system from I believe we were at 5.2 to version 6. So in this new version, which you should definitely check out even if you're not an artist, a photographer, whatever, this is a great generative AI tool that has a wide variety of business applications and use cases. But there's some greater prompt control in V6 and it more accurately follows prompts apparently from some early testing. It's a little better with hands, right early on, some of those hands were always messed up in your AI image generators. Also, it finally handles some input text, just some minor things. That's one thing that Mid Journey has been behind. So if you want, you know, someone holding a sign with words on it, it always jumbled the words. Never got it right. So this new version 6 is the first Mid Journey version that can handle text, minor text. So, you know, probably not going to get fantastic outputs, but you'll probably get usable outputs. And then last but not least, there is a built in, in upscaler. Pretty, pretty fantastic. We're just, just talking pre show with our guest about Magnific. So now that AI Image Upscaler is going to have some competition on their hands from Mid Journey. All right, so that's not what we're here to talk about. We'll talk about Mid Journey some other week. Today we're here to talk about what is your AI business strategy and are you ready for 2024? Because I'm guessing you're probably not. So this isn't just me ranting. We have a great guest here today, so please help me welcome on the show Marcus Bernhardt, the chief consultant at Endeavor Intelligence. Marcus, thank you for joining the Everyday AI show.

Jordan, it's a great pleasure to be here. I'm a regular on the show, just on the listening side, so really cool to be fully part of the conversation.

I love it. I love when we get, you know, even when I hear from, from listeners or viewers for the first time. And people are like, oh, I watch or listen every day. I'm like, that's fantastic. If that's you, let me know. I always like hearing. But, Marcus, tell us a little bit about what your background is. What do you do at Endeavor Intelligence?

So what I do is I support people in their AI strategy. And what does that mean? That means supporting individuals, smaller teams, as well as departments, all the way right through to leadership teams and C Suite, with a special focus mostly on chief talent, chief learning and chief Human Resources officers all around the AI strategy. And the key there being that, yes, it's about the tools as, as is the everyday AI show, but it's also about the humans. It's also about the processes and procedures. And to be, to be ready and to have an AI strategy covers a lot of different points. And it's really interesting work I do there. And then I'm also chief AI strategist over at the Thinking Effect. This is a community of practice, so to speak, that I run together with Michael Vaughn. And it's got over 400 AI tools on there and news about learning. So it's about a. And using it for learning and neuroscience and. Yeah, so that's my role in a nutshell.

I love it. I love it, Marcus. You know, I'm always curious from a consultant, from a business consultant perspective, right, because we've had some consultants on the show before, but this was many, many months ago. What's, what's this in the consulting world? What is kind of the, the pulse on what companies. Are companies proactively seeking out help with AI implementation and strategy? Or is it more from a consultant perspective? You're like, hey, company, you don't have a plan yet. You've got to get going.

It's shifting. I think more and more people, as they're getting ready for 2024 and beyond, are realizing that they need more than a vision and a budget. Some have been leaning in heavily, some have been holding back and wanting to see what others are doing. You know, that's the innovation curve. We're happy to go along with that. But being, being ready does not mean having a vision and a budget in place. It goes far beyond that. It goes into the details of how the process and the procedures are ARR in an organization and how all those parts of the business, internal and external, that we're used to doing, how they change when AI comes in and drastically accelerates, for example, the life cycles that we're used to and the approaches we need so generally lots more coming on the pull side now. We used to push out this information more, but organizations are realizing that they can do with a little bit of help and there's enough of us out there to support organizations in doing so. Yeah.

In your, in your personal experience so far, Marcus, are companies maybe realizing this a little too late? Right. If they're just coming up right now at the end of 2023 and they're like, hey, we should start, you know, strategizing for implementing generative AI into our business, is it too late for them?

That's one of those questions since I'm a regular on the show, Right. And I talk about this generally all the time and have for years. Right. I'm not one of those who joined the craze just over a year ago when ChatGPT came out. I was aware of GPT2 and GPT3 and all those things. So this is, this is a really key question. We tend to think that everyone by now has got to a certain level and is moving along with the flow because we have so many conversations about it. But we're still surprised. Even the fraction of people that have not tried even GPT3 just gone on and doodled for five minutes. And it's especially humbling to see how busy last year leaders have been that have not been on. And we're finding ourselves in a, in a situation here where it doesn't matter whether you're the fresh graduate who's just joined from college or whether you're the 10 year CEO, super successful of the company, you have the same experience with regard to this new changing situation and that is zero. And even if you are ahead of the times right now, remember things are moving quite quickly and we're resetting that to zero every week, every month at the moment. So even if you had a small advantage, if you're not staying on top of it, then you're back to the starting point. But it's not difficult also to keep one up to date and to jump in now. So I would say probably from our perspective, you and me, this is a little bit later to join the gang, but generally it's never a bad time to start the process and many are realizing that they need to start. And even those that have been more cautious have been more worried about the ethics, have said no, we're going to hold back a little bit on this. We don't quite know what's coming. That's all well and good. And then of course there's smaller organizations who can't afford really cool AI enterprise solutions and to just deploy things in smaller workflows, etc. Those are also not late to the table because we can't just make up a budget that isn't there in the first place. Right. But yeah, as I said earlier, as the innovation curve brings us all along with it, more and more will be joining and it's always the right time to start.

You know, one thing, Marcus, that even from myself talking with, you know, business owners and leaders at larger, larger organizations is it seems like when they talk about, you know, AI implementation or their business strategy around AI, they still have this, you know, we'll call it a web 2.0 mindset. It seems like they still have this, you know, standard operating procedure that they go through in order to test and implement a new technology, which sometimes is turtles pace. Right. It is extremely slow. Can organizations keep that same application kind of methodology where they go through these, these, you know, they have panels and internal meetings and they test out different ones and they put out RF. Is that the right way to implement AI?

Well, you mentioned RFPs there, so that's a fantastic example to dive into. Right. We used to, especially in larger organizations, we used to run our RFPs, maybe with six months timeline, checked out a few products, had conversations, saw demos, then brought it all together and decided where we were going to head. Then we bought one of them, signed a contract, two or three year, sometimes it's self renewing. We ran the system for two or three years. Maybe we didn't even review properly after the first run and it took another two or three years for the second run to, to establish itself and we called that business as normal. And then at the end we would review that, see the value we've got out of it, and then maybe go through a new rfp. Well, if that's how you want to approach AI, you're, you're already dead. Sorry, but you're, you're already gone. I call it the three constants that run us alongside. You have to be on RFP mode all the time. You have to at least have an eye on the market. You're running in parallel, your business as usual, because that's your business and you have to look at the value constantly. And with the field changing so rapidly, you're going to need to deploy fast and hard use cases, sign a deal for 10, 12, 14, 16 weeks, run a use case that can offer you whether the value is there that you're seeking, whether it's internal or external. We can always Build a use case that minimizes risk, maximizes return on investment opportunity, whether you're addressing a pain point or looking for new opportunities for your business. And then reiterate. And especially in that process, as you just said, we've got the new mid journey is out. They were loop fragged by Magnific when it comes to certain image qualities. Now they've come back and said, no, here we go. But technologies are coming hard and fast. They're leapfrogging one another. And this system is a little bit more complicated, let's call it chaotic, than taking an organization and rolling out the Office package and then saying to departments, you can all use this, here we go. Some of you might want to dive into Excel a bit more and there might be even be a few weirdos amongst you who will do VBA programming in the background of the Excel sheet. Well, that's all well and good, but you all have the Office package, off you go. And so, and so this is too fast. Things are moving far too fast and there's far too many tools out there to have that kind of an approach. And so that brings it back to a human element. In order to tackle this, we have to have a basic understanding about AI. Generative AI, non generative AI. That's why your show is so good and that's why people should be on it. We have to be able to communicate about the strengths and weaknesses. We have to know what hallucinations are and when they might be a problem and when, when there's probably not a huge risk and those basics need to be covered and then we can have a conversation internally. And you know, I'm not normally a fan of big quotes, but they always say, you know, the, the Steve Jobs quote, at least it's, it's attributed to him. Probably, probably is true. You know, we don't hire great people to then tell them what to do. We hire them to tell us what to do. That continues in an AI age still. And there will be some good ideas out there, but can you utilize all those good ideas that you have across your organization and in your teams and in your little pockets for where the opportunities lie? With AI, that's not going to come from the C suite, that's going to come from the organization. And so that's when knowledge is really key and the human element and the comms is really key to then, to then navigate these stormy waters and be ready for the next wave and the next wave and the next wave. Because for the time being they're gonna they're gonna keep coming.

And hey, as, as a reminder, thank you everyone for joining us live. So Megan and Brian and Douglas and Lance and all these other people, Josh and Kevin and Ellington, thank you all for joining us. But as a reminder, we have Marcus Bernhardt, the chief consultant at Endeavor Intelligence. So, Marcus, something that you just said there that I'm super interested in is this concept of what, leapfrogging, right? And you know, there's always different tools or different techniques or, you know, flavors of the week that draws everyone's eye. So how can businesses when, when this is so, you know, so paramount, you know, even, even with the bigger companies, you know, it's like, oh, you know, two weeks ago, everyone's looking at Google, Gemini and then everyone's looking at, oh, is this chat GPT 4.5. You know, with so much innovation, so many new tools, acquisitions, billions of dollars being thrown at different tools, different technologies, how can companies even correctly look at the best way to implement something when there, there are so many changes, something coming so quickly?

Well, the main thing is to try and stay ahead of this. And so key here is to have your eyes out on the market and see what's happening around the tools that you might be using and can constantly have that conversation and reevaluate. This is particularly going to be a problem in this phase, if you ask me, of AI, where tools are very small, very powerful, addressing very specific aspects as they become more enterprise and the more successful ones start gobbling up and bear hugging and, and acquiring some of the smaller ones and become, become those bigger tools that we will be using that come with many different features that are great across the organization. These waters are extremely choppy. And like I said on the thinking effect, We've got over 400 AI tools already there, just those of interest to mainly L and D for learning. And so you can, you can imagine none of, none of us have tried all 400. Absolutely impossible, right? But this is, this is key. And for this you need all your teams to be doing some research and to keep, be keeping themselves up to date. And if you're looking to enhance your career, as you always say at the start of the podcast, if you're looking to move forward, then no, don't wait for it to deliver, deliver a training that will help you in this AI world, that's not going to happen. You're gonna, you're gonna have to take this onto yourself. And there's a real opportunity here as well. One, one of the best opportunities possibly ever in the working world where you can have your own initiative, keep yourself up to date and make yourself part of a conversation where in many organizations it's still to be decided who's in that conversation and even who starts that table. It's not said that the IT department or the chief AI person starts that table. The first department that has a really good AI strategy in place, in writing, ideally with processes and procedures, and can communicate that cross departmentally and among leadership. That's where the table will be created, where the discussions are being had. And that's a career opportunity for anyone out there.

You know, Marcus, you know, a couple of minutes ago you, you, you talked about how, you know, it's kind of the people that are doing the work or using the tools that need to have inputs and it's not necessarily a top down approach. When we look at AI implementation into your business strategy with that in mind, it seems like another maybe problematic thing is a lot of people in different levels, depending on the function of where they're at within an organization, you may not even speak the same language per se, especially when it comes to generative AI. How important is it for a company whether we talk about from the bottom up, top down, whatever you want to say, how important is it for them to all kind of speak the same generative AI language and to get on the same page?

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Great question and I'll give you a simple example when I run my AI basic workshop, then at the end of the day I've got Teams talking about machine learning, deep learning, natural language processing, and all, all those basics with confidence, they, they get what hallucinations are and where they come from, and that it's not a bug in the system, but that the system is designed in such a way that this basically the system is dreaming up the answers non stop. It just happens to be that when they're untrue, we call them hallucinations. And when they're true, then the knowledge engine is strong enough to have given us a correct answer, right? They start talking about these aspects with confidence, even after a day of having the team together and spending a really intense day around these things. And then I get the feedback that not only internally is it fostering good conversations, but people who deal externally with clients suddenly, very quickly feel confident that they can field very basic, sometimes even the one or other intermediate question from a client around AI as part of the solution and why or why not that might be a good idea. And so for me it's really key here with that as an example, how simple it is with the right tools and with the right setup and training for your team to move huge steps forward. And I often see feedback such as long overdue when I run these workshops. But everyone, everyone leaves with high levels of confidence and the conversation then is ongoing. It's, it's something, it's something where you're empowering the team to take it from there themselves. And once you have these pockets in your organization, they will start spreading, people will start talking that kind of language. And no, you do not need a degree in computer science at all in order to cover these basics. Of course, a little bit of a deeper understanding is never a problem. And there's some good videos out there that even, even the big speakers around AI, whether they're from OpenAI or from hugging Face or you name it, whatever work they're doing, if you know a little bit more, that will only build your confidence further. But the basics are right there for the taking. And there's also courses out there. It's not just in a consulting world that we do these things. In a consulting world, we then also look at business strategy and other things, of course, but the basics are there for everyone. And every individual can look to, you know, pursue the right courses and the right strategies to improve their personal career, because that's the value to the organization is how much value are you bringing. And if you're keeping yourself up to date and you're part of the conversation, well, guess, guess who's right at the top of the list for the next promotion and for the next growth phase of the organization. Yeah.

Marcus1 I, I love this comment here from Brad and I have a question following up on his comment. So, you know, Brad saying when it comes to implementation, he says he's going to look at what's costing my business the most money currently and then peeling back, peeling the onion back bit by bit. You know, for those companies that maybe have been thinking about generative AI or they're like, all right, well you know, let's, let's focus on this year end. Let's, you know, this is a big thing. Let's talk about it Q4 and implement it. You know, Q1, 2024. What, what is the best approach for those companies that are maybe doing this for the first time they've known it's a priority. You know, maybe they've been talking about it for a couple of weeks or a couple of months. But what is the best approach? Is it what Brad's mentioning here? Is it a different approach?

I, I would say do more, do more of what Brad's doing. If you've identified your biggest pain points and you're starting to peel back the onion, you're ahead of the curve. And if you're also at the same time looking at where your biggest opportunities might lie when it comes to automation and processes and start to unpeel that onion, that's the second half of the equation. Now you can go out and look at the tools that are out there. You can go to conferences, you can speak to people, you can speak to vendors, and now you can match what they're offering to your pain points and to your opportunities. And now it fits the bill. Too often in 2023 have we seen people walk around confidence conferences and the vendor floor finding shiny, fantastic tools and thinking, what's the problem in my organization that this fantastic, shiny new thing could solve well in the innovation curve? That's a normal thing to do early on. That's your first time in Toys R Us, right? You're just overwhelmed and you think, oh my God, there's so much cool stuff here. How can I use this in my organization? But then we take a step back and we say, well, let's be considerate. We've only got a certain budget, we've only got a certain amount of time. So what Brad says is spot on. Take your pain points, take the opportunities, start peeling back the onion, then go out and see who can support you with that. And if you've done your basics and you know your Basic stuff. Then you can also ask vendors the right questions. And that's also key because we see a lot of vendors in 2023 where they say, you know, we've got this tool and we use AI to automate that piece. Yeah. And that's it. That's the information that's given. And then the buyer is supposed to say, well, oh, if it's automated it, that must be fantastic. So, but that's not the moment anyone signs the contract. So we, we also need to have better conversations with vendors and vendors need to need to also get their salespeople up to speed to have better conversations with everyone who's interested. I mean, even to the end of the first half year of 2023, I went to vendors and I asked what LLM there they're deploying in the background. And the sales team said, we're building our own. And I chuckled and I said, no, you're not. I know you're not one of those companies who do. Please go back, go, go back to the team and ask and ask which one it is you've got in the back. Yeah. And do that for yourself because you're going to want to have some better conversations out here and you're not building your own LLM. I know you might be building some more the one or other algorithm and you might have some AI tools in the background, but that's not how you're approaching. So go, go and get the answer.

I love, I love that one. Marcus. You know when everyone says they're building their own large language model, not knowing to build an even usable one, it's a multi million dollar investment and you have to have some of the most talented and in demand, you know, people in the world working on your team, which people don't have. But that's beside the point. I do have a question though, because I've been saying this for months, is that I think that generative AI is the only ultimate like leveler of the playing field. Right. I think that for decades that your large and enterprise companies have had unfair advantages when it comes to tech implementation because a lot of times, you know, small teams don't have the budget or they don't have the, the capabilities. Right. But I think it's completely different now because these tools, generative AI tools that even now the biggest companies are using, they're available to the everyday person at small costs. So getting to Mabrit's question here, curious about your take. What use cases are there that are maybe underestimated by biz and Founders, what gets overestimated in regard to AI. So maybe kind of specifically even asking here about business founders, presumably maybe smaller businesses. But what's, what's your take on that?

The advantages smaller businesses have always had on the big ones is the big ones are oil tankers and they don't move very quickly and you ask them to change direction, that takes forever. That's why really cool startups get gobbled up by bigger organizations, because that's how big organizations do innovation, because otherwise they're too slow. Now we can already see that the smaller guys have an advantage here. And that also, I think goes for AI. Not only in terms of budgets and tools that is now accessible. Fantastic. But also in terms of size and the general agility that we have in smaller organizations. So you don't need to be a small tech startup. You can be a small startup in whatever sector and you can have your workflows optimized. You can have utilize AI in specific areas. We're asking about the perfect use cases, but basically if we listen to the show here, we've heard salespeople, we've heard marketers, we've had education people, we've had everyone on your show and they all talk about how they are utilizing the tools, right. So there's the agility, the accessibility is there. The market is so fast moving that even as a small organization, you're going to struggle a little bit. That's the new normal, so to speak. And so you, you're ahead of the curve here. You're small enough to be agile. Utilize that to your advantage in larger organizations. Even, you know, even a department or team, if it has enough people will really struggle to be that agile. And then they still have to run, run things past other organ, other parts of the organization. And they want to remove silos, they want to utilize AI to reduce silos. AI brings us a huge opportunity to reduce silos in the business world in, in organizations. But it also brings with it the danger of being the best tool to entrench those silos. All of those things have to go on in a large organization. You have to do none of those in a small one, especially in a startup. So for me, yes, it is a leveler, definitely. And the smaller the organization, the more agile you can be and the more you can utilize what's out there, regardless of what your products and services are and how large your teams are.

You know, Marcus, it's interesting the, the concept of the hidden dangers of, you know, working in silos and maybe generative AI actually Might make that worse. Specifically, when it comes to implementing an AI business strategy coming into the new year, my personal take is you're going to have CEOs, you know, people in high, high up positions making decisions that they do not have the experience or the background to make decisions in. With that in mind, what are maybe in, whether it's from your own experience or not, what are some of the dangers or some of the potential obstacles that business leaders need to keep in mind when it comes to creating and implementing their business strategy for the New year?

The fact that this needs to be trickled down, ideally, and the fact that no one has any experience with this. So if you're, if you're preparing for the new year, one of the things you should have been spending a lot of time and effort on is preparing your teams to be ready for that moment when the new budget releases, when the AI policy is out, and when the new vision is out. Because if you're releasing that and you haven't done any pre work with your, with your managers, with your VPs, if they're not ready to answer the questions they'll be getting in turn from the individuals within those teams, then you're not ready for 2024. So key aspect here is the communication and the processes that are in place. Where are the conversations happening? How do we share the communication? How do we share our strategy cross departmentally and with leadership? And how do we keep that cycle going that a good idea starts somewhere? How does that good idea make it all the way through to the right table can be debated and we can fish out the really best ones and we can then utilize those ideas also cross departmentally. The more important, the bigger the organization. Right, Because a good, a good tool that finds an application in one department will most certainly at least have one other department where it can, where it can provide real, really big value as well, especially in a larger organization. So those processes and procedures and that communication, that is the key bit. And that's where, that's where leaders should be focusing on. Are the teams ready? Do they have the answers to the questions that they will have and that they'll be getting from their team members? That's where the focus should have been.

Marcus, We've, we've tackled this from so many different angles. We've talked about kind of the short term challenges, long term implementation concepts of, you know, tools leapfrogging each other and kind of, you know, looking at all the different new toys and you know, so we talked about so many different things. But, but as we, as we wrap up today's show, what is maybe the one most important piece of advice that you have for business leaders, for decision makers when it comes to creating and implementing an AI business strategy for the new year?

My biggest advice I'll go very broad here is get stuck in yourself. Know what you're talking about. Don't be, don't be one of those business leaders who thinks that AI is just a tool within this world. It's yes, it is a tool, but it is one that is reshaping how we do our jobs, how our businesses operate, how we interact with our clients, and how our products and services are delivered and communicated. Everything is changing. If you haven't, if you haven't been on the free version of one of the chat tools, be it GPT or be it bard, if, if you haven't got stuck in and started yet, it's just about time. My biggest advice is do your homework. And the more you are a leader, the more you should be doing your homework because you're only leading when when you can steer the ship and we can when you can answer some of those questions, there will be, as they say in leadership, there will be wicked questions to which no one knows the answer. That's part of leadership as well. But a good basic understanding and knowledge has never hindered anyone to steer the ship to who threw a wicked problem.

Such, such good advice. And hey everyone, we covered a lot today. Some great insights from Marcus and don't worry, we're going to be recapping it as we always do. But Marcus, I just wanted to say thank you so much for joining the Everyday AI show. This is super valuable information for all of us, all business leaders, decision makers, as we look forward to 2024. So thank you for joining the show.

Thank you very much. It's been an absolute pleasure and really cool to be on after all these episodes that I've listened to myself.

I love it. I love it. And hey, as a reminder, if you haven't already, make sure to go to your everydayai.com Sign up for that free daily newsletter. Not only do we go over, yes, all the AI news of the day, fresh finds from across the Internet talk about all these tools that are leapfrogging each other. But we're also going to have an in depth breakdown of today's conversation with Marcus. More resources, more insights from the conversation. So don't miss that. And also don't miss this is actually a good precursor for tomorrow because I think this is an alley oop situation because tomorrow I'm going to be talking about Gen AI in 2024. Some predictions. You know, now that Marcus gave us the the road map, I'm going to be coming in with some extremely hot takes. So you don't want to miss that. Thank you for joining the show, and we hope to see you back tomorrow and every day with more Everyday AI. Thanks, y'. All.

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