AI Reshaping Work & Learning

Build it while you're flying, it comes to mind, and there's not an organization that's dealing with AI that is not actually operating from that perspective. We actually sit at an interesting intersection in that technology space. And one of the things that we're finding is that the traditional approach to adopting this technology is to establish a policy, and that comes from the cybersecurity perspective where policy is meant to drive behavior. Behavior is meant to dictate how the organization moves forward, and I actually think that that's the wrong approach. I think the approach to this should be strategy first. What do we want AI to do for us? Or what do we want to do with AI?

Where in our organization do we want to be enhanced by an AI tool? And then once you understand the framework of that strategy, now you can move into the policy to dictate how the organization is going to implement AI and how it's gonna be used on a daily basis. So to try to answer your question, yes, it is advancing faster. AI has stirred the pot of culture, technology of every aspect of our lives, and we're just at the tip of the iceberg of figuring out what this technology can really do for us.

And so that whole adage about, of building a plane while you're flying it, we're gonna be in that mode for a very long time until we actually see things begin to settle down and figure out how do we guide this, this technology instead of being overwhelmed by it The jury is still out on that because the infiltration of AI has not settled down yet. From a cybersecurity perspective, when we talk about artificial intelligence, we look at it from a standpoint of how can we enhance the human element in the organization?

And in our space, because data is king, what AI is doing is actually streamlining our ability to be more efficient in threat identification and response, doing things like establishing context. You walk into some of these companies, they have many of what we call point solutions that are all cybersecurity focused, that are generating gigabytes of data every day that overwhelms the human element in the operation. And so what we've done is looked at how we can use AI to do aggregation, correlation, and analysis to provide that context so the security operator can be positioned in the right place, being informed, deciding, and acting.

And as we see AI begin to take further hold in that space, I think you'll see a lot of these common everyday threats that we hear about every day kind of go away. But we don't know what new threats will manifest as a result because, again, AI is still infiltrating and still being adopted. We just don't know what that future is going to look like. But I think that right now our consideration should be around the whole data analytics aspect of it. How do we collect, correlate, analyze, and then inform security operators to be able to respond to what they're seeing in a much more quicker way?

So to answer your question about what new vulnerabilities, we don't know yet Well, what I consider to be as the sudden onslaught of AI has thrown us for a loop. We're still holding on to where we are now when we should be thinking about what are the opportunities in the future gonna look like. I think about the industrial age in the early 1900s when labor was very manual, and you had the ditch digger that would do that job in a very manual way. But when the mechanical aspect came along and you could dig ditches using a machine, you could dig ditches a lot faster, and you could get a lot more work done during the day.

Well, that allowed that individual who was a manual digger to then be retrained and retooled to do something else. So look where we are today. I think we should be thinking about what future opportunities are there, uh, and how can we begin to train people in being able to take advantage of those opportunities. The country of Trinidad, for instance, and I've spent a lot of time there, they're a geological-based economy, oil and gas, basically. But they know that their supply of oil and gas is going to run out in the next seventy or so years, so they're shifting the entire economy to what they're describing as a knowledge-based economy.

Very educated culture, and so that shift is easy to do because they're already educated, but it's just a matter of understanding where does that shift need to be and how do we get there. With that kind of support that's driven by the government to make that shift, it makes it possible. And so as we're all kind of chopping at the AI tree individually, what eventually is gonna have to happen is there's gonna have to be concerted effort across various sectors, across the government to develop what that future program, if you will, is going to look like, and then begin to provide the resources to help various sectors of our society to get there. But right now, that's not really happening.

People are still trying to figure out the who's gonna, what's what of it, and it's creating a bit of a challenge that we're experiencing today as a result. But we need that concerted government. We need that concerted thought leadership. We need that concerted corporate leadership in order to create what that future's gonna look like. Otherwise, it's gonna be a struggle for a very long time. The challenge of the speed on this new technology that has not really established a directional foothold, if you will. So nobody really knows what's going on. Everyone knows it's there.

They know they need to be doing something about it because they don't want to get left behind, and so they're doing the very first thing in front of them that they know to do in order to understand it so they don't, quote-unquote, "get left behind." But that lacks the policy, the standard, the structure that provides the guidance and the direction that's necessary for people to understand what that means for them in the immediate and long term of their professional lives. That's a very hard question to answer because we don't really have any other choice but to do it the way that you just described it. It's the fly in a plane while you're building it scenario, right?

So until-- And actually, there's nothing wrong with that because what you wind up experiencing is some normalization over a longer period of time where you begin to see this picture forming. You know, I go back to the movie, what's it? I, Robot with Will Smith, with all the robots and stuff like that. Well, that was a scenario of a society that had fully adopted that technology into every aspect of its life. And so they really knew what they were doing when they were doing it. We're not there yet. I mean, we-- I was watching a video the other day of this robot that was dancing. It wound up kicking a kid in the stomach, and the whole audience kind of freaked out about it.

Never seen a robot harm a human being like that. Now we've got a new picture of that, so what do we do about that? So we're still figuring it out. And unfortunately, management, senior leadership, they don't understand it as well because it's all just as new to them as it is to the workers down at the lower levels. So I would venture to say that most companies are still in that experimentation phase because they have not yet determined in a definitive strategic way how AI is going to shape and move their business going forward. It's a trial by error kind of thing. What we're seeing, and let me say it this way, in some sectors that's the case.

In other sectors it's not, particularly in those sectors where data analytics is huge. For instance, in our space, data analytics is huge. We are implementing it in a very meaningful way because the, the, the, there was a natural need for it. Because of all the data that we generate on a daily basis from our security tools that was at one point in time having to be reviewed by a human being, now we can employ AI to do that review, and that contextualization allows us to get through that process a lot faster. So it really depends on the sector.

If you're in a procedure-based profession where it's based on tasks and so forth and so on, it's a lot harder because what you're looking at is automation of those tasks. And the question is, well, how do you use AI to automate those tasks? What components of those tasks, uh, can be successfully automated? So it really depends on the, the, the industry that you're looking at. In the medical field, probably not so much. In the banking field, yeah, because banking is really all about data. In the technology field, you've got some places where it could and couldn't. We talked about coding being the biggest industry, for instance, of displacement. We're developing a tool.

We're using AI to do a lot of that coding now instead of hiring a whole team of developers to bang out that code like we have before. So it's subjective. It depends on the industry that you're in and the particular business objectives that you are serving. Yeah. So I'll take this one because I work in government. I work with municipalities all the time, and I'll give you another adage. How do you eat an elephant? One bite at a time. What's happening is because this technology is taking us by storm, we're trying to get our arms around it before we know what the actual impact is going to be.

So the approach that we recommend is just by asking a simple question, how can we use AI to enhance this process? Once you do that enough, you'll begin to see trends manifest that can then begin to drive policy, that can then begin to drive regulation, because you'll see the impacts of those decisions across a wide-ranging aspect of the economy and society, and so forth and so on. And now you know what ordinances, what regulation needs to be put in place in order to mitigate that known threat. But we're looking at it from a fifty thousand foot view and trying to figure out what is not formulated yet. This is really a grassroots bottom-up approach that we have to take.

And I think the question about the workers going at it first is not a bad approach, because what you can begin to see if you're looking down from the fifty thousand foot view at it is how is this beginning to impact our, our culture, our organization, our operations, and where are the benefits and challenges there that we need to be mindful of or address and mitigate based on the impacts it'll have in our organization.

So they really need to take a myopic look at it in order to see where is it having its individual microscopic impacts to then determine how can you then approach it from a lawmaker perspective, which is an all-encompassing kind of approach I think as entrepreneurs, there is a world of opportunity for us, and one of the things that I think people miss is the opportunity to be extremely creative in how they take this technology and employ it to solve a problem. I, I think your decision to go in that direction is an excellent one because the sky's the limit. I'm an entrepreneur. I can do whatever I wanna do.

You just put yourself on that same path to be as creative as you wanna be with it, and so, you know, kudos to you for that. More people, as was mentioned earlier, should be looking at entrepreneurship as it relates to this technology 'cause there's really no boundary to it I'm gonna tie this back to something I said earlier about opportunity and creativity. Yes, Texas does have that issue. There is a company and, and all-- we have all these data centers that are popping up as a result of needing to support the, the appetite for AI. They're of course gonna require power and a bunch of different resources that are gonna impact communities around them.

There's a company that has proposed a solution to this, and this kinda comes from your world. The Nimitz aircraft carrier is being decommissioned. It has two nuclear reactors on it, um, that they typically just bury out in the desert somewhere. This company has proposed to take those two nuclear reactors and turn them into power generation stations to support data centers in a particular area.

We have a couple of aircraft carriers that are gonna be decommissioned over the next few years, and they're proposing to do that, and the government is seriously considering that because of all the challenges and issues and concerns that are being raised by communities around the country that are having these data centers pop up. That's creativity, that's opportunity, and that's how we really need to be looking at this as we move forward, 'cause it's not going away. Question of security of the technology? Yes. Okay. Uh, so my previous answer was we don't know just yet, but there are some concerns, and you kinda hit on one with SQL injection, data leakage, and so forth and so on.

Those are real concerns, but that are first answered by strategy. What do we wanna do with this technology? What area of our business is this technology going to affect? What data that's generated by those areas, technology that are going to be impacted by it, and what risk mitigating factors do we need to put around it in order to ensure that we can protect that data? Now, some of this is going to also require a, a consideration around how you go about it. Most people are using off-the-shelf tools, Copilot, um, and Anthropic's Claude, ChatGPT, so forth and so on.

So they have no control over the back-end technology that's running those tools, so they really don't know where that data is going. If, if a company really has a serious concern about the security of the data, then they really need to be looking at creating an environment on their own where they can securely or where they can confidently secure that data to ensure that it's not going online up in the wild. But right now, we just really don't know. I know companies say that, you know, if you're not using the public variants of these, the LLMs, then there's more security controls around it. But how do you really know? So it's, it's all about strategy.

It's all about policy that you have to develop first before you go down that road