The Board Takes on AI With Gerard McInnis

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Learn more and get started at FractionAIO.com. Now, Jordan, I'm so excited to have you here, because this is a really interesting topic. We've heard so many CEOs complaining. The board directors told me to do AI, but they don't know what it means. And I was like, it's time to finally let the board defend themselves. And I guess that's a great place to start, because we're in this cycle now where everybody wants AI, but they're not exactly sure why and they're not exactly sure what it means. And I've seen this happen a couple of times in my lifetime, where everyone needed a website. And I said, why do you need a website? I'm not sure, but I know I need it. And then I need a Facebook page, but I'm not sure. And certainly AI can help a lot of companies, but I think the uncertainty is why we're seeing some just vagueness and decision-making. So I'd love to start with that perspective. Now, from coming from the board's perspective, what is your mindset when there's like a hype cycle like this or a new technology? How quickly do you want to adapt it? Do you want to be at the front of the line or do you want to wait till it's a little proven or do you want to be late to the party and like it's really secure? Yeah, a great question. And that would be actually the question the board would ask themselves. I thought it might be helpful to start even from a perspective around the differences of what types of boards are out there. Like if we're talking about a full fiduciary board that has what I'll say full governance responsibilities or an advisory board where they're more associating the management team to guide and direct and particularly maybe in areas where management doesn't have the deep expertise and they have advisors on a panel or something like that. So I guess I'm starting with that. AI is just so, you know, per prevalent now that I'd say every director would be feeling some sort of responsibility. What does this mean for me? What does this mean for the business that I'm in? And they might not even like then like legitimately might not know the answer. So they might just be simply asking a management, hey, what does this all mean for us? You don't have some directors that have actually taken on quite a bit of interest have been taking their own education programs on it. Maybe I've seen applications and other businesses that they serve on boards for. So then they try to port that over too, right? So you've got, you know, board of director members are people as well as management are people and they have varying skills and various levels of education when it comes to AI. So I guess I'm really trying to say that question is broad and purposefully would be a different answer depending on who's asking it and what context for what type of role they've taken on. So some of what I've seen is that there's this desire to implement AI and it rolls downhill. So I've worked on a project where the CEO was told by the board, you have to do some AI. So he found something and bought it and then he told the CTO, hey, look what I got figure out how to use it, justify my purchase. And so it's like it's starting to roll downhill. So I've been the second step down or like, what, what problem does this solve? He goes, I don't know, but it seemed really good. And there's such a wide spectrum of pricing and different elements. And one of the things I wonder about a lot is we're seeing a lot of security issues or mistakes happen. We just had a lawyer who got into a ton of trouble because in his brief, it covered, it mentioned 24 case laws and 21 were fake. So it's only three were real cases and it's the biggest fine so far. I'm sure they're going to get bigger and bigger as people get caught making these mistakes. And so there's this danger with AI that we just assume it's always correct because it's so confident. It will say a lie in the truth, the same level of confidence. And also, once you connect an AI to your systems and I've seen people connected to everything, all of your data is now transferring around. So they'll say, oh, we have this new AI tool, just connect it to our payment processor, just connected to our bank account, just connected to our customer data. I'm like, then it's not, what's their security policy? Is there a pro like, do they have a sock too? Do they have what's their policy on if there's a data breach? Well, they notify us all of these things because it's just a fig leaf. If we say, oh, they promised us they're not going to keep a copy of our data, but like, it still can be a really big problem. So from the board's perspective, you also look at kind of the security and do you maybe participate in before they make a buying decision go, let's talk through this because this is such a novel technology. There's probably perspective you haven't thought about just because it's, and the buying cycle seems so much faster. Like, the buying cycle for technology used to be one year, two years, three years, and now it's one week, two weeks. I've worked on a project where they talked about something on Tuesday and then signed a contract on Wednesday and I was like, wait, can I, we need to audit their technology first and it's, it's because we're so excited, we're bypassing our usual caution? Yeah. No, that's fair. So it's been said that when it comes to the role of the board, this expression of noses in fingers out and that traditionally is how a board has function. So they'd be asking guiding questions and high level questions of management and the board has the ultimate oversight for risk in the organization. So everything you just mentioned there, Jonathan, 100%, like those are the questions again that the board would put to management to say, how are we protecting our data? How are we making sure that we're not breaching confidentiality, et cetera. So the identification of use case, specific use cases probably doesn't need to go to the board. Like that might be getting too close to fingers in, but knowing that they're having confidence that there's policies in place and that the procedures that managers taken to protect data are in place and that might mean slow down in order to speed up, right? That would be like a guidance from the board, but AI can be used as like for maybe internal purposes or to maybe just operating efficiencies, or it can be more of an external application that's really more direct for use of delivery of the product or service. So those have different implications in terms of the exposure that you're going to get with going outside of your own enterprise. My understanding, and I want to be tear like I'm not a techie, although I play with this as much as I can myself. There are the equivalent of intranets within an AI environment nowadays, right? And that means you can have sandboxes inside of your own organization where you can start to experiment with different AI tools and applications without exposing your data through external to through your firewalls. You talk a little bit about risk management, which is something that as someone who came from the world of entrepreneurship and bootstrapping, I always try to risk manage with the type of clients I work with on the project, where there's projects where you get paid upfront and then projects where you get paid a percentage of the back end. And I try to not have all of one or all of the other, there's no risk and there's too much risk. And so I'm very interested, how does the board assess risk? Is there an algorithm or a system for how you measure how much risk you're willing to take? Because I think this is especially important because we have a lot of startups who listen to the show. And I think that when it's your first business, you're, I certainly see this as like growth and there's never, oh, we'll deal with cybersecurity and all the other risk things later. So what is like your framework from assessing risk? Yeah, no, great question. Maybe I'll start by going back to what the role of the board is. The board is an intermediary between the capital provider, let's call it the shareholder and management. Right? So that's the board role. They sit in the middle, but they are a representative of the capital provider. So when it comes to decisions around risk, they need to have, they need the board needs to be in sync with the risk tolerance of the capital provider, if that makes sense. Because again, they're the agent of the capital provider. So I use the word risk tolerance, but you actually start broader and there is the objective ways of defining your overall risk appetite and that might be measured in dollars. And then taking that down on lower level, you have individual tolerances. So something like a data breach, then tolerance might have some colors on it. We were willing to take a bit of risk and we might get a risk left and there might be a penalty to pay, but don't let that slow us down. Something like harassment in the workforce or a safety issue or someone might be seriously being injured or killed on site, zero tolerance. So for each aspect of a business, the risks are really, you can calibrate them based on these tolerances. I chair the board of a private company where the capital provider has a quite high appetite for risk. So then decisions that the board make and guidance that the board gives to management, respects that. They might have other capital providers who may be their pension funds that might have a lot more regulation or stricter expectations on them from their shareholders, what have you, and then their risk tolerance is going to be different. So if you're on the board of two different companies and the financial provider one is very risk tolerant and the other one's very risk adverse, you would make different types of recommendations at each of those companies. 100%. Yeah, because again, the board is trying to make sure that as the agent for the capital provider is really making sure that management understand is giving management the appropriate direction. So if they're saying, "Hey guys, we don't have time to wait. Our business is going to be disrupted if we don't change and change quickly because one of the business I'm involved with is financial services. What's happening with FinTech and move to open banking, et cetera. The automation of tasks that's been with us for a while, putting that on steroids with AI and agents and backing agents and like the pace of change in terms of executing on the business model was so fast that management needs direction where this isn't the time to sit around and quantificate or take our time with it. We got to get moving. So in a situation like that, the decision is to accept a higher level of risk so that you can have a faster moving operation so you're trading risk for speed. Correct. But the board still says we got to put some colors on that. We can't afford like a privacy breach because that would kill those financial services where we'd have to shut down. We can't afford reputation risk because we're brand heavy and our brand reputation means so much. You say let's put in these go fast, but make sure you don't do this and this don't put us in the ditch. I see. So there's different categories for the type of risk. So if it's something internal, because one of the things that I see a lot is a lot of language and it's coming from my industry, which is oh, you could replace all of our employees with AI and it leads and then they come to me and say we want to do a pilot project with our employees. If you tell the employees we're going to launch an AI program and once it works, we're going to fire you, they're going to sabotage it. You create, they have a negative incentive to participate. So I always say let's start, especially if you have employees coming into the office with how many people or don't want to go back to the office, if they don't want to work at the Amazon offices where there's five star chefs and ping-pong tables, I've never worked in an office like that. Like I can't imagine how nice that is if you don't want to work there. You don't want to work anywhere. So I always say if you have people that come into the office and they're loyal, it's better to upskill them and employ plus AI and I see these dangers with morale because sometimes when I'm talking to the employees, the first thing I'll say is don't optimize me so much that I become redundant. I've had multiple people I work with say that to be specific. I'm like, that's not what I, I'm not that type of consultant. Like I'm not the, I understand that's more of an M&A thing, but I am aware of that. So with kind of the mindset of AI, sometimes there's the hype is so big AI can't replace employees. Now, we constantly see people go to risky and then there's a lawsuit in Canada recently where a support bot said something and then the airline goes, that's not our policy. And then the court said, let's set it. So you have to honor it. So it doesn't matter that it's an AI. If it's your representative, whatever it says, and that's people aren't paying attention to that little risk that it, because the beauty of AI is that it's creative. And that's also the dangers because it's going to say something different to the same question every time. And every once in a while, it's going to say something you wish it didn't say, if your guidelines are perfect. So when it comes to the morale perspective, we're bringing AI and looking at the holistic and the value of the team, do you think it's better to do, because I've seen two approaches where it's a small pilot program, let's start with a couple of people, let's solve one problem. And then another, and I've seen other ones where they say things like you have to be 70% AI by the end of the month that you're fired. I've seen like the two ends of the spectrum. What do you think is a little more, is the more measured approach better or is the accelerated approach better? Or is it dependent upon the risk tolerance of the business? Yeah, I think it does depend on the risk tolerance of the business, but it also depends on where you see the biggest disruption from AI. So if it's in the direct delivery of product and service to your customer, and there's other players that are going, that you've seen or that you fear I'm going to react quickly or quicker, then you'll have to keep step, right? If it's a process improvement, cost efficiency type of internal initiative, probably can go a little slower. At the end of the day, it's going to catch up to you because everyone's demanding share older returns, and everyone expects profitability to be increased with productivity, with the use and adoption of technology, et cetera. But if it's an internal use, you've got a little bit more time. If your business model is at risk because of the adoption of AI, then you need to move more quickly. I love your example, though. I agree. I think in the early days, and we're talking six months ago, get into what I call that early. Is this get buy-in, let the use case come from the workforce, prioritize use cases within foot from your employees, get some quick wins, get their trust and confidence that you're not there to replace them, et cetera? Now, that approach is fine. I just feel I think there's a greater sense of urgency to move that along quicker. And I believe that the sophistication of the tools has already lead frog from where they were six months ago. And I think people are, like you were saying, the adoption of the internet initially. I think people are just more comfortable. So the fear factor of it, I think, is subsiding a bit. And people are starting to say, "Hey, I can actually use this to help me in my job. I can do higher level tasks because the lower level tasks, I can get assistance using my AI agent." There's a recent example that I became aware of where, I think it's a great example where the exposure of the AI agent was only internal. Direct interaction with the employee and management, and it has to do with field staff. So when the field staff are on the clock and they have a ticket and they're being tracked by GPS, you can set parameters for when certain tasks are supposed to be completed. And if the task isn't completed by that time, an agent can reach out and say, "Hey, do you need some help? Do we need to send someone else?" And the stacking of agents, which is something that's just become aware of recently as well, an agent will actually connect with another agent if something needs to be escalated. But this is all within the walls of the organization, and it doesn't have any risk or visibility to the customer. That's a great example of just starting to use it internally if you're on operating efficiency. One of the things that is interesting is that as soon as we get more time to work on a task, we just get assigned more tasks. So what we've seen is that with AI, you can do five days of work in four. So we're just going to give you more assignments more in time. So I've seen this at some big Fortune 500 companies that I've talked to that do a lot of consulting. Now we expect our agents to deliver fully ready presentations instead of rough drafts, and they have to do three presentations a day instead of two. And it's this idea of just constantly maximizing for speed, which risks efficiency. The biggest danger with AI is that it's so easy to push the button and then not double check its work. And I think that's the danger of it, is the easiness. And that's why we even had a judge who had to withdraw a decision recently because someone said, you wrote your decision with AI, and he goes, let me double check that. So it's not just the lawyer's doing it, it's the judge is doing it, and we've seen it all these little cases. And probably for every case I hear about there's 100, I don't. The danger is that it's easy to cheat. When I was in high school, cheating was hard because there's someone walking around the room. But if there was no one watching you take the test, I'm sure cheating would be way higher. So because it's so easy to just go, you know what, I'll just copy and paste it. The last nine emails that AI wrote were fine. This one's probably fine. And that's when the holes in the Swiss cheese line up, and that's when something bad happens. So I've also heard this approach, this top-down AI approach, which is, hey, this is a system we're going to use, we're going to train you on it, and then this is, and I've seen the top bottom up where they go, see what tools you like, and then we'll approve it or not approve it. And I've even heard someone say to their team, everyone needs to learn AI. And they go, which tools? He goes, just use tribal learning. Figure out with each other. And I was like, what, that's too broad. Give a little bit of a direction because there's 100,000 or 50,000 AI tools, like how could you possibly, you need a little bit of guidance in my opinion of what problem you're going to solve, at least our starting point. What's your perspective on how to bring in a good type of strategy that you see as most effective? Again, you're touching on a great point. You have to legitimize the use because the use is going to take place anyway, right? We know of examples where employees have just taken work home and then spun it through an application that they like at home and bring it back. So I think you're better at springing your own computer policy, right? Like the end of the day, you just throw your hands up and just say, okay, so we're going to legitimize the use of AI and agentic tools and generative search tools, but we need to trust each other and we need to be transparent. So if you make it, again, it comes back to policy, you make it such that you're not trying to catch someone else. You use the tools and generate that, that doesn't sound like your language. You actually legitimize it, right? And then that way, again, you can put the parameters around it in terms of how it's being used. You make sure that things like concern around plagiarism or copyright violations there are being respected. Again, it's like trying to keep the calculator out of the finance office. Like eventually you gave up on that, right? Or these tools are here. They're not going away. And they're only going to directly say they're only just getting more and more powerful by the minute, literally transparency, communication, policy, the whole hostecty commingled, I think. And let them have fun with it. And again, I don't believe in being a police agent. I think you got to trust that people understand why you need to put the colors or the policies in place, but make them as liberal as possible so that you encourage innovation. Most of that innovation is coming from a younger generation as well, right? You want that to percolate up through the organization. Okay, I think that you just have to create guidelines for how you get a tool approved. I think that's important so that people can say, "Oh, I need this tool," and I always ask this question, which is, "What problem is it going to solve?" Yeah. And that's my core question, even when I'm working with C-Suite and they bought a tool, I go, "What problem does it solve?" And if they don't have an answer, that's when I get worried. Because what happens is it's the same thing. If I go to the hardware store with my wife, if I buy a measuring tape, when I come home, I'm measuring stuff all over the house to justify my purchase. I'm measuring the kids, I'm measuring stuff you don't need to measure. You want to make it look like, "I didn't waste money, look, I'm using it." And I do think there is room for innovation because sometimes the employees go, "We really want this tool," and I go, "What problem does it solve?" And if you have exactly because if you don't have any system where they're allowed to ask or tell you, they'll just do it in secret, which creates that security risk. And I think that especially now, we have to have more of a security policy because if you accidentally give something to an AI, there's no undo button. If you accidentally give it credit card numbers or home addresses or social security numbers, there's no reversed. And when I was working on a larger project, we had a license with Google Business. So we have the BAA with them, we have the more accelerated contracts and the security stuff, which is we're not going to copy your data. And they were like, "I want to use this tool. You have to use... The reason we use this tool is because we have a security and compliance issue. If you want us to add on another suite of tools and some people really need to chat, GBT, I said, "Okay, we have to get a BAA with them first." So make sure you're using the corporate account and sometimes there's decisions are made at the top and the team doesn't understand, "Well, what's a BAA and why does that matter?" And they're just like, "Oh, compliance, that's just the IT department and the tech department." You know, once it gets a little bit of the decision-making processes, then people can come more on board and go, "Oh, the reason I shouldn't just use chat, GBT, on my phone is because it is a security risk and now I understand that. And that if I need a tool, we'll find a way to bring an end to the ecosystem." And I think that's kind of been my experience that you at least need to create. What's the framework for our decision-making of whether or not we'll accept a tool? Because I've seen where someone created a really long proposal for a tool that's $20 a month. I was like, "This is too long. This doesn't have to go to the board of directors for a $20 a month decision." And then we bought something else that was like $20,000 a month with no decision-making. I was like, "What's happening here?" So I've seen both ends of it where it's really, for a small startup, that's a big decision. It was the same company and it's like that understanding, at this price point, here's the process. At this point, here's the process. What parts of the decision have to make and then what we have to look at, especially if you're taking a tool from a startup, you have to look at, they've only been in business for six weeks. They don't have a security policy. They can't have possibly done SOC2 because that's a six to 12 month process. They don't have a CISO, they don't have a CTO, they don't have any security policies. And also there's one thing people often forget about is when you're moving data between different countries. So if their servers are in Canada and you're in America and it's going back and forth, there's a bunch of rules about that with compliance that sometimes that a regular employee wouldn't even cross their mind. Yeah. The reason I use that you can bring your own device to work kind of the example is for years organizations tried to fight that and they know you got to use our computer because we know how it's configured and we know eventually, okay, we'll let you bring your own device and you need multi-factor authentication or you need this or whatever. So you put some parameters on it. The use of AI tools is I think the most democratized technology in recent times, right? So that horse is out of the park. Trying to create that awareness is all you can do. Then it comes back to like say a general sense of risk, but I believe doing it in a way that is encouraging the use of the tools and creating it an exciting culture to really truly take advantage of these technologies as they emerge. Not a compliance fear culture because I heard, yeah, I think that's going to go a little badly, I think. With how easy it is to get an AI tool, there's free versions of everything. It's impossible to -- unless you take everyone's phone at the front door, impossible to lock. It's certainly one of the things that I find interesting because I started off in IT way back in the 1990s and back then, you had an intranet. No one had access to the internet at work. You just had this and it was a complete opposite of like you had only the internal documents. If you wanted something external, you had to justify it. Now it's the opposite of where we try to -- you have access to everything and then we block the chat GBT for a Gemini company or we block Gemini for a chat GBT company and it's the opposite perspective of everything's open but we block the bad things and I've really seen shift in mindset and I remember everyone used to have two phones, your work phone and your personal phone and you had work computer and I remember when my dad wanted to work from home sometimes, the IT department came over, they set up the computer with a special internet wire and you had a little token that did a different code and for him to log in, I remember it was like full passwords. So it was a really -- It was a secure ID token and you have to wait for the authentication number, right? To bring this back to the board, a lot of this, I take a personal interest in, it's at a level -- it's probably at a level more detailed than a board discussion normally would go. What a board discussion should be and in fact I've done this and I've used generative AI to help develop my board, my questions for the board. What are the 10 things I should ask of management when it comes to security, right? There's the 10 questions. It just creates a checklist for management to say have we communicated a policy clearly? Have we -- are there any tools that we've authorized or are there any that we should clearly say we don't want our staff to use or whatever? Are we only using these tools within our -- I'll call it our internet, within a safe internal environment or have we authorized the use of tools for external use or whatever, right? Those are the types of questions that a board would put to management and from that, you get an assessment of how current -- like management's currency with these issues and you really want to get confidence. You don't want to be hanging over the shoulders of management telling them how to do things. That's not the role of the board. You do want to have confidence that they are in tune with these types of issues and concerns. But again, I look at risk management as underpinning the liberation of then using the tools appropriately to drive value in the business. I wouldn't want it to be a view that the board's role is only to manage risk. The board's role is really optimized -- it sounds crass -- but optimized returns for the sharehold, the capital per rush. Value is a trade-off between risk and opportunity. So you want to understand those risks. You want to manage those risks appropriately, but you do not want to do it at the expense of capitalizing on the opportunity. Does that make sense? When boards are making decisions right now looking at things, how does AI rank in terms of importance? Is it, are you talking about it all the time or is it like the seventh thing on the agenda? Or does it rank in importance in top of mind for people right now? Definitely top three. So I like to look at the way I structure my board agendas is working in the business and working on the business. And working in the business, historically, has been the compliance aspects of the board governance -- historical, financial performance, safety records, employee turnover, whatever those compliance issues are. And then working on the business and your strategic discussions, AI appropriately fits in both of those buckets. How are we employing AI in our business? How is it helping to draw efficiencies in costs or opportunities in revenue? How is it effectively impacting and contributing to our bottom line results? And then AI working on the business, how is this shaping the business models of our clients? What's the impact of our clients? What's the impacts within our supply chain? How does it impact our own products and services? What are our competitors doing? Those are questions that you would ask if you have the working on the business type discussion. So AI is at the top of the agenda in both of those. I put it third because you still need to look at current day issues, financial position, financial -- because other things that have to be dealt with in your board agenda. But AI is absolutely full on the agenda for every board discussion these days. One thing that I see a lot of AI startups and AI consultants talking about is increases in efficiency. And so they say, "We'll make your staff 20% more efficient." I saw someone post this on LinkedIn and I couldn't believe it. He said, "If you have 40 employees in sales and we make them this much faster, you save this much money." And I was like, "Yeah, if you fire two of them, you still have their salary." Even if they are working seven hours -- they're getting the work done at seven hours instead of eight. And it's like, in my opinion, it's the wrong calculation. You really care about from the board or from the business perspective as much as the increase in revenue. Because efficiency -- I couldn't tell you if I'm more efficient today than yesterday. I don't know. It's so hard to measure efficiency unless it's a factory and you're measuring output. You have to have really specific metrics. Efficiency is so vague or hard to grasp. But I see so much of this language. We're 7% faster, we're 17% faster, and it's undetectable. Sometimes I'll see these two AIs and they'll go, "We're 1.1% better." I'm like, "That's not detectable." I can't tell if something weighs one gram more. Like, it doesn't really make a difference for me if a laptop's 1.3 pounds and 1.31 pounds. I won't be able to tell the difference. So how do you feel about focus on efficiency or is it more important to focus on increasing top-line revenue? Yeah. I'm more a fan of this strategic applications of AI for revenue and product and service development. I do think that -- I mentioned this earlier in our conversation -- I do believe that there are opportunities for efficiency. And I think there is an expectation that productivity can be improved with the use of these tools. So I think it's both. But I get way more excited about the product and service opportunities, like to increase revenue. And to be honest, we've had process automation now for a long time, right? So there's not really a new thinking around a robotic process or a chatbot or what have you, right? I think what's different is, again, I've talked about this idea of stacking ages. I think the sophistication of the tools has changed. I don't mean this in the derogatory way, but what I'll say is low-skill or low-level tasks, we've already been identifying those as being capable of being automated. And where did those employees go? Hopefully upskilled, hopefully doing higher value tasks within the organization. But we will see -- I think we'll continue to see these tools being used for what I call those low-level applications. I had a recent example where I was trying to get in touch with an airline company because I had to make a change on my flight. And obviously, I was dealing with a bot. They tried to sound like their person, but it was a bot. And then that bot wasn't able to solve my problem. So they said, "I'll transfer you to another agent." They transferred me to another bot. Well, participant. Now I have another agent, because the way it was interesting is basically triaging a customization with kind of a low-level bot, and then it triaged it up to a bot that only took exception cases, but it was still a bot. So those, I guess I'm just saying, that did displace a human. There would have been a human taking that call previously. Now you have to go through three sets of bots before you finally press zero and get to a human. I don't know if that's more efficient or not. I always ask people who want to implement that, "Are you going to give a bot the ability to give someone a refund?" If it doesn't have that, I'm like, "No, what if it makes a mistake?" I was like, "That's what the customer goes in knowing that the bot can never solve its problem if it hits the wall." So you go in knowing right away that this person doesn't have the power to solve my problem. I've worked at a lot of different companies, and I remember my friend was head of all support for the top computer company in the world, and it was about 20 years ago, and he was like, "I can't even set..." I have to get all his paperwork to send out a replacement mouse, and he was in charge of thousands of tech support people, and it was like, there's always these kind of inefficiencies in all of these things, and because you want to have all the bots in place, don't provide a better experience. It never provides a better experience, because I've never, I always ask everyone, "Have you ever had a bot solve your problem?" I've never had that, and I'm like, it doesn't create a positive experience, and I'm okay with putting bots at other places in the sales cycle, but when someone calls customer support, they're already not happy. No one ever calls customer support, and I just want to call you guys and say, "I had an amazing flight." It's already someone who's a little bit upset, so you want to, that's the worst place to test it in the process, whereas if someone's doing an inquiry and a bot can end, those are simpler questions, so I always say, "Let's start out with something a little less risky, where you don't make someone's not already mad." Sorry, I was just giving you an example. We're using it for loan adjudication in a business that I'm associated. The task of the person that receives the inquiry from the customer is simply to capture information and put it into the system, and it does like a background check or a bank statement check or whatever. It's an automated, so that's an example where that task can be automated. The customer phones in, they provide the five pieces of information that's required, and then the system does its thing. You still want a human there to manage the customer relationship, so now the human's time hasn't been used to try to input data and to do all that. They're like, "They can be there right away to create a relationship with the customer." They say, "Great news. You got approved, and now you're building a relationship, and you're not using your time just to try to just get the data captured and be measured on why is it taking you so long to input data, and it takes you two minutes longer than the other person to get your data input or whatever, right?" Yeah, I think we're going to see this shift towards an increasing value of human-to-human connection because we want to know we're not talking to a bot. I don't see the appeal in talking to a bot on the phone because there's no chance the bot is going to feel bad for you. When you call customer support, you're hoping that you can make a case like, "Please have mercy on me." You're trying to create rapport with the person with a bot. There's no chance of that, and there's no human connection. They don't know how you feel, and I think, as I always hear about these tools, "Oh, you can create an AI-generated podcast." Who would listen to that? Who wants to listen to two AIs talking to each other? I can't think of anything more boring, and we sometimes think of these use cases that nobody wants. Just because you can, there doesn't mean you shouldn't do it, but there's another example though. If you go back to the report, that's what I alluded to earlier. If your secret sauce is customer relationship, and your brand is associated with sincerity and empathy and care, and then the board doesn't oversee management making changes that compromise those values, then the board has failed. That's why I'm trying to use that as an example to say, "The board puts these expectations on the management team to say, 'Sure, we need to empower and take advantage of these emerging technologies.'" Remember, our secret sauce is empathy, caring, sincere customer relationship, and we cannot compromise that. Yeah, I think that's such a strong thing to remember is that not everything, just because it can do it, doesn't mean it's a good idea, because I have seen where you start using AI to put out all your social media content, and people go, "This is AI-generated," and you decrease your stock, your brand value. There's something about knowing that the company or the business or the people who work at the company are paying attention to you or care about how you feel, or if you didn't take the time to write it, why would I take the time to read it? My mindset on stuff like that. And to open culture as well, because it's at that corner. Right now, with all this emerging technology, but to your point about human connection, like, particularly in employee relations, they expect bespoke management. They expect you to care about them. And so you're right. I think the more that we become autonomous or automatic, robotic, we're going to fail our employees and we'll fail our customers. How can we kind of balance efficiency without losing our central thesis or our humanity or kind of the thing that makes a business special? That's a loaded question. I do believe I'm a big believer in organizational purpose and having employees be truly aligned to purpose. And that's every corporate strategy should be anchored in purpose. So I think it just goes back to what I was just saying there, like, sincerity in that. And then that has to permeate down through the values of the organization, how we treat each other and how, and what the expectation is relative to how we treat our customers. And that's a tone of the talk, like that the ultimate guy for culture is the board, again, as a representative for the shareholder. But that tone at the top has to come from the board. I think that's really powerful because I always want to remind people that AI is just another tool. It's just a technology like the calculator, like the car phone, page or cell phone, smart phone that we want to buy from people. We want to do business with people. And like, when I see a company saying things like, oh, we're replacing all our employees with AI. I'm like, I don't want to support that. And we've seen companies get back lashes from saying that. It's appealing to the shareholders financially, but it can really kill your relationship with the customers. Because what do you mean you're firing everyone? I don't want people don't want to support that people are more, pay a little more attention to the companies they do business with. And I think that's an important thing to end on. And I think this has been a really powerful discussion, certainly very educational for me. So I appreciate your time, Drard. For people who are interested and want to see more of what you do, it's linked in the best place to see what you're writing about and the amazing things that you're doing. From the board's perspective, which I think is really, it's really nice to see that. Yeah. The LinkedIn would be the best. I call it my portfolio life. I do board work. I do corporate advisory work. I do some pure cow sowing. So my LinkedIn kind of represents all the different things I do in the community. Thank you so much for your time. 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