EP 23: Using AI in the C-Suite for Human Connectivity

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Are AI companies going to be having too much impact on the stock market? So that's one of the things that we're going to be talking about today on Everyday AI, your daily livestream, podcast and newsletter, helping everyday people like you and me and so many of us out there not just understand what's going on in the world of AI, but to actually use it. So one special guest today helping us all do that is George Alefragis, the executive board member from the Cybersecurity Global Alliance. George, good morning. Welcome to the show.

Good morning, Jordan. Thank you so much for inviting me.

Yeah, excited to get into it. So before we talk a little bit about George's unique background and how AI is going to be impacting kind of the C suite in general, let's go over what's happening today in AI. So kind of what we opened there with is, is AI companies having too much impact on the stock market, you know, kind of impacts all of our daily lives, whether we realize it or not. So Nvidia yesterday, which is one of the main companies creating these GPU chips that power generative AI, they said, hey, we're going to be producing a ton more of these chips. And what happened is all of these AI related companies saw a cumulative $300 Billion added in market cap after that announcement. Wild. George, what's your thoughts? You know, even just seeing how, you know, one or two companies like this can have such an impact on the, on the market?

Yeah, absolutely. I think it's, it's, it's more than wild. It's unprecedented. I do think it's a little bit overestimated, over exaggerated at this point. I don't get me wrong, I think there's tremendous potential and I'm really excited to see concretely how companies commercialize generative AI and really advance different sectors. And I will say it's going to without a doubt disrupt every single industry. So with that, there's a ton of opportunity, there's also a ton of downside. But I think it's very early on to just kind of estimate that it's going to have this type of impact on the economy especially.

Yeah. So speaking of disruption, George, one company trying to disrupt OpenAI and ChatGPT, kind of our second news piece of the day is Anthropic. So Anthropic is the parent company to Cloud. We haven't talked about cloud on the show a lot, but it's another large language model similar to GPT. So Anthropic announced yesterday that they raised $450 million, so almost half a billion to compete with OpenAI and chat GPT.

1.

One important thing to note to the everyday listener out there who maybe doesn't follow large language models as closely as we do here@everyday AI. So so many of these AI chats are based off of GPT. So anthropics cloud is one of the only ones that's not, aside from Google Bard, it is the only large one to be on its own kind of language model. George, how do you see this affecting, you know, the everyday person or, or do you see it affecting.

So. Good question. I don't think it'll have a near term impact right away. What's incredible with Chat GPT is they are definitely the front runners and the category leaders. Right. So if we look at history, if you're a category leader, you are the one who has already captured, I would say say the majority of the mind share. And because it's so accessible and it's democratized generative AI so well, folks are continuously kind of gravitating towards going back to ChatGPT. Right. It's exciting though because there are so many large language models out there and we're not only going to see disruption and innovation in terms of how companies leverage this technology or embed it within their existing offerings, create new offerings, but we're also going to see competition amongst these players. Right. So that's going to actually further accelerate the pace of innovation. And if we take a step back and look at it through either a data science lens or really the found the foundational components of how this technology is built, I'm even more excited about how they're going to complement one another. And once you actually bring them all together, the level of sophistication I think is beyond what we've seen before.

Yeah, it's great, great points and excited to dive into that more a little bit later in the show. Kind of another news piece of the day to get your take on real quick here, George. So opera the browser, maybe you've used it, maybe you haven't, but they're kind of maybe number four, number five in the browser wars. So they announced, yeah, so. So they announced yesterday, you know, in one of the busiest days in AI news in a very long time. So they kind of announced that they are releasing a update or a huge refresh of their browser that essentially bakes in ChatGPT into their sidebar, allowing you to chat with any webpage that you're on. George, is this going to affect your plans at all? Are you going to, you know, go, go download Opera after this call?

No, if I'm being really honest, I won't.

Yeah, I know it's hard too, because, you know, I think Microsoft, Bing, you know, they kind of released this functionality a month or so ago and I think people who wanted to have that functionality probably flocked to, you know, Microsoft Bing, you know, or sorry, Microsoft Edge is their browser. So.

All right, so kind of it's, it's interesting. Just kind of quickly there. I mean, we can't forget that we're also managing change, right, and behavioral change. So it's not because Bing released this feature that all of a sudden all of the market share of Google is going to automatically kind of go over to Bing. I think a lot of us tried it, but how many of us are still using it? Right. So that's really where we're going to continuously monitor an adoption curve. And it's not going to be as easy as, let me just integrate this type of technology and then imagine that I'm going to go from fourth to third just because of that.

Yeah, yeah, that's a good point. I think a lot of companies just think they can throw some AI products into their offering and it's going to catapult them. As we transition, George, a little bit into your background, another kind of piece to focus on. So a company in your space, Infosys, announced Topaz. I hope I'm pronouncing that right. I'm not sure if I am. So this is, you know, working with enterprise companies. They are. Infosys is wrapping up all of these deep learning models, machine learning, generative AI. It was hard to get details because it was just a lot of, you know, prepackaged things. So, George, as we kind of get into your background, you know, what do you make of this Infosys news and how do you see this moving forward in the future with larger companies that work with enterprise clients kind of packaging up these AI offerings?

It's a good question. I think we're going to see a lot of it coming up. Actually, I saw different news. Telus International, which is also in the space, announced something really similar. Quite frankly, you already hit the nail on the head. It's repackaging, it's more repackaging of existing offerings that have, have been there before because truthfully, a lot of the foundational blocks are the same. Right. And companies like Infosys, IBM, Cognizant, Telus International, there are quite a few. And then there's a ton of more boutique firms or more vertically aligned firms that, that are, and within that space are really well positioned to help enterprise clients advanced across this journey just because of those foundational components and blocks that we've already leveraged so much either in product development and system integration. So I think they're going to be well positioned. Is it early? Yes and no. So I think there's going to be a lot more. I think there's going to be a huge focus on proofs of concepts more so than anything else. And that's the right approach. I mean, McKinsey as well will be there in that space, Deloitte, all of the digital arms of the big consulting firms also. So my concern already is how much of that will actually be different and unique in terms of really assisting the large enterprises and then enabling them across that journey. So it'll be interesting to see how all that evolves and how those organizations also create differentiation within their offerings and then true impact. But I think it's going to be a huge focus on proofs of concepts to start, which is fun.

Yeah.

So you know, now, now as we kind of, you know, talk a little bit about your background, George. Talk, talk a little bit, kind of, you know, what you're doing in the day to day, but then also how AI, you know, so far has kind of been been used or leveraged in your industry.

Are you still running in circles trying to figure out how to actually grow.

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Yeah, so good question. So I'm fortunate where I live and serve a few industries, so high tech being one of them. Former CEO of sri. So we actually were just acquired by Orion Innovation and there is a ton of internal experimentation going on within that space. We have to keep in mind that there are very few inventors of generative AI and we are adopting the technology as we go. We are already though, because of how the technology was built, we are able to start creating new offerings really quickly within that space. I would say the component that's most leverage is actually Copilot, so enabling it across our development teams to develop faster and smarter. So that I would say is a huge area of prioritization and focus and one that's been adopted very quickly and one that's really valuable. Right. Because again, what I've seen in terms of offerings is there's a lot of buzz, there's a lot of excitement and it's fair and it's the right type of excitement to have. But then as you go deeper into actually trying it, experimenting and then asking yourself how much will this really impact my day to day? It doesn't always hit the mark. Right. And it kind of stays at that surface level. Whereas Copilot is definitely one that is helping us advance our development and then respective innovation really quickly. So that's one of the ones that we've leveraged quite a bit. And then I think a lot of organizations who are deploying these new technologies are actually leveraging as well because they're, they're enabling their developers to, to develop, you know, at light speed at this point. Sure.

No, yes, it's. Speed is the name of the game. Right. Being able to do things in minutes or hours that used to take, you know, days or weeks, I think is the name of the game. Yeah, yeah, months. Great, great point, George. I think you'll do this better than, than I can, you know, can, can you kind of explain to the, to the everyday person just kind of what your role actually entail? I'm keeping up with it, but you know, for. I think you'll just be able to say it better. So kind of like what does your day to day look like from a high level so we can dig a little bit deeper?

Yeah, of course. So like I said, former CEO, but the day to day life was really focused on helping drive the entire business forward. So looking at all the various teams across the organization, STRIUS was a global organization, so we had various delivery centers across the world. My main focus has been go to market. So that's really where I'm able to bring a concrete value within the go to market teams. It's really where sales, marketing, partnerships, customer success all come together and go to market to support new endeavors, new projects, growth, and also support existing clients and projects. So it's making sure that all of that is running extremely smoothly, that there's the right level of structure, governance, the right teams in place, the right operating models and that's, you know, we're looking at existing and what's important for this year, but also responsible to look at what's important for the organization the next two, three to five years. So doing that, more longer term strategic planning and at the cybersecurity global alliance, it's so I'm part of the executive board and that's where we look at strategic priorities. We look at the roadmap, we look at the key initiatives that are, that are underway. We're providing guidance on those, we're signing off on them. And there's obviously a significant level of governance around making sure that we are making the right decisions and that we're also challenging ourselves to do better and to do differently. Yeah.

You know, one question, you know, I'm curious, you know, you say as you're planning out the next years, I think that at least even for me, and I'm sure a lot of people that can seem daunting in the age of AI, right. When, when there's so many new advancements. Yeah. So, so how do you, how do you handle that? You know, creating actual plans or potential infrastructure, you know, for large teams? How do you handle that when you're looking years in the future when sometimes it seems like it's hard to keep up with, you know, all of these advancements on a, on a day to day basis?

Mm, it's a good question. It's actually never been harder because of those advancements. Right. So what's interesting with, you know, this new technology is really, it's, it's reinventing our playground almost on a daily or it has the potential to. Right. So now it is to your point actually, and it's a great point, even harder to be able to plan for the future. That being said, it provides a different mindset and framework in terms of the possibilities, how, how endless and how that possibility looks so different. So, so you still need to come together as a team and ask yourself, okay, where do we need to be now in this age of, you know, infinite innovation and disruption? Where do we need to be next year? Where do we need to be in three years? How are we going to now reinvent our playground? And what does that actually mean? Given this new environment, Are we staying within that playground? Are we actually reinventing ourselves completely? So again, these are questions that we wouldn't traditionally ask ourselves as often before, whereas now it's, it's, it's top of mind, right? And you also need to be very close to your clients and the different industries you serve to understand, like how are those industries going to get disrupted? Because that's really going to be at the heart of a lot of this innovation, right? And a lot of, a lot of this evolution. So, so, so we're also looking at it through an industry lens because although you may feel or you may think as an organization that you either don't need to reinvent as much or you have a thesis that you want to start experimenting and deploying and working towards you, also you take a step back and look at it from an industry level. How is that industry going to potentially evolve and what is it going to look like?

You know, even, that's a great point. So even when you're looking at, you know, change across industries, a lot of times that change is driven by the leaders, by people in the C Suite, you know, how do you see that working? You know, but so in my head, right, I think, oh, if the C suite is pushing AI and using that as part of a long term strategic vision, you're, you, you're potentially losing that, that human connectivity, right? So how do you see that happening on AI, pushing organizational change but still maintaining that, that human connectivity in leadership? Or is it possible? Or is that one of the biggest challenges? Like how do you see that playing out?

It's a great question. I'm not seeing enough of it. So I'm definitely concerned on that front. The reason I say that is we are over indexing and making it all about the technology and not making it enough about the people. Because we have to keep in mind that it's human beings who built this technology, right? And we are still going to remain the pioneers and innovators behind this technology. Although there's, you know, debate around, you know, AI and its capacity to start doing a lot of things on its own. So that being said, I think there has to be an even greater focus on the people. I think as generative AI emerges, the conversation needs to shift a lot more towards responsible, purpose driven technology that truthfully empowers evolution but also focuses on accelerating human achievement. So it's really, you know, reframing it around human augmentation and that being at the core. Why like and why it's, you know, it's normal that we're seeing Copilot grow so quickly or being adopted so quickly is even, it's how it's branded. It's, you know, we should be viewing AI as a co pilot to all the different functions. Right. So I see HR, business leaders, CXOs and IT and if you are fortunate to have chief transformation, transformation officers all come together. And one of the priorities that I think needs to be discussed and really solidified is how are we going to upscale our workforce? How are we going to create the next generation of impactful roles? With that then you're setting yourself up for success, to continue to stay ahead of the game and to think through different scenarios and different potential futures that you didn't necessarily think about before because it's a completely different playground right now. So it's really embracing AI, automation, emerging technologies, but doing that through a cultural lens and bringing your people together. Not creating actually too much kind of, you know, scare tactics in terms of, you know, what it means in terms of eliminating my role, but more so how is it going to augment that role? And then yes, there's going to be productivity gains across that and yes there'll be, you know, financial gains from that as well. But the focus needs to be on really human achievement and then with that human achievement comes the organizational achievement.

Yeah, you bring up a fascinating point that I haven't even thought about a lot. Even the naming of the AI, right? And what that says about companies who are using it on a day to day basis and implementing it. Copilot, it's like, oh, that makes sense. So they want their AI to actually be viewed as bringing humans together and copiloting something and Google Duet. So same thing. So interesting point. Thanks for bringing that up. So I know we already went a little bit over George, but I have to ask you one last question. So as you, you know, as someone working with large teams, you know, I think there's a lot of listeners who can are helping drive those teams. So you know, small, you know, small business CEOs or you know, maybe people out there leading departments. So what's your maybe piece of advice or maybe one thing that you've learned so far in, in your experience, leveraging AI, you know, what's kind of that one takeaway or one piece of advice that you can give to the everyday person to actually use AI to create something positive on the back end.

The great question. I guess two things come to mind, really building off what I shared, which is focusing on how are we going to accelerate human achievement, how are we going to augment our human capital, our team members, I think that's what's extremely important. And where I would start is and this model actually, because we're all learning as well as we go. And this model came from one of McKinsey's conversations is the two by two model, which is simple but impactful. And those are the models I love the most. So the two by two model is basically approaching it in a way where you tackle two use cases within your organization that don't require a lot of change management. So we spoke about change management earlier, right? We can't forget that that remains a huge enabler or disabler of innovation if you don't approach that properly. We've been talking about digital transformation for more than a decade, yet a lot of organizations still struggle with it. At the core of it is because of the lack of change management. So I would say first and foremost, the two by two model is really interesting because you start with two use cases that are simple, don't require law change management, but still bring value to your employee experience. So make it about the employee experience first and then look at two more sophisticated use cases that will require a lot more innovation and change management and focus those on your customer experience. So how are you creating a creative value for your customers? So by looking at it through that lens, you have a framework that you can work within and you've already created some parameters that are actionable and meaningful for both your employees and your customers. Wow.

A lot to digest in a very short amount of time. George, that was very insightful. Thank you so much for joining the Everyday AI show. I appreciate it.

Likewise. Thanks so much for having me.

All right, thank you for watching Listening. Make sure to go to youreverydayai.com, check out former episodes or previous episodes of the podcast. Also, subscribe to the newsletter. So a lot of the things that George talked about, we're going to have more resources. We'll send some more information about the 2x2 model that he referenced as well. So make sure to go sign up for the newsletter. And thank you for watching Listening and we hope to see you tomorrow and every day on Everyday AI. Thank you.

Thank you, Jordan.

And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going for a little more AI magic. Visit youreverydayai.com and sign up to our daily newsletter so you don't get left behind. Go break some barriers and we'll see you next time.