AI Opportunities and Threats in 2024

This transcript was created using AI tools and is not a verbatim, word-for-word transcript of the episode. Please forgive any errors or omissions from the finished product.

Courtney: [00:00:00] What are the biggest opportunities and threats presented by AI in 2024? How can you capitalize on opportunities while negating the threats? And are you ready for the coming wave of AI PCs? That’s right, Dude, you’re getting a Dell! just may be ready for a comeback. Hi, I’m Courtney Baker and this is AI Knowhow Podcast from Knownwell, helping you reimagine your business in the AI era.

As always, I’m joined by Knownwell CEO David DeWolf, Chief Strategy Officer Pete Buer, and Chief Product Officer Mohan Rao. We also have a discussion with Kastle Systems CEO Haniel Lynn about how to pick and choose the right AI opportunities to go after. But first the news. Pete Buer joins us as always to break down some of the latest AI headlines and [00:01:00] how they apply to your business. Hey, Pete, if it’s not too late to say it, happy new year!

Pete: It’s definitely not too late, and it’s the first time I’ve seen you. So happy new year.

Courtney: Happy new year. The first article this week is from Investors Business Daily, and here’s the headline, PCs Could Spur Upgrade Cycle in 2024. This is the first time I’ve heard of the term AI PC, and there’s a lot of jargon about hardware specs in this article. Pete, what’s the takeaway for business leaders here?

Pete: So there’s a lot of fun, good news in the notion of AI PCs. Um, on the, on the jargon note, the thing to know about AI PCs is they’ve got an array of chips that enable, uh, local running of AI powered, uh, applications and large language models. So, [00:02:00] basically the ability to do at home on your computer without the internet, the types of things you would otherwise do through the, through the cloud with AI.

Why is that good news? You avoid the latency and cost issues of operating in the cloud. There’s also added security by, uh, by way of the ability of having and using AI enabled threat detection. So cool concept, uh, WallStreet is digging it and, um, anticipating a boost to the PC market resulting from this next, you know, run of, of innovation that will, that will go for several years.

I think the relevant question for execs is where can you get one right? Buy one, experiment with it, and form an opinion about who in your organization would benefit from having access to the same sort of capability.

Courtney: That’s awesome. I will say I’m really excited, especially for industries that are highly regulated. Um, this seems like maybe an answer to those different [00:03:00] industries. It’ll be interesting to see how this plays out in 2024.

As we look ahead, let’s think about what the future of work might look like.

A ZDNet headline recently read. Soon every employee will be both AI builder and AI consumer. The article says, among other things, 98% of executives believe that within the next 10 years, every job will be a tech job, and tech skills will be crucial to every work sector.

Pete, what should executives take away from this?

Pete: Well, if you think about it, it wasn’t that long ago that we realized. With the internet and digitization that every company was at some level to become a tech company. So by extension it makes sense. We’d get to a place, especially with the boost of AI, that every job would at some level be a tech job. Um, worth noting that the [00:04:00] survey question in the article proposed a 10 year window, and that’s naturally, I think, gets you to 98% agree, or, you know, or 98% of, uh, jobs will be tech jobs. I don’t think anyone’s got the luxury of 10 years to get to this, to get to that place. Um, jobs are transforming as we’re talking right now,

You and I, and I think leaders have to take a long hard look at, um, what jobs in the business are going to transform in what order, how there’s a fair amount of work to be done here between the leadership team and the talent management team.

To get ready for this future and not find ourselves way behind the eight ball in a bitter fight over AI, uh, capable, talent out in the market. and frankly, we don’t have the luxury of time to run that analysis and come up with a thoughtful plan. We need to be experimenting now.

And so, uh, leaders who are listening, if you don’t have your experiment in place, you should, um, and, you know, think quickly about what that should [00:05:00] look like. You know, what, what kind of, uh, parameters do you wanna set up on the experimentation so that people can get some experience with AI powered applications?

How do you run it in a safe and controlled manner? And how do you start moving this enormous population of your team to a different place on the adoption and proficiency, curve.

Courtney: I will say for everybody listening, and I feel like I say this quite a bit, I think this is an article worth reading. We always send these articles out in our newsletter, which you can sign up for at Knownwell. Pete, thank you as always.

Pete: Thank you, Courtney. Love it. Take care.

 

Courtney: In one of our more recent episodes, David DeWolf and I chatted about his predictions for AI in 2024. Definitely go back and listen to that episode if you missed it. This conversation with David and Mohan Rao about AI opportunities and threats in 2024 [00:06:00] felt like a logical if perhaps a bit more granular extension of that conversation.

Courtney: David, Mohan, welcome to the show. How are you two?

Mohan: Great. How are you?

David: Hey Courtney,

Courtney: and I, when you were gone, we talked about predictions for 2024 when it came to AI and I thought this next topic was the perfect next iteration of that conversation, which is to talk about opportunities and threats when it comes to 2024. A little more practical for business leaders listening here. So I wanna start not with a good, the potentially bad, and I’d love to hear

David: She’s fear mongering Mohan.

Courtney: Mongering. Just call me clickbait. Over here, I want to hear what the threats are that you think executives should be aware of when it comes to this year, this new year that we’re in.

What makes you [00:07:00] scared? Are you scared? Are you too scared?

David: We’re never scared.

Courtney: Never scared. I knew you

David: No, I just, what I think people should be scared of though. Um, I think if you step back and listen to the AI conversation, there’s three conversations that have gone on in 2023. One is the large language models, the advancement of the technology. One is the personal productivity.

How do we accelerate our work? Um, you know, do things faster. Write content for us, get us 80% of the way there. The third one’s where the fear is, and that is. Operationally, what’s this gonna do to our businesses? How do we run our businesses differently? What’s it gonna do to jobs? I think in 2024 that question’s gonna start to be answered. And as an executive, I think you better be ready. You don’t have to guess what the answer’s gonna be. You don’t have to be the inventor, the innovator that’s gonna solve that problem and create that vision, but I think you better be ready to react to it. I think you better be ready to get on the wave and to [00:08:00] ride the wave because I do believe that operationally. AI will fundamentally transform the way we run our businesses. And if you’re left behind, you’re left behind. And it’s just like the digital revolution that we’ve gone through where all of a sudden products and services became digital in nature. If you weren’t ready for that, when it hit, you got left behind. And I, I think there’s a risk that is going faster. And spreading faster and becoming more popular and having a bigger impact than anything we’ve ever seen before. And if you’re not ready to jump in and ride the wave, I think you can be left behind.

Mohan: I think I, I agree with that. Uh, there’s gonna be, there’s huge potential here, and there is no question that businesses should get on this, but my protection is in a different way. I’ll take it in a different way. There has been so much hype around AI that I feel there is gonna be a feeling of being underwhelmed in the business [00:09:00] context.

Right? So it’s seen as a panacea for so many things. Uh, replacing human intelligence, but within the business context, um, it’s, people are gonna feel that just because their context is, their bot has been set so high. And, uh, it could be for multiple reasons. It could be poor implementation, um, it could be, um, premature implementations, it could be any of those.

So, so I think the thing to guard against is how underwhelming it might be relative to expectations. In 2024, but David is right. The, the potential to do good and to elevate the human is there and that lives on. And, um, and we’ll see that in 2024, but also guarding against that trough that’s coming, uh, is gonna be very important.

David: So the trough that’s coming, that, that’s fascinating to me. Because I, there’s part of me that wants to disagree with you say, yes, I think the expectations [00:10:00] are high. But I have yet to see where AI hasn’t met the expectations, even though they’ve been high for a while. And I’m curious why you think specifically it’s gonna hit as it is applied to business.

What is it about the intersection of the advancement of AI and its adoption with business that causes that to be the first time it trips up?

Mohan: I think it’s because people have gone about this the wrong way in many cases, right? They’ve made, uh, million dollar investments in 2023, especially with modern data stacks and such that they expect the results to show up in 2024. So what I’m thinking is relative to the investment thesis that was there last year.

With a lot of hype and as AI is seen as panacea for many of the, uh, problems in a company, it’s gonna be underwhelming in that sense.

David: You know that, that’s interesting because that hits me as one of the things I was gonna say is I think one of the things executives should be [00:11:00] fearful of. Investing in building things in a world where what is going to be built hasn’t matured yet. Um, and I think a lot of organizations I’m seeing are starting to actually move and make investments, which I love to see, but they’re starting to build things that candidly in a month I think are gonna be outdated and irrelevant and you can buy off the shelf for a lot cheaper. Um, and that really resonates with me as you described it, as that ROI equation of what they did this year impacting next year. I could see it.

Mohan: Yeah. And beyond that, Courtney, there’s gonna be the usual slate of things as this becomes real. Um, there is gonna be issues of data privacy. There is gonna be impact on, uh, the workforce, uh, in terms of jobs, um, cyber security. All of these concerns remain, um, of course around transparency, uh, bias and such.

All the things that we’ve talked about previously will come to the fore, but, fundamentally, it’s taken a realistic look at [00:12:00] your use cases and where you’re using AI and getting the best leverage for your dollars.

Courtney: I love that. And so you, you’ve really given me a, a pretty lengthy list of potential threats here. Um, I’m not surprised. would love to just do a quick hitter on some of these. So I’m gonna give you the threat again, what I heard you say. I’d love for you to just give me what is the practical thing. I as an executive and for the people listening, what do we do about that?

How can we quickly, what’s something you could give us to help offset that threat? Okay. So David, you’re up. What you said is be ready for what this does for jobs and be ready to react to it. Basically. Don’t get caught flat-footed.

David: Yeah, I think one of the things executives should be doing is surveying the landscape for new products and platforms that are on the horizon or have been announced. Um, I think we talked about this in the episode where I talked about predictions for [00:13:00] 24. Um, I believe that 24 is gonna be the year where we’re not announcing new LLMs and new foundational models, but the, the application layer, the new platforms of this new world that we live in. Um, and if I’m an executive. Um, I make sure that somebody on my team and, and myself to a degree, are watching what is hitting the market so I understand it and I can be ready to implement those, which makes sense. Um, I think right now the focus is on what should I be building, how should I be doing it? What about the buying? And I think we’re gonna be seeing a wave in 24 about the buying. And you don’t wanna miss that wave.

Courtney: Okay. Mohan, you said the bar being so high and executives being underwhelmed, and I will say, know, this is also something that OpenAI is. Their executives are talking about as well. They’re saying y’all might be underwhelmed, which is, uh, you know, we could probably have a whole episode debating that as well, but what is, what practically, [00:14:00] what do executives do to offset that threat?

Mohan: I think it’s just to be realistic, right? So take a look at where your investments have gone, what you’re working on. What the status of, that particular initiative is, and to be very realistic about the results you’re gonna get in the, in the short and intermediate term, meaning in the next six to nine months.

Now, there is no question that if you are on this journey, it’s the right thing. You gotta keep continuing. As David eloquently said, without it, you are gonna get left, left behind. But it is, we do live in this world of quarter to quarter. Results, and you’ve got to really look at it very carefully and say, what am I gonna get in this first quarter?

What am I gonna get in the second quarter? And be super realistic about it, as long as you’re being realistic and set the right expectations. And understand that, gonna get X and what X means is this for your workforce, for your business, for your profitability, for [00:15:00] your growth, for your service, then you’ll be fine.

It’s just, uh, caution towards, uh, being very realistic with what, where you will be in the next few months.

Courtney: Okay, you two. Let’s look at the other side of the coin here, and if you listen to our predictions episode, I think where opportunities is different is these are things that you can really take advantage of. This year there are not things that might happen, but you should be looking to do these in 2024. So, Mohan, you weren’t here for that predictions episode, so I want you to kick it off for us. What is an opportunity that you’re excited about executives, latching on in 2024?

Mohan: Think your number one opportunity is gonna be around, um, looking at your existing revenues and optimizing for client retention. For client upsells. And that is gonna be your most immediate opportunities because these are the clients that you already have. Uh, you can [00:16:00] always, uh, impact new revenues and new products and services, but I think that’s gonna be a little bit of the longer tail here.

But the best thing you can do is to look at your existing customer base and look at, uh, quality of service as well as, uh, the client retention aspects.

David: I think it’s interesting as you say that Mohan, because not only are they the customers that you have already, um, not only does all the research show that it is more powerful to keep your customers and to grow your customers, uh, to the bottom line. But it also happens to be the area where you have the most information and data already, right?

Where you can combine not just what’s publicly available with the new prospects or whatever, but you can look at what we already have around communications with your clients and that, and that type of thing. So I, I totally agree with that. I also think that there’s still, um, just an opportunity. for education, are seeing a lot of people start [00:17:00] to move.

We have moved the past of just total paralyzation. We don’t know what to do. People are starting to move with AI, but I am getting over and over and over again that it is. Only a handful of people within each enterprise that are driving that momentum and that are the champions for it and are starting to experiment.

And I think as a CEO, I’d be really focused on moving this from. Individuals within the organization to a holistic mindset as an organization of we are in a point in time where transformation is the name of the game, and we are going to be steeped in a knowledge of what AI is and starting to look at every strategy, every part of our operations, every single process, and really. Creating that mindset and that culture of embracing that change. I think that’s a huge opportunity and [00:18:00] will unlock the ability for teams and organizations to take advantage of all the other opportunities.

Mohan: Completely agree. That’s a great opportunity to bring everybody in the. Company forward here and get on the same, uh, strategy. If there’s a number three that I can offer, Courtney, it’s around offering personalized experiences for your users. Uh, learn their behavior of how they use the application and what’s the best way to deliver.

Insights to them or provide intelligence to them and be able to personalize the experiences could be another powerful thing that sort of goes along with what David said, which is about individualization and, uh, elevating the human in all of us.

Courtney: So really quickly, uh, uh, beyond client retention, uh, we have. The opportunity of education and really getting your whole team aligned and driving forward, uh, towards AI transformation. And then the third one again, was personalized experience [00:19:00] for your clients and how you deliver your product to the world. Mohan, I think this was a wonderful conversation. It was wonderful to be back together again.

David: Courtney.

Mohan: Great. Thanks Courtney. Thanks David.

Courtney: It wouldn’t be a new year without some big news. Knownwell announced last week that we secured a $2 million pre-seed funding round to build the world’s first intelligent enterprise operating system. You might be curious to know more about that. Well, we’re gonna be telling you more on this very podcast, but in the meantime, go to knownwell.com and sign up for our newsletter so you stay in the loop on what’s happening here at Knownwell.

Courtney: Haniel Lynn is the CEO of Kastle Systems, a leading provider of managed security to more than 10,000 companies around the world. We were excited to get a chance to [00:20:00] talk to Haniel about how AI is being put to use in their business and what he sees as the biggest opportunities and threats with AI in the year ahead.

Pete: Hey, you welcome. It is so great to see you, uh, after so long.

Haniel: Yeah, it’s awesome. Thanks for having me.

Pete: I’ve had a swipe card. I feel like we all have, uh, encountered Kastle somewhere in our careers, but I also suspect folks listening don’t understand the full extent of the business. Uh, so can you give us the short version of what an executive would need to know?

Haniel: Uh, yeah. You know, a lot of people know us these days. Uh, for this back to work broader thing, this index that we publish that’s tracking card swipes and the percent of people getting back to the downtown offices. But Kastle itself is a managed services technology company that provides our own access control video solutions to primarily Class A, class B commercial office, multi-family building.

So a lot of people know us from the cars that you’re just talking about or on the trucks, uh, but we basically, uh, help people [00:21:00] open doors and make sure that faces are secure.

Pete: Well, with, with that as backdrop, I’m tempted to start by with thoughts of, uh, defending the, the Kastle. Uh, what are some, what are some threats that you see posed by AI to, uh, businesses such as those listening?

Haniel: Yeah, sure. you know, we are a security company at heart, and, and there is some sensitivity in the way that we describe it as the security of security for our clients. And so you think about the, uh, physical, uh, security devices like your RFID readers or you know, video cameras or whatever. These are all solutions that we provide that are connected to the internet.

And then ultimately become a part of the cybersecurity perimeter. so you also have a lot of the critical infrastructure, uh, and the, the cybersecurity tools that are on the servers and systems and networks and all these other devices that really are protected, uh, by, by Kastle. And so as a physical security services.

Role that we have, it [00:22:00] can play a really important role in protecting against your AI attacks or using the AI tools as a cap, a capability to, and and processes the security measures for our clients. So that’s all kind of big deal for us. And so our vulnerability ends up potentially being our client’s vulnerabilities.

And so we take a lot of, of, we spend a lot of time and spend a lot of attention, pay a lot of attention to, uh, making sure that we’re compliant with the most rigorous standards and protocols, and making sure that, that we are, you know, delivering the kind of protection and security that our clients need.

Pete: Nice. As you’re having conversations with clients or tracking it on your own, are you seeing increased incidents of attack, new forms of attack?

Haniel: Uh, so I mean, we see all the stuff that we see in the papers and from our side, I think we feel pretty good that we are, we’ve been able to go, uh, pretty well protected, I guess, across the number of years that I’ve been around.

Pete: Okay, so let’s go from, from threat to opportunity. Um, I know you’ve had, uh, uh, you’ve been doing some work on behalf of customers thinking hard about, uh, how [00:23:00] AI could, enable the business, protect the business, whatever the case might be. Can you share us some of your insights?

Haniel: I, uh, get pretty bullish, I think, on AI in general and how it might be a tool for our business. And, so there are a lot of places where you can use AI to enhance physical security systems ultimately, I think just deliver better security for our clients. But then there are, are ways to leverage it so that you get better operational effectiveness and efficiencies and cost efficiencies in the way that you do stuff.

Pete: How about inside the business? We spend a lot of our time thinking about how AI can transform our own businesses, in terms of efficiency and effectiveness and new capabilities. How are you thinking about that at, uh, at Kastle?

Haniel: Yeah. You know, for, for us, uh, lots of customer applications that we just talked about, but maybe, uh, we think about maybe. Even more excited about the stuff that we can do internally to run ourselves differently. and I’ll give you a couple examples of

Pete: Yeah.

Haniel: so we, as a company, you can probably [00:24:00] imagine we have a pretty technical product and it depends a lot on the, the systems implementation, the, the technical integration, the configuration, the delivery of the core technology to make sure that ultimately it works the way you intended it to work.

A lot of times it’s hard for the novice. User, and you can think of as user as a u as a customer of ours, or even an internal employee, to be able to understand whether something is working the way it should or when something goes wrong, why it’s not working right? And so how do we help all this technical information to identify the right spots that could be the point of leakage, and then be able to support our customers in as quickly as way as possible.

So if you think about that backdrop, what we’ve been uh, doing a little bit is to train. Our own large language model with all of the, uh, the internal support materials, the technical documentation, the emails, all the back and forth, that we can identify all sorts of edge use cases that are, sorry, edge conditions and when things go wrong.

[00:25:00] And then that way we can support our teams to be able to support our, our clients more effectively. And then we’re using a chat interface on top of everything so that you can get to the underlying information. And just make it more findable, make it more usable. And so somebody who might not be familiar, again with our system, an a new employee, can get to, uh, answers hopefully a lot quicker.

So we’re thinking about that for, at first as an internal application, and then hopefully at some point turning it into an external facing, uh, application for our customers as well. So that I think is really cool.

Pete: How did you structure the process to prioritize, uh, what to explore first? Where to go in the business, in what order? Like there’s so much opportunity. How did you, how did you, uh, come up with your blueprint?

Haniel: I don’t know that we’ve got the perfect process by knee stretch, um, but maybe, uh, the way that we think about it at Kastle has been very organic, to be quite honest,

Pete: Okay.

Haniel: because I, I think one of the, the good things about Kastle and then maybe the bad things about Kastle is that we are super idea productive and so

Pete: Mm-Hmm.

Haniel: is [00:26:00] really more, uh, more opportunity than there really is time to pursue everything.

And so what I’m trying to do is pick a couple places where we can advance the ball from an experimentation kind of standpoint. And, and if you, if you look just across all the different areas that, that, even just in my examples that I just gave, so you’re covering like machine learning or natural language processing or automation, robotics, like a whole bunch of different stuff.

Computer vision, I guess inside of that. And so the trick of it is like, what, what are we, where are we gonna go and learn and how are we going to go do it? And so we got both, uh. Business side people and the technology side people come together and then try to come up with different ideas. And, and I think as we’ve gotten into this, we’re finding more and more ideas that come as, we’ve made some progress on some of our ideas because I don’t know that any of us knows,

Pete: Great.

Haniel: what was possible.

Pete: Right.

Haniel: And so the, the, the thing that a team member shared with me that I thought is really interesting is [00:27:00] AI projects feel very different from traditional projects in the sense that it’s hard to identify the exact use cases right off the bat for AI because you’re learning and you’re building from there.

and, uh, and that’s true for the technical side people as much as the business side people. And so we have to iterate to ultimately get to the outcome and the use case, that you’re talking about. and so, uh, a lot of that is now iteration. So in the past you might’ve said, Hey, we know the point.

And it’s about iterating to get to the point. Now it’s actually about the point of it is iteration to identify the next point and how, do we take it from there It’s just a different way of, thinking about the whole thing. And so we’ve been trying to play with more prototyping because as we’ve done the prototypes, we’re like, oh, this is possible, or this is not possible.

In fact, actually we just did one and we’re like, oh this is a bad idea. Let’s shut that down and try to do something different. But because it’s pretty easy and fast to implement and not that expensive. Surprisingly then we’ve been [00:28:00] trying to take this iterative posture to hopefully, keep us advancing the ball.

Pete: Haniel. Um, thank you, uh, beautiful balance of insight and pragmatic guidance. Uh, for, for folks listening. I’m so grateful. Uh, thank you for joining.

Haniel: Thank you. Thanks for having me again.

 

Courtney: Thanks as always for listening and watching, and don’t forget to give us a review.

If you like the show, five stars would be awesome. We would really appreciate that and if you can leave a review or share this episode on social media, Hey, ChatGPT. Happy New Year. This episode we’re talking about the biggest threats and opportunities AI will present to businesses in 2024. So we’re curious to hear, what do you think? [00:29:00]

Now you’re in the know. Thanks as always for listening. We’ll see you next week with more headlines, round table discussions, and interviews with AI experts.