Leveraging Business AI with Chris Happ

In this episode of The Better Leadership Team Show, I sit down with Chris Happ, Founder of Virtuous AI, to explore how business leaders can practically leverage AI to close execution gaps, move faster, and compete with far larger organizations—without losing control, culture, or clarity.

AI as a Present-Day Leadership Capability

• AI enables leaders to build and deploy sophisticated tools in hours rather than weeks.
• The opportunity with AI is not primarily about technology itself.
• The real advantage lies in improved execution, increased speed, and measurable outcomes.

The Most Important Trait of Great Leadership Teams

• Respectful debate is a defining characteristic of high-performing leadership teams.
• Productive conflict strengthens decision-making, innovation, and truth-seeking.
• Teams that avoid conflict risk stagnation and blind spots, particularly in rapidly evolving environments like AI.

AI as a Transformational and Polarizing Force

• AI represents the most transformative technological shift since the internet—and exceeds it in scale and speed.
• Leaders generally fall into two camps:
  • Those who see AI as a powerful accelerator of creativity and productivity.
  • Those who fear job loss, misinformation, and loss of control.
• AI functions like fire: it can be used constructively or destructively, depending on leadership intent and responsibility.

The Execution Gap Facing Mid-Market Companies

• The execution gap is the distance between strategic intent and actual delivery.
• Mid-market organizations face structural constraints:
  • Limited financial and human resources.
  • Difficulty competing for elite AI talent.
• Their competitive advantage lies in agility and speed—both of which AI can significantly amplify.

Why Business AI Is Different from Consumer AI

• Consumer AI tools are designed for individual use and personalization.
• Businesses require AI systems with:
  • Guardrails

  • Shared rules
  • Consistent decision logic
• Effective business AI operates as a corporate brain rather than a collection of individual tools.
• This ensures alignment with company values, policies, and financial accuracy.

Bottom-Up Adoption vs. Top-Down Strategy

• AI adoption has largely been grassroots, driven by employee experimentation and tool sharing.
• While experimentation fuels innovation, it often stalls without leadership direction.
• Nearly all mid-market CEOs are increasing AI investment.
• Only a small percentage have a clear AI strategy.
• Sustainable progress requires alignment between individual experimentation and executive leadership.

Why AI Must Be CEO-Led

• AI initiatives fail when they are not driven by the CEO.
• Delegating ownership solely to IT or technology teams creates resistance and slows adoption.
• AI adoption is an outcomes-driven effort, not a software accumulation exercise.
• Effective leadership requires:
  • Clear prioritization
  • System consolidation
  • Focus on results rather than tools

Virtuous AI and the BAIO Platform

• Virtuous AI is the company.
• BAIO (Business Automation, Intelligence, and Outcomes) is the platform.
• BAIO:
  • Automates core business processes.
  • Centralizes organizational knowledge.
  • Combines deterministic execution with predictive intelligence.
• The platform allows leaders to focus on strategy while AI manages operational complexity.

How BAIO Works with Existing Systems

• BAIO initially sits on top of existing systems such as ERPs and CRMs.
• Over time, organizations reassess the need for multiple disconnected tools.
• By unifying data across silos, BAIO improves clarity and decision-making without forcing immediate system replacement.

• AI becomes a comprehensive lens through which leaders view the entire business.

Real-World Example: Inventory Optimization

• A consumer apparel company used BAIO to improve inventory forecasting.
• Results included:
  • Forecast accuracy increasing from approximately 70% to over 90%.
  • Millions of dollars in freed-up cash.
  • Implementation completed in weeks rather than years.
• The unified data environment also enabled better marketing, customer lifetime value analysis, and strategic planning.

Managing Rapid AI Change Without Chaos

• AI tools evolve too quickly for most organizations to manage internally.
• Separating business knowledge from AI models allows organizations to:
  • Swap models as technology evolves.
  • Retain institutional knowledge.
  • Avoid costly system rebuilds.
• The focus remains on outcomes rather than technical churn.

Data Privacy and Intellectual Property

• Business data and processes are core intellectual property.
• Secure AI architectures ensure:
  • Company data remains private.
  • Sensitive processes are not exposed to public models.
• Public AI is used selectively to preserve competitive advantage.

Implementation and Change Management

• Successful adoption begins with structured onboarding focused on outcomes, data alignment, and leadership clarity.
• Long-term success depends more on people and change management than technology.
• A growing ecosystem of consultants is emerging to support organizational transformation.

The Future of Leadership Skills

• Leadership skill requirements are shifting rapidly.
• The most valuable traits now include:
  • Curiosity
  • Creativity
  • Willingness to learn
• Leaders must support teams through transition by offering growth pathways while being transparent about change.

https://www.virtuousai.com/ 

https://www.instagram.com/virtuousai_official/ 

https://www.linkedin.com/in/clhapp/ 

https://www.facebook.com/VirtuousAIOfficial/ 

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  Transcript
  

   

  [00:00:00] 

  Mike: Driven by a deep understanding of the challenges mid-size businesses face, Chris Hap launched virtuous AI to close the execution gap, the costly distance between a company’s strategic goals and its ability to deliver under his leadership. Virtuous AI is redefining how businesses compete. In the AI era, not by outspending the giants, but by out executing them.

  His mission is to empower mid-market leaders to move faster, work faster, and achieve measurable outcomes that drive sustainable growth. We’re gonna talk about everything AI on this episode. Chris, welcome to the show.

  Chris: Hey Mike. Thanks for having me. I love the confluence of AI people and leadership, so really excited to get into this.

  Mike: Yeah, I’ll tell you, AI is one of those things. I’m not a technologist,

  but. But [00:01:00] I am kind of a geek when it comes to that kind of stuff. And you know, I just found out, and this may be dated depending on when people are listening to this, but I just found out about the launch of Gemini three last week and decided I’m gonna go in and try to create a web-based application,

  and I created something in a few hours. Kind of recreated something in a few hours that it took a developer, I hired about a year and a half ago, about three weeks to create, and my app is much better than what they created. So like anything, ai, I just dive in and I, we can talk about this for days.

  Chris: Oh, it’s mind bending. It’s absolutely insane. I’ll tell people I can’t unsee. This technology and,some may call me a zealot now for it. And, I almost take that as a compliment because I just, I’m so passionate about getting it, like your reaction you just had getting that in other business leaders’ hands.

  ’cause [00:02:00] it’s incredible what you can do with it. You gotta embrace it.

  Mike: absolutely. Absolutely. and. You know, well, why don’t we dive in? First question I always ask, we’ll start there and then we will dive into everything, you know, AI and virtuous ai. 

  but Chris, from all of your experience, what do you believe is the most important characteristic of a great leadership team?

  Chris: Debate, absolute respectful debate, challenging each other. Pushing each other. Difference of opinion, difference of thought. It’s critical how you have that debate and how you have a respectful way to challenge each other. But I found that to be the hands down, the most important thing. I absolutely love, the getting in a meeting room with people and just.

  Putting an idea on the table and reasoning through it and really just working through that with a group of, like-minded people.[00:03:00] 

  Mike: Yeah, I agree. In fact, I’ll use a stronger word where some people think it’s a stronger word. The word conflict

  tends to have a negative connotation, and I’m

  like, no man, we gotta seek out conflict. If there’s no conflict, we’re doing something wrong.

  Chris: Yeah, a hundred 

  Mike: I love that. I 

  Chris: Especially in ai, there’s a campus that, one of our investors is on, I absolutely love it. They’ve reconstructed what it feels like to be at a academic institution, right down to a debate chamber in the, on the campus where they have this, sort of seeking of truth, kind of vibe going.

  And I just absolutely love that as a business concept. ’cause I don’t think we have enough of that. and, but I actually like your, I’m gonna steal your word. I think conflict is better.

  Mike: Yeah, I sometimes I wish. AI would have more conflict. I’m sick of chat, GPT telling me every idea I have is the best I, is the best idea in the world. So we’ll see if we could work that into ai. But I wanna start, you know, Chris, maybe be really big [00:04:00] picture 

  AIis, you know, there are. You know, individuals that look at this kind of AI era for lack of a better phrase, as the most amazing thing. Oh my God. The things we can do and we’re gonna be able to use it to, to cure disease and all this different stuff. And there’s others that look at it as if it was sent. From the devil, you know, people are losing their jobs and a and Amazon just cut 30,000 jobs.

  And is that because of ai and, you know, people are gonna, you know, putting out fake videos and we can’t tell the difference between reality and ai. how do you think about AI at that level and how do you suggest others think about it?

  Chris: I love that question. It is no doubt the most transformative technology that I’ve ever seen. and I was coming of age during the [00:05:00] internet. that’s when I first started my career. So I saw the impact of the internet, and this is 10, a hundred, a thousand x that I remember. I was at a, was at a conference and Sergey Brin was talking.

  he relayed this story where one of his, he was at a coffee shop, sort of semi-retired, and one of his friends came up and said, Hey, what are you up to nowadays? And he was just saying, eh, kind of dabbling in things here and there. And, his friend said, what are you doing, man? Is the, for someone like you, this is the single greatest moment in your lifetime with this technology that’s now available.

  You gotta get back in the game. And he’s literally said, the next day I went into Google and just got back into it and just fell in love and was enamored ever since. And likely that’s to your point about Gemini three that, you know, I think some of his fingerprints are on that. so it’s that, I think transformative from someone that is one of the, Biggest brains in the technology era for them to [00:06:00] realize it was that transformative. and I agree with the premise that it’s polarizing. I wish it didn’t have to be, but I think that’s just the reality because there’s gonna be people that understand how to embrace this new technology and there’s people that don’t.

  And I think it’s scary. Like anything new. But again, I’ll go back to just seeing your face when you talked about what you accomplished in a, you know, afternoon, which took someone else a year and a half to do and it gave you the power, what the, what’s terrifying, I think for a lot of people, especially in the tech era, was that.

  You were beholden. You have this great idea, but you can’t do anything with it. It’s sit there, it’s stuck in your head. You couldn’t get it, you know, pencil to paper there, and now you can, you have this, incredible power. So it unleashes this creative ability that you didn’t have before. ’cause it can amplify your strengths or [00:07:00] if your.

  Brain works a certain way and not another way. You now have this tool in your pocket that can help work with you. But it’s a, a mind shift to, to think that way. And you know, if we go back to what you had said, you know, we talked about what’s the best characteristic of a leadership team. You need people with different skill sets.

  But we now have a tool that brings something to the table as well, where we don’t need, The traditional tool sets, which might have been, I understand accounting really well, or I understand how to program really well. Well now we have a tool that can do that. So now what do we value? Human thought, human ingenuity, creativity.

  It turns out AI is not good at end to end the last mile. It’s very good at the middle stuff. We give it direction. It executes. But it’s not great at, what is the idea and then how do I complete that, sort of the nuance. And that’s where I think we need to learn how to really operate and then accentuate our uniqueness.[00:08:00] 

  Mike: Yeah, the simplistic way I look at it and I look at this with any. New transformative technology

  and social media is another good example

  of any new technology to me is like fire. You could use it for good or you could use it for evil. People are gonna use it for both. I mean, I’m sure. You know, n next big election coming up, there’s gonna be a whole lot of videos out there. A candidate saying things they didn’t really say because someone went on Sora or Nano Banana, whatever the different tools are out there. Someone went and created it, but I think we have to understand as leaders. That it’s the world we’re living in. and if we don’t leverage it, you know, people are gonna pass us by. 

  that all being said, you talk a lot about the execution gap. Say a little bit more about what that is and what it’s costing [00:09:00] us.

  Chris: Yeah, so. this is particularly salient for the mid-market where we, and I say we, I’ve started multiple businesses. My dad was an entrepreneur and we have a unique set of challenges in the mid-market. We aren’t as well capitalized. We have smaller teams. We just have less resources. we can’t, if I wanted to go hire, as a typical company, I’m obviously in the space, so I have different challenges.

  You’re not competing with Meta or Google to go hire an AI engineer, and it’s just not a reality. So we have to compete different. And in the AI era, that difference is amplified because they can throw a lot of money at this new technology. So we can see them getting further and further ahead, or the potential for them larger companies to get further and further ahead because they’re investing in it.

  And it creates this gap in what we [00:10:00] want to deliver and what we can deliver. So that’s what I’m trying to solve is that how do I give the mid-market the technology they need to close this gap? And it turns out the great part about the mid-market or businesses that are smaller, we’re just nimbler. We can move faster.

  So if you were to give me a Fortune 50 company. And say, go make them AI first. I’d say gimme 10 people from that company and I’m gonna create, you know, fortune 50, dot AI or whatever that company is. Take their 10 best people and create the anti version of that company with AI and let ’em go compete.

  ’cause they’re just gonna be able to move faster. There’s too much bureaucracy built in and AI doesn’t work that way. It’s extremely creative, it’s extremely fluid. We have a saying that, process is a replacement or can be a replacement for judgment? Well, as you start to embed AI and letting agents work through [00:11:00] processes, things like being large slows you down.

  So that’s where we think if we can give mid-market a technology like we’ve created, called a Baio platform, we can help them. Close and in fact eclipse the execution gap just by leveraging what they’re good at, which is speed. We can take, you know, as you’re building a company, what do you do? You have a great idea.

  Then you build all this infrastructure around your great idea, and you’re not great at that. You might not be great at accounting if that’s not your business or all the HR components, but now we can leverage this super technology to fill in those pieces and just spend all of our time and effort on what we’re great at.

  So that’s what we’re trying to do. Is close the gap where large companies can invest in ways that mid or smaller companies can’t.

  Mike: Yeah, I love that way of thinking, where on the one hand, they could invest way more money than the mid-market, [00:12:00] but. we as folks in

  the mid-market, or me as, you know, my business, I work with mid-market, but my business is smaller than mid-market. I’m one person with a bunch of helpers. Like, we could move with such, like, like I said, I went on and created an app in a few hours and did it and deployed it and you know, that would take a company a lot longer because. It just takes a lot longer to make decisions. So, you know, it’s not about how big you are, it’s about how fast you’re moving.

  Chris: I was speaking with a CEO yesterday and she was talking about this meeting she was in and. We all fall into this trap where we do it the old way, and they were going around, they were laying out the marketing strategy for the next year and talk. Two, three hours later, she goes in, an AI platform, asks, lays out sort of the plan, asks for the marketing strategy.

  Turns out they pivoted the strategy right there based on that to be the point of view of the product as a point, [00:13:00] as opposed to the point of the view of who they were trying to sell it to. Just took off, went viral. This was a B2C play and, I just loved it. It’s exactly what you can do. You can literally be very creative, go in a room, add this AI tool to your, process, and you can get outsized outcomes, but you have to be willing to do it as well, which is the gap we’re trying to solve.

  Mike: In your, I read through your white paper

  Chris: Oh.

  Mike: I’m actually lying. I sort of skimmed through your white paper, but I had AI give me a great summary of the white paper. Yeah, I may as well stick with what we’re

  talking about and. 

  Chris: talking to me 

  Mike: Yeah. 

  Chris: Yeah.

  Mike: And, you know, so I know you talk about, business ai and I know you know Baio, which, we’ll, you know, I’m sure we will get into, you know, business AI is the fir first part of that.

  But what does business AI mean and how is it different than the way most of us typically think about AI and use ai?[00:14:00] 

  Chris: Yeah,it’s a really interesting, place that we come at the market. and the best way I can explain it is when you interact with, Gemini, for example, you are having a back and forth. It’s learning about you personally. It becomes a really, personal experience that you’re gonna have.

  And it starts to kind of, kind of understand you. The difference is if I put you as a person into a business, the business has rules and policies, and you may want to give someone a discount. Let’s take a chatbot. There was a case where Air Canada chatbots were giving large discounts, went up, went to court, they were held liable.

  These are their agents. So as a business, we can’t have every individual chat bot in person acting. on their own behalf. We need a set of business rules, core values, ways that we speak, [00:15:00] processes that we follow. Things as simple as how do you calculate sales? Well, there’s some nuance to that. Everyone might look at it different.

  how do I handle returns? How do I handle discounts? So there’s a, some rules we have to follow as a business. There’s a brain that needs to form that is the collective corpus of that business. Now, you as an individual are gonna interact within that. So you’re gonna use tools on your desktop and help you get more productive.

  But that has to have some rules and guardrails that’s run by business ai. So I think of our Baio or our platform as an orchestration layer and a set of, corporate learnings and core values. That we all abide by. And so it’s meant to make people move faster, but within the agreed upon best practices of our company or the rules of the company.

  Mike: So there’s kind of an interesting interplay as you help me understand that, [00:16:00] you know, part of me looks at that and says, oh, it’s kind of, you know, AI growing up a little bit and becoming a real business tool versus just everybody doing it one-on-one. But here’s the interplay that I wanna,I want to talk through a little bit

  is what I have seen. So far in organizations and it may or may not be right, it also may be just short term versus long term, but what I’ve seen. Yeah. That’s very different than any other technology. It’s very different than implementing A CRM or an ERP or anything like that in an organization is AI has been very grassroots. It’s not okay. Everybody, you know, our chief AI officer has made the decision that we’re all going to use. Jack, GPT in this way. And what I see happening, and it’s been actually a pretty good thing up until now, is it’s a whole lot of individuals playing with stuff and saying, Hey, [00:17:00] did you know what Perplexity could do?

  Did you know we, you can go into Notebook, LM, and it can create a podcast, you know, based on this, it’s individuals bringing it back and then an organization saying. or leaders within that organization saying, that’s a great idea. We ought to share that with more people. So I’ve seen it be much more of a bottoms up technology than a top down technology. Have you seen the same thing and how does that interplay with the idea of business ai?

  Chris: Yeah, that’s an interesting, perspective and I don’t disagree. We just did a, mid-market, survey where we pulled, several thousand mid-market leaders across all verticals. And the resounding feedback was, we’re all investing more in ai, so net budget increases over the next [00:18:00] year in what we’re gonna spend on AI to the tune of something like 98% of CEOs said that 7% said they had a strategy.

  So underscores your point. We know we gotta do this, but we don’t know how. And individually, people are really curious because when you interact with it, you see what it can do in your daily life. I don’t write emails without it. I don’t do tasks without it ’cause it just makes me so much more efficient.

  So individually, the a fluid market would suggest that curious people are gonna move to these technologies regardless of any corporate edic. Right. So the interplay is how do you leverage what people are doing because they can’t, we all know that the sort of drawback on AI is, it can hallucinate it tries to please you.

  As you said, your idea is always the best idea. [00:19:00] it’s terrible at math. You know, you can still look at things now like five point,nine 5.09. Versus 5.11 asking AI what’s bigger and it so it’s not good at certain things, and that’s where business AI comes in. We have math, we have rules.

  There are certain things in a business I don’t want AI to touch. When there’s a predictive process that I have or something that we’ve agreed needs to happen and a set of rules that we follow that should happen now, AI may guard around or move me around. And getting to help make decisions, but there’s certain things I just want to execute.

  So if I say, pay Mike a hundred dollars, it shouldn’t be 101. It shouldn’t be 99, it’s gotta be a hundred dollars. And so that’s what business AI does. But it shouldn’t stop people from individually being as creative and out there as they can, but as you start to make decisions or execute on specific things, that’s where we need very.

  [00:20:00] Predictable outcomes, which is what the software industry did for so many years. So it turns out most of our customers end up with a Baio, which is the corporate brain, and most of them end up with a desktop app like a copilot or chat, GPT or Gemini. and then there’s specific things people might code with Claude because it’s very good, or there’s other specific areas, but you have the interaction of people with a corporate.

  AI or a business ai.

  Mike: So I, I definitely wanna dive into to your tool, the Baio tool. before I do though, continuing this line of thought is when it comes to kind of the top down and the bottom up and how that works, how. How do you think about, how should mid-size companies think about AI leadership? You know, is it, you know, is nobody [00:21:00] accountable for ai?

  Everybody’s just doing their little part. Is it the CIO that’s accountable for ai? Should there be some new chief AI officer in the organization? I haven’t seen anybody really. on that much at all. They’re just dabbling. and maybe that’s not a bad thing, but how do you think about leadership?

  Chris: If this isn’t run from the CEO, I think it fails. So we said there’s 7% have a strategy. It’s no shock that these projects are nothing more than pilots, and there’s logical reasons why. So, one, if you hunt, and when we’re selling, if I, if we get kicked to A CTO, we’re generally gonna qualify that prospect out.

  Because what happens is you’ve built your career as a tech person by consuming enterprise [00:22:00] software. So you’re part of the sort of software industrial complex. you buy more, you get tickets to games, you go to cool conferences, you, your career is built on the back of, you know, a Salesforce or Microsoft, or an Amazon, which is, I’m not knocking it, that’s just what it is.

  So there’s a disincentive to change and the tech part of the organization has a lot of power right now because they control information in a company. What a Baio platform or AI does, just what we said with your example, it gives back power to people who aren’t technical, where you didn’t know how to write a query or you couldn’t make a webpage.

  You can now do that. So you need the right technology organization to, to roll this out. So I do think there’s gonna be a [00:23:00] chief AI officer. I think it should be the CEO, but I get that they may, you know, instill that or, lean on a person to deliver that. But I don’t think it’s the traditional person who amassed a fiefdom.

  Because this is about outcomes. This is not about more software, more process. It’s generally breaking that down. And my thought when I look at the spend on SaaS applications in a mid-size business, it’s something like the average mid-size business has 50 applications and spends 5,000 per employee per year on these things.

  Yeah. And you start looking at it, and I’ve done it myself. I mean, if you go look at all the subscriptions you have and all these silos of data and all these places where information resides, you’re just, making it harder for any sense to be made of the business. So my vision of the [00:24:00] future is that we start to condense all of that ERPs, in fact go away.

  or the concept of ERP. Most software is a web front end on some data and that yet we stand up 50 of these for the exact same kind of pieces of data. So I really believe it’s a CEO led effort and it’s an outcome led effort. What is your one, two, and three biggest pain point? Solve that, get the right assets in place, meaning people, systems, and data, solve it and then move on and you’ll start to eliminate systems.

  And it’s gonna highlight places in the organization around people that, I’m not saying get rid of people, but places where we can repurpose what people are doing.

  Mike: How do you part of the problem? in leadership of this 

  and I’m with you. If it’s not, you know, I think 

  people think I’m gonna hire a head of HR and they are now accountable for culture. Well, [00:25:00] that’s a line of crap. The CEO has got to be accountable for culture because they model it or they don’t model it. And so, so I think it’s the same thing here where it’s CEO driven, but when it comes to kind of the day to day, week to meet, week, month to month. Ownership of what are we doing and how are we achieving the outcomes using these amazing new tools. 

  One of the challenges is how fast it’s changing, right? Like I, I literally, what was available last week is very different than what’s available this week.

  Chris: You nailed why we built baio. It is way too hard to figure that out. Near impossible. I look at our guys, these are the smartest minds in ai. They changed. Literally, I’ll say, oh, you’re using X to code. Nah, we don’t like that anymore. A week [00:26:00] later, they’re on to something else. And that’s at an individual level where you can kind of understand your preferences and gut check it.

  So imagine a company who makes an investment and has an ROI and wants to look at it and. You can’t just throw something out a week later, let alone understand it. And this technology is not simple. It’s not you. You double click the install button and it just works. chat, GPT and Gemini, and these make it look really simple.

  And it works fine for you as a individual, but when you’re gonna deploy this for an enterprise, it needs to talk to all of your data, your systems. It needs to connect with the people. So. That is an effort. And then underneath that, the technology that makes all that work, to your point, changes every day. I watch what our team changes and I’m amazed at the fundamental things that they change based on what’s better and importantly cost effective.

  ’cause [00:27:00] the cost structures of these are quite expensive in terms of power consumption and compute. So you’re constantly looking for trade-offs in terms of. What’s the right cost structure for the job I’m running? So the point is nobody should have to understand that in the mid-market. ’cause you can’t afford a team that would understand it.

  You couldn’t keep it up to date. If you built it, it’s obsolete in two weeks anyway. So that’s what we said is let’s just solve that problem and then take that, eliminate that from the, from the chess board, so to speak, to let a CEO then focus. Okay, what is the outcome I want to achieve? I know the technology that I’m building it on works, but now I gotta focus on the business problems.

  What is the outcome? What are the options? How do I break down the silos? But the technology isn’t what I’m worried about.

  Mike: So let’s, so we’ve alluded to it a bunch of times, but

  let’s dive into what. 

  What your company does and the product that you offer. So the company [00:28:00] is virtuous ai and the product is Baio. And tell me my, and first off, do I even have that terminology right? that’s the company and that’s the product.

  And then dive a little deep and tell us a little bit more about the product.

  Chris: Yeah. So that’s the company. It was the, the name, which I love, the. The name. Now the founder did his masters in brain computer interfaces. So the name virtuous AI was very important. ’cause if you’re gonna be interpreting brain signals and he was, he did his thesis and in fact built a better, more efficient neural link.

  But if you’re gonna be moving people’s hands, you better have some virtue in, in what you’re doing. If you’re understanding the brain signal and moving. We’ve now taken that and made it a business focus where. it’s a virtuous cycle. So as I get, a learning from maybe customer lifetime value, and then I get cost of goods sold, and then I get, did that customer come back?

  we create [00:29:00] a virtuous cycle of learning that just informs an AI more about your business. so that, that’s how we got to the name and that is the company. 

  We’ve created a category which we call Baio, which is business automation. Intelligence and outcomes, and I’ve stripped ai, AI out intentionally from the name, obviously it’s in the acronym, but, AI I think is table stakes and AI is not, we all think of it as chat, GPT or a large language model, but I really think of it as automation.

  So let’s automate processes in a company. Let’s leverage the gen AI or generative AI LLMs because they’re incredible at human language. But then let’s focus on outcomes. And a lot of the outcomes that we’re going to focus on are machine learned models, which are take all of your data and predict [00:30:00] outcomes from that.

  So what are sales gonna be next year? Turns out most of our customers. It would say, okay, I want to grow the business by 30%. So that’s gonna be sales next year when we use AI and partner with AI to do that and take data from the past and predict the future, those become machine learning models, which is the byproduct of doing the automation and the business intelligence that you can get from this.

  So that’s where we really think the future of this is a platform that does all of that and combines the. Predictive power of machine learning with the deterministic outcomes that business need. So back to the simple example, I’m gonna, pay someone, I need a determined process to pay them so I know they get the right amount, but I may want a more predictive or creative process around that where I can use AI to, to help kind of move.

  Things [00:31:00] faster, but then once I know what to do, I want to execute on it and I don’t wanna allow for any chance, of hallucination or incorrectness.

  Mike: So, and I use two examples

  of larger systems that I used before. Let’s say I am a, you know, a products company and I’ve got an ERP system that helps me manage inventory and financials and all the wonderful stuff, or not so wonderful stuff that an ERP system does. And then I’ve got a CRM to help me manage my, my sales pipeline and my customer relationships does this tool fit on top of and complement those tools? Or at some level, does it replace those tools?

  Chris: Well it sits on top, at least initially. And then for those that see it, they say, why do I have these other tools? And I’ll give you an example. So.[00:32:00] 

  Mike: like a Trojan horse.

  Chris: It is, and I don’t, we didn’t set it out that way, but people just start asking us, why do I have these? So if I flow information through and every business is the same, I have a lead.

  That lead becomes an opportunity. That opportunity becomes a closed won or closed lost deal. Once I win it, I have to deliver it. So a, you know, a project or a process kicks off. Now I have. Cost of good sold in delivering said project. Now I know if I was profitable or not, and that should feed back into the loop.

  Do I want that customer or lookalike customer in the future? So right now I have that data in A CRM, I have it in a inventory management, I have it in a you know, maybe a web sales tool. I have it in five different places. And each one of those is selling you an AI agent that optimizes itself. So I take, we have a restaurant customer.

  If I look at them as an example, I wanna get [00:33:00] people into the restaurant. I wanna make the meal profitable, and then I want them to come back. If I let each one of those optimize itself, we’ll end up, it’s easy to get people in, make it free, but that’s not gonna be profitable. I may. Get people on the table.

  But if they’re not buying profitable items, then I don’t want them to come back. But if these aren’t working together, ultimately that’s the holy grail of letting AI start to go figure out those sort of, the, those sort of processes. But what we do is we build systems that silo those. It’s too complicated for people to think about all of that and replace all those systems.

  And I wouldn’t advocate for doing that. What we say is, we’ll come in, you put a Baio on top. It ingests the data and it’s learning. And over time as you start to think about what is this? Am I, is this system serving me or am I serving it? Because a lot of these say, [00:34:00] morph your process to me. My, you know, I’m a best practice.

  Morph it to me. And so that’s where I think the ERPs start to go away. ’cause again, all they do is they’re gonna manage, and we’ve all said we need one. But it manages that process that I said, and then you have these bolt-ons around it. But really centralized data and a process flow is gonna solve for that.

  And, it’s a way to visualize that on top of it. which again, you said you, you built a web app in a day. AI is really good at building a visual layer on top of information.

  Mike: So you mentioned the restaurant and I’ll let you choose whether they’re the best example, but what would be a good example of, you know, a company that, that you have worked with to implement this tool and give us a sense of kind of, specifically how they used it and the business results

  that they saw. 

  Chris: Yeah. 

  I’m gonna, one of my favorite examples,and I’ll call them out [00:35:00] specifically ’cause I love their jeans. So it’s a company called Muggsy Jeans. I recommend anyone listening, get a pair ’cause they’re athleisure jeans. so very cool. a challenge around inventory. So wanted to better manage inventory.

  The implication is cash. The less I have an inventory, the less that goes stale, the more cash I can do other activities with. So traditional way of managing inventory was take a the sales forecast and then have a top down back into what inventory guesses you would make. AI approach is in take all of your data.

  So in this case, we’re looking at things like Shopify. Amazon where you would sell inventory management, purchase order systems, take that and take a bottoms up prediction. What am I actually gonna [00:36:00] sell? When am I gonna be outta stock on inventory? And then have the system suggest when to replenish.

  So it went from a 70%. Accuracy to, I think they, they’ll tell you 92 to 94% and that is several million dollars in cash available that was not spent in inventory from ai. And this is not a multi-year process. This is a, you know, two to four week process to do something like this. With the key body of work being what is the outcome I want to achieve?

  Better inventory management, better understanding, better sales forecasting. And then let’s connect up that data and get buy in and go execute on it. Now that leads to many other things that came out of that lifetime value of the customer. Who, which emails, are working best? What is my best customer?

  What other, you know, demographics and what other signals are work because [00:37:00] all that data now lives in this corporate brain or this corporate AI that you can start to ask all those other questions, which is what they’re doing now.

  Mike: and back to the wonderful thing, but also the challenge of how fast this technology moves. I, if I am using the Bayo tool within my company and as different as AI has greater and greater capabilities, I is it your team that’s kind of working behind the scenes to make sure. All of those newest capabilities,as, and if they’re important that those new capabilities are kind of entered into the system.

  And then, you know, how does, you know some of those are gonna change processes, I imagine, at the client. So how does that all work? ’cause that as things change, I am, I imagine if you’re not careful, that can become pretty chaotic.

  Chris: Yeah. So one of the challenges with [00:38:00] AI today is that it’s not write? It’s read only. So when you prompt or you get a request back, you’re not really writing to it. you have a point in time of this model or the, this predictive engine they’ve trained. So you’ll notice when you, when you talk to, or you chat with ai, it’s limited in its knowledge of current events, and now they’ll supplement that with internet searches, but they train it on a set of data and then that’s gotta stop at some point.

  What we want to do is create a brain, which is the learning of your company, the sanctioned learning of your company. That’s constantly evolving. And so every interaction an employee has with it or instructions you give it. It’s storing that or writing that. So it now has this pool of information to supplement the technology with, and you can move [00:39:00] that anywhere you want.

  So let’s say a better you now like Gemini instead of open ai or. I for a specific task, I like a different model. The programmers like different things than the business. the accountants, like the point is the platform should be able to move interchangeably, take your, the business knowledge, but ask a different model that’s maybe more purpose built.

  So it’s our job as the technology platform to always have the tools available. It’s your job as the business to make sure the knowledge. Is basically just interacting with the system and then when it’s wrong telling it, no, let’s not do this. this is the way we do it. So what, no matter which model you’re interacting with or which technology you’re interacting with, you don’t even really know or care, but the business knowledge comes with you every time.

  So then you’re never beholden to a model as they change it. You don’t have to [00:40:00] redo all your work because the core learning and the core rules. Are what you’re building as a business, and that’s really what you want to do.

  Mike: Yeah, so it’s back to the idea, I think you said earlier about, you know, this whole thing being outcome driven and so behind the scenes that brain is getting smarter

  because of. Of data from your company, but maybe new capabilities in these different tools. But what I care about is running my business,

  and if I’ve got a smarter brain helping me run it, that’s beautiful.

  But I don’t have to, you know, as the VP of operations, I don’t need to keep up on all the different technology changes. All I know is this AI member of my team continues to get smarter every day.

  Chris: That’s it. And you would say, so if I’m Fortune 10, I’ll probably, I have the budget that I would build this myself and keep. All of that internal and the mid-market just can’t do that. It’s too, [00:41:00] it’s just too difficult. So that’s where we come in. 

  The other thing that I think is really important that should never be overlooked is your data is your IP anymore.

  That’s your capital is that business knowledge. Your processes are what makes your business what it is. And if you just outsource that to. You know these models and put all of that out there. They are training, they’re learning, and maybe not overtly taking, here’s the price of a widget, but the process and understanding that is all training these models for the future.

  So I think it’s absolutely critical and part of what we do is we store all of that privately, so that will never run. And touch. So we’re not gonna send all of your data to open AI or Gemini. And I’m not suggesting they’re being nefarious, but that’s your data and your models. And when you’re, that information should remain in a closed loop [00:42:00] process.

  And when you’re asking for more creative things or web searches, that’s fine because that’s public information. So I think that’s really important as well as part of any of this technology. And that’s why I think a lot of the bigger. Yeah, bigger enterprises will build a lot of this in-house is just to keep it private.

  I actually think there’s gonna be a move back to on-prem over the fullness of time because of that.

  Mike: And give me a sense of what it looks like when you work with a client. Is it. one extreme is, you know, we implement the tool. Good luck. I hope you like the tool, and you leave and they pay you some, you know, monthly subscription fee. The other extreme is, you know, you’re in there consulting day to day and helping them use it better.

  Like where is there a consulting piece of what you do or is it more, Hey, we’re gonna train you on this product and then you’re gonna be able to use it yourself?

  Chris: it’s [00:43:00] more the latter. So we generally embed in a contract and other people could do it different ways, but we generally embed 90 days where we bring in the big brains to help set it up. And that really is, let’s get the data. With you structured and the outcome structured and give you a pattern that you can follow?

  I think over time we, it’s too expensive for me to have a whole team of consultants and keep them at customers, so, so it doesn’t behoove me to, to have a long-term consulting arrangement. And in fact, I want to set it up where the customer can. Own their destiny and we give ’em the tools and they can take it in creative ways and expand it.

  I do think there will be a industry of consultants that help deploy because it is challenging enough and there’s a lot of more, I’ll just say the change management side or the people side of this is probably the harder part. And I think there’s gonna be a big consulting push around that. I [00:44:00] find our team who tends to be more technical, gets pulled into a lot of that.

  And so I think we’re trying to find more and more partners that are industry subject matter experts and business consultants that can help kind of couple this process change or this people change with the technology. Yeah.

  Mike: Yeah, and I think part of the change management, as you said, is I think leaders. Need to find ways to communicate about this, honestly, because the honest truth is there are peoples whose jobs will change significantly. There are people whose jobs will go away. Jobs have already gone away and. That’s not gonna change. And is that a bad thing? Yeah, it’s a bad thing for some people. It absolutely is the same way when any, you know, any new big technology does that. but there are a whole lot of different jobs that spring up now, like maybe these consultants here talking about that, where that didn’t exist before.

  So that, that [00:45:00] is a, it’s not an easy change management, challenge. and it’s an important one.

  Chris: yeah. Yeah. 

  if we bring it back to the, you know, the kind of full circle on the topic in leadership. Who I look for has definitely changed over the course of my career and the biggest change has been in the last couple years in terms of what skill sets I value and, what my expectations are of people.

  Now we’re in the technical side of ai, so you could argue that the absolute bleeding edge of it, but the emphasis I place on creativity. And, curiosity is so much higher than any sort of learned experience from the past. ’cause I think there’s tools that help them with that. Or I’m less concerned with their proven ability to write code than I am with their ability to be curious and creative with something that can help [00:46:00] them write code.

  So, you know, the question I don’t have the answer is, as a leader, how do you one identify the new skill sets? That you’re gonna value. And then two, make people in your organization comfortable that you’re willing to get them there or give them enough headway that, hey, if you don’t wanna embrace that, that’s fine.

  That’s your choice, but This is what the off ramp looks like. But I’m more than willing to invest in you to get you there.

  Mike: Yeah, that’s important. This is, you know, Chris, I’m already thinking about my client list is going through my head of who I need to kind of introduce this to. But if Chris, if someone want, does, want, know more about the company, about the product and how they can go about, you know, taking next steps, where’s the best place for them to go?

  Chris: I think probably our website we have, which I really like as a, an assessment and we, as I mentioned before, we’re less salesy and [00:47:00] more, Hey, is this a fit? And most importantly I found it’s trust building. ’cause you throw a nickel, now you’re gonna hit an AI sales person. So how do you build trust?

  I had a CEO tell me if I’m 95% sure of success in this, I’d sign up today. But I just, I don’t know yet. It’s, there’s just, it’s really difficult to suss out the signal to the noise. anyway, I, we have a free assessment that people can do. It’s not meant to be salesy. I think you can get there from virtuous ai.com and then there’s a link at the top where I think you could take that.

  It goes through a 45 minute workshop, which should lead to whether or not you use our product or something else. It should lead to what would I do as a CEO to implement AI for an outcome.

  Mike: Excellent. And I think we’ve got that link that we’ll put in the show notes. and if we don’t, we’ll make sure of it.

  Chris: Okay, thanks Mike.

  Mike: Excellent. Well, Chris, this was great. You know, I, I. I can go on for another two hours with you [00:48:00] talking about this stuff. It’s so interesting. But I have to get back and code another application in Gemini three, so,

  Chris: I know I wanna send it to me. I wanna see it.

  Mike: but hey,I always say if you want a great company, you need a great leadership team. You know, I think these new tools are such a big part of that. So, Chris, thanks for helping us get a little closer to that great leadership team today.

  Chris: Yeah, thanks for having me on. Mike, thoroughly just enjoyed getting to talk about it with you. 

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