Turning AI FOMO Into Real Business Growth With Peter Kornberg
Peter Kornberg is the Managing Partner of CypherWorks, an AI-first business performance company that helps organizations use AI to drive revenue, profitability, and efficiency. As an entrepreneur and executive with over 15 years of experience driving revenue growth and business transformation, Peter specializes in helping companies apply AI strategically to solve specific business challenges and improve customer experiences. His approach combines AI, customer experience, and business strategy to deliver measurable results.
Here’s a glimpse of what you’ll learn:
[2:14] Peter Kornberg discusses how CypherWorks uses AI to solve critical business challenges and drive growth
[3:33] Peter’s shift from customer experience consulting to an AI-first approach
[6:22] The mindset that separates successful AI adopters from other companies
[9:03] Why AI should target specific business problems rather than serve as a cure-all
[10:13] Peter talks about the Smart Partner Framework for identifying AI opportunities and business impact
[14:22] Building customer experiences around systematic feedback and the voice of the customer
[18:01] The difference between AI dabblers and companies implementing AI strategically
[22:49] Measuring AI ROI through specific use cases, productivity gains, and profitability
[29:14] How businesses can prepare for AI disruption through incremental improvements and proactive strategy
In this episode…
Businesses are under pressure to adopt AI, but many struggle to determine where it can deliver meaningful value. Without a clear strategy, companies risk spending money on AI tools without improving revenue, profitability, productivity, or customer experience. How can leaders move beyond AI experimentation and use the technology to solve real business problems?
Peter Kornberg, an AI strategy, revenue growth, and business transformation expert, recommends starting with specific business pain points rather than implementing AI to keep up with the trend. He suggests identifying measurable problems, determining which functions affect those metrics, and then developing an AI strategy and implementation plan around them. Peter also emphasizes incorporating customer feedback, establishing systematic feedback loops, measuring ROI through specific use cases, and making incremental AI investments rather than trying to transform everything at once.
In this episode of The Customer Wins, Richard Walker interviews Peter Kornberg, Managing Partner of CypherWorks, about using AI strategically to improve business performance. Peter discusses measuring AI ROI, creating customer feedback loops, and preparing businesses for an AI-first future.
Resources Mentioned in this episode
"[Perspective Series] How Personality Coding Helps Businesses Increase Sales With Esther Wildenberg" on The Customer Wins
"Building the Future of Private Markets Technology With Gareth Lewis" on The Customer Wins
"Transforming IT Buying: Authentic Matches With Tonya Turrell" on The Customer Wins
"Transforming Customer Experience Through Culture and AI With Katie DeFeo" on The Customer Wins
Quotable Moments:
“If you understand your customer, you're far more likely to give them what they want and need.”
“It's not, I just want to throw AI at the business and see what sticks.”
“It has to be designed around a real gap, problem, or need.”
“Just hearing them and really listening to them is gold and they will tell you things.”
“You have to actually begin thinking top to bottom, how your business is going to exist.”
Action Steps:
Identify specific business problems before implementing AI: Start by pinpointing clear pain points, needs, and opportunities so AI is applied where it can create meaningful value, making it easier to develop a focused strategy and measure the resulting business impact.
Build systematic customer feedback loops: Regularly interview customers and gather meaningful feedback instead of relying solely on surface-level metrics such as NPS, helping uncover valuable insights about their experiences, needs, and perceptions of competitors.
Move beyond experimenting with AI tools: Develop a structured implementation strategy rather than simply giving employees AI tools and hoping useful applications emerge, helping the organization solve specific problems and build stronger institutional AI capabilities.
Measure AI ROI through specific use cases: Connect AI investments to measurable improvements in productivity, efficiency, revenue, or profitability, making it easier to determine whether AI is producing enough business value to justify the investment.
Adopt AI incrementally and proactively: Focus on targeted improvements rather than committing everything to one technology or solution that could quickly change, allowing the business to adapt as new tools emerge while preparing for future disruption.
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Episode Transcript:
Intro: 00:02
Welcome to The Customer Wins podcast, where business leaders discuss their secrets and techniques for helping their customers succeed and in turn grow their business.
Richard Walker: 00:16
Hi, I'm Rich Walker, the host of The Customer Wins, where I talk to business leaders about how they help their customers win and how their focus on customer experience leads to growth. Some of my past guests have included Esther Wildenberg of Codebreaker Technologies, Gareth Lewis at Helm and Tonya Turrell at TechnologyMatch. Today, I'm speaking with Peter Kornberg of CypherWorks, and today's episode is brought to you by Quik!, the leader in enterprise forms processing. When your business relies upon processing forms, don't waste your team's valuable time manually reviewing the forms. Instead, get Quik! using Quik!.
You'll be able to generate completed forms and get back clean, context rich data that reduces manual reviews to only one out of 1000 submissions. Visit quickforms.com to get started. All right, I'm excited to introduce today's guest. Peter Kornberg is managing partner of CypherWorks, an AI consulting and implementation firm focused on helping organizations turn AI opportunities into measurable business results. An entrepreneur and executive with over 15 years of experience, Peter specializes in revenue growth and business transformation with an AI first but not AI only approach.
He served in various executive roles across three continents. He's led organizations through growth, reinvention, and digital transformation through CypherWorks and Catalyst. Peter helps enterprises implement AI strategies, modernize operations, improve customer experience, which is why he's on the show. He's got a huge background in that and optimizes revenue performance. Peter, welcome to The Customer Wins.
Peter Kornberg: 01:51
Thank you very much. I'm very happy to be here. Exciting.
Richard Walker: 01:54
Yeah. And for anybody listening to this podcast who hasn't heard it before, I love to talk to business leaders about what they're doing to help their customers win, how they build and deliver a great customer experience, and the challenges to growing their own company. So Peter, let's understand your business a lot better. How does your company help people?
Peter Kornberg: 02:14
So CypherWorks is what we call a business performance partner, not a consultancy, not an agency. And what we do is we help especially mid-sized, small and mid-sized companies, solve critical business challenges and needs using AI solutions primarily, but not only so building off of a long history in things like customer experience, product service marketing, and sales optimization and strategy, we combine all those things into these solutions that help move the needle on key metrics and businesses. So most, from my experience working with entrepreneurs, founders, leaders, business stakeholders is that the pain points tend to be very common across businesses, even though they're all in different industries. And we really focus on how do we solve those specific problems in a meaningful and tangible way and actually deliver revenue growth or more profitability as an outcome?
Richard Walker: 03:17
That's awesome. I'm curious, because you've been doing this type of work for quite some time, but AI has really come to the fore in just the last handful of years. When did this click in for you that you said, we've got to be AI first as much as possible?
Peter Kornberg: 03:33
Yeah, it's a distinct thing because for a long time we focused more on CX, customer experience, UX user experience, and in different companies, he's doing a lot of traditional research and design work and strategy, experience, strategy and things like that. The principles were the same now, which is if you understand your customer, you're far more likely to give them what they want and need and have them buy from you and say, buy more and buy longer. And it was successful for a long time, but the emergence of AI was twofold. One was the impact on how we did our work was significant. We were seeing that AI was changing the way that we actually could execute new tools, new technologies across all of our skill sets and design research.
Everything, everything was becoming AI enabled one way or another. So we were able to produce, work differently, faster, better, go deeper, go wider, you know, do a lot of different things in new ways. But also a lot of our clients were asking for it sometimes not even knowing why they were asking for it. Just wanted to know. And one thing that they were asking is part of our framework, which we call smart partner is the top layer of that.
The top layer of, of demand from our clients was just FOMO, which is just nonstop noise and talk about AI. I'm missing the boat. I don't even know what I'm missing or what boat I'm missing. I'm just missing something. What's my competition doing?
What should I be doing? So there's that very high level of yes, we have to know our customer. Yes, our products and services have to work and deliver and so on. All that's good. But could AI play a role?
Could it somehow unlock more opportunity for us or more efficiency or whatever else? So we felt it was really important, so important, in fact, that we pivoted our legacy businesses into a new entity called CypherWorks. We wanted to give it a fresh flavor, which was this AI first, you know, angle. But again, not only because we do a lot more than just AI, but the AI layers where the most attention is and most demand is right now.
Richard Walker: 05:44
Yeah, the noise is incredible. There's a new app every week, every day. There's new features from the frontier models pretty much every day, every week. It's so hard to keep up with. And I focus most of my energy on software development and there's an unlimited amount of stuff to learn there, let alone marketing, sales, all the other places that have this happening.
So I can get that FOMO and that challenge. I'm curious, I mean, if you focused on growth, are you finding that there's a certain style of company that does better with AI enablement than others, like B2B versus B2C? Certain types of products, certain types of sales processes. What are you seeing?
Peter Kornberg: 06:22
So we're not seeing it in terms of types of companies. We see it in types of people and thinking. And it reminds me of, you know, a lot of projects I've worked on in the past where you have certain assumptions. I'll give you one example. We had a telco client years ago that offered a home installation service.
Like you'd get a box sent to you that would have your modem, your, you know, your, your, your phone, everything, all, you know, self install your entire home set up for internet, cable and phone. And it was a disaster before they hired us. You know, nobody wanted to use it. And there were a lot of reasons why, but one of their theories was people didn't, you know, people did not have the technical acumen. You know, technically technical savviness.
And there were these preconceived notions that older people didn't have the technology savviness and younger people did. And what we found was that was not true at all. Either people were technically savvy or they were not. It didn't matter about age. And we've had many, many experiences like that where it's counterintuitive.
So we also came in with the assumption that, you know, SaaS companies, tech companies, fintech companies, you know, leading edge tech companies would be the first to adopt AI and the best at it. It's not the case at all. We find that when someone is open, we think about it this way, which it's not, I just want to throw AI at the business and see what sticks. I want to look at my business and understand how my business works and where AI can play a role. Right.
So you're reverse engineering it that way. So that mindset we find to be most important is that they're still thinking in traditional terms of I need my business to function and perform well, right? Each part of the business has to succeed. How does AI play a role with that? And that curiosity and the ability to, to see it through, to experiment a little bit and to then to implement and to stay on it is really very important.
And some of the biggest companies you work with don't have that, that, that mindset at all. And they're not very good at it.
Richard Walker: 08:20
Yeah. You know, I work mostly in financial services, and I cannot tell you how many times an enterprise has said, oh, we have older advisors or older clients. They won't do e-signature, they don't have the internet. I'm like, really? They don't go to the store and pay with their iPhone the way the rest of us do.
I mean, come on.
Peter Kornberg: 08:40
It's a total myth. Total myth.
Richard Walker: 08:41
Yeah, it totally is a myth. But I think if I'm hearing what you're saying, you're saying when people approach their business, I'm going to use different words, by the way, because this is how I'm digesting this. When people approach their business, how do I improve my business? And oh, by the way, there's different tools and technology out there to apply to it. It's just a different tool and technology to apply, and AI is playing that role now.
Is that fair? Is that what you're saying?
Peter Kornberg: 09:03
That's exactly it, I would say. You know, the only nuance there is that AI is already far more impactful and influential over a business or has the potential to be than probably anything else, you know, since the internet. So yeah, it's just another tool, you know, in literal terms, probably the most powerful one to deploy. But you have to know where and how and when and how far to go because it's not a cure all. And again, if you think about throwing AI at every problem, it feels like a cure all.
And AI is not what it's designed to do at all. It's not very effective at that. It has to be pinpoint. It has to be designed around a real, real gap or problem or need that you can isolate and work on or a set of them that you can put together and make, you know, make sense as a whole. But it has to be done in a traditional framework of solving a problem, a specific problem.
Richard Walker: 09:56
Yeah, I agree. I've always looked at technology as the last choice that you make because you've assessed everything else. And now it's just what's the right tool for the job? If you were to teach the audience, maybe at a high level how to approach this problem, what would you tell them? Like what's the steps that you generally would go through?
Peter Kornberg: 10:13
Yeah. Well, we defined it for ourselves. Other companies have their own way of working. Ours is called the Smart Partner Framework. We even built out our own AI powered diagnostic tool that does the smart partner methodology for free, by the way.
The way we approach it is you think about it like a 4 or 5 layer cake. You know, top to bottom, the top layer is that FOMO layer of I'm not even sure what the problem or need might be. I just feel like I should be doing more than I'm doing right now. Help me figure out where I should focus. That's where a lot of people are, which is totally fine.
The next layer below that is I actually know where my problems are. I know my needs are. There's a difference for us between a problem and a problem like it. My conversion rate on my website is very poor. My churn rate of customers is very, very high.
My retention rate, my lifetime value of customers is too low. Those are specific problems. Needs would be. I know I need a new website or a new app. It doesn't work very well.
So either way you identify with the pain point is where they need pain and gain points. And then from that we try to think about if those pain points, those problems, needs or. Problems, needs or challenges were addressed, what would the impact on the business be? What are the metrics you look at? If we could move the needle on something that would prove the value of the effort you're about to make to change anything, then we look across the functional parts of the business that are impacted by those numbers and by those problems and needs.
So it's sales, marketing, operations, customer success, or anything else. Then comes the strategy. Then comes the implementation plan. So we think of it that way. So I think to kind of give you a more simple answer to your question is look at the business holistically, see where the pain and gain points are.
Zoom in on those and think about if I made the change, what would that change look like? What would it do for the business and how do I actually get there?
Richard Walker: 12:14
When you think about customer experience, are you designing first for the customer or first for the internal user that has to deliver the customer or something else?
Peter Kornberg: 12:24
So there are three different things we look at at the same time with, with, with customer experience. And you think about a Venn diagram with three circles. One is the business and that means business needs, business requirements, business, you know, goals, right? It could be financial, it could be any number of things, people, roles, functions. Then you've got the other circle is the external environment that the business lives in, which is competitors regulation, the economy, any number of things out there.
And the third circle is the customer, the actual user. And all three have to be represented in equal measure to reach a successful outcome. And CX is in the dead center of that. The CX is like the facilitator, the curator, the arbitrator, the balancer of those three things. But its job is to interpret what the business wants and needs and can do with what the customer wants and needs from the business, and what the landscape around both of them actually look like that are affecting how both can behave.
I would say this, though, if a lot of companies rely on those top two, you know, the business and the environment only ignore the customer completely if you don't have the voice of the customer. That's a cliche, I know, but if you don't have the voice of the customer in that Venn diagram, in that conversation, you are almost guaranteed to fall short with whatever the business wants to do.
Richard Walker: 13:56
Yeah, I know. I hear it Quik!. We are. We try to be customer centric in everything we do. And I feel like we still don't hear enough about the customer.
We don't hear enough from them directly in terms of what we're doing or how we could be doing it. And I feel like one of the biggest challenges companies face is how do you really interact and get that information constantly and keep it flowing? What do you see the best companies doing to achieve that?
Peter Kornberg: 14:22
It's actually not hard. That's the weird thing. We it's, it's sort of a non joke in our industry, or at least in our, in our, in our business, which is it feels like magic when we do it for our clients. But it's really very simple stuff. And it's, it's also tried and true.
It's been out there for a long time. Right? And even a lot of the AI solutions have not really tried and true. It is putting in place two things. One is you want to design the experiences with the customer in mind.
So you want to either start with that in mind or later on re-engineer optimized to have the customer in mind. That will save you a lot of pain and suffering downstream. That's the first thing. The second thing is to have a formal, systematic feedback loop where you can capture real feedback, real sentiment from your customers, you know. So on the first one, on the first part of that, for example, we do a lot of customers, but we did a lot of customer experience mapping.
You know, you see, where does the customer start? Where does the customer finish? And you know, what are all the touch points across that journey that the company has to deliver? What happens behind the scenes? What happens in front?
The customer faces very often doing that. It's the first time our clients have ever seen that experience. They've never actually seen it holistically before. So that's that's a gap right there is that they just didn't do it before and.
Richard Walker: 15:43
They've never been their own customer then.
Peter Kornberg: 15:46
Never been their own customer. And exactly. And it's, again, it's not hard to do this kind of work. It just requires the mindset, as I said before, to actually want to do it and do it. It means breaking down silos.
It means people have to let go of some egos and accept the fact that maybe they were not doing the best work. All those things have to happen which require some, you know, some, some political or, you know, social capital inside the organization. But on the listening side a lot of companies will check the box by doing things like a little survey to get an NPS, a net promoter score that might tell you what it's not going to tell you why it doesn't go any deeper. So we tell our customers, our clients, that you should interview your customers routinely. Regularly.
It doesn't cost much. You can, you know, pay an incentive to your customer for a 30 minute phone call or Zoom Zoom meeting. Do some, you know, some longer surveys, invite them in, you know, have conversation, whatever it is, just hearing them and really listening to them is gold and they will tell you things about your business, your competitors, business and everything in between, and they're happy to talk about it all day long. It's gold, so we don't know why more people don't do it.
Richard Walker: 17:01
You know, I honestly feel like that's part of the sales process. If you're not asking the question, what pains do you have? What problems are you solving? How are you solving them before you're missing out on that opportunity here? What's really going on in the world in general?
And then of course, then can you fit the problem or not with your product set? But it's magic when you go back and talk to customers that way and ask them, hey, why, why did you buy this? Is it working out the way that you wanted? Are you getting the results you're after and how are things changing for your business? You know, we're 24 plus years into our company.
And I would tell you we'd be out of business if we weren't doing those things and asking, how can we innovate and provide more value to you over time? Peter, I'm curious if you're seeing trends from all these companies that are afraid of missing out. How do I get AI? How do I use it? Is there a trend in terms of what they're looking to do?
Is it just optimizing processes as an internal tool? Is it customer facing AI interactions? What's the driving force that you're seeing?
Peter Kornberg: 18:01
They come generally in two camps, I would describe it. One is what we call the AI dabblers, which is someone in the company who says we should be using AI. I'm going to get everybody, Claude or ChatGPT on their computer or copilot to start using it. And to an extent, that's empowering. I think that they're, they're asking the companies essentially, you know, self, you know, crowdsource solutions and ideas, but it's relatively unguided in terms of an actual strategy.
They're just, you know, again, I think we have to be using AI. Let's do it that way. So AI dabblers sometimes evolve into what we call the more AI real users, the savvy users, which is they've understood, again, the problem needs a paradigm like we have to solve specific things. Where can we apply it specifically and get serious about it? And then that's when they begin to engage with companies like us.
There are certainly many dozens and hundreds more like us out there, but they get serious about solving a specific problem or set of problems. So on the dabbler side, you don't make a lot of progress. You don't build a lot of institutional muscle. You don't really solve specific problems. The individual employee might for themselves.
By using these tools, they might actually solve a little need they have of being a little more effective, more productive, whatever. On the company level, though, the power users, the real implementers, they've identified, again, their problem in need and they're actively implementing AI solutions. In many cases, automations examples would be very common examples. Data within organizations often lives inside different silos. You have a, you know, sales, CRM, you have marketing, CRM, whatever.
They're not communicating, integrating those different sources of data and then generating a consolidated view for management, a dashboard of all that real time that has a smart layer of analysis that helps them actually. What do the numbers mean? How are they changing? That's a typical AI solution. Not even that hard to do.
So we're seeing when they go for those specific solutions and take it seriously, they're getting a massive bang for the buck. And a big outcome of that is they're seeing an uplift in revenue and profitability without adding headcount. So it's changing their mindset about stuff. It's like, hey, I'm actually working. We're making more money and I didn't have to do the old stuff.
I'm just hiring more people or whatever it's going to be.
Richard Walker: 20:33
Yeah. Okay. There's two topics in there I want to get into. So first of all, if you have dabbled, if you've given out ChatGPT or cloud to all your team members, and some people claim they can't live without it because it's automated, some emails, it's done some tasks for them or whatever. How do you know if there's real value there?
And is it worth the number of dollars you're spending on those seats for all those users to have it? How do you get to that ROI measurement? Should you just pull back, pull it all back and see who complains?
Peter Kornberg: 21:03
Yeah. I mean, you could have a strategy for implementation. That's my answer to that one. And there's another way you have to do it from the ground up to figure this out too, to start it ad hoc and then go back and see if it's working is really tough. I would also question the value.
You know, the individual productivity in use is hard to measure, you know, one person by person across the company. My bigger concern with that is are they trusting the AI tools to do something that maybe they were not designed to do and maybe are not that reliable to be doing? You have secure information, you have HIPAA compliance, you have hallucinations, you know, left and right. I routinely with my AI tools, see that it does make stuff up and it does so very happily. And if you don't, you know, double, double check, have a real quality control mechanism in place, and there's a massive risk that you're making decisions based on faulty information.
So it's really important to get serious about it. I think implementation of your AI, measuring the value of the AI dabbling is, I think, very, very hard.
Richard Walker: 22:08
So I want to think about this from a different perspective. We all have, for example, Microsoft Office, Word, Excel, and PowerPoint. Not all of us use those tools. Not all of us use the tools to their full extreme or capabilities. And you're spending whatever, ten, 15, 20 bucks a month to have that.
Arguably, the company can't live without it. Everybody needs a seat, especially just for email. If you're a Microsoft shop like we are. Does AI fit that? Like, does a ChatGPT account fit that now?
Is it kind of like you have to have it for everybody because they could be using it to get some amount of value and it's just de facto standard. Is that how we look at it? Or do we actually say, are we getting value out of this tool and pull it if we're not?
Peter Kornberg: 22:49
Yeah, I think it's the FOMO layer. And then it's implemented without a strategy. And then someone, some at some point the CFO or the CEO, the CEO, whoever it's going to be, the founder leader says, I have seen no change in the business in terms of revenue or profitability or anything else, but I'm spending X thousands of dollars per month on these tools. So let's pull the plug, right. It doesn't make any sense.
To go back to your question about how you check about the value and impact if you have a strategy while you were talking, made me think of someone. If somebody's job is managing, let's say, contracts, lots and lots of contracts, and they have to look at an old version and a new version. And the old way was highly manual to compare and contrast these two documents. There's a specific use case right there where AI could play a massive role. And you could then say that person went from doing, let's say, ten contracts a day to 100 and, and they're, and they're probably maybe they're leaving at five instead of ten.
So there's a use case there. You can actually apply AI for a modest investment. And then you can track the efficiency gain or productivity gain and profitability gain for that specific role. So again, it goes back to if you have a strategy or an implementation, it's so much easier. Otherwise it is just dabbling and ad hoc.
Which people do, you know, FOMO drives, you know, crypto. I mean, my mom was buying crypto before she understood it. It's like it was just FOMO. I have to go buy crypto. Why?
Why do you have a strategy for it?
Richard Walker: 24:21
Yeah, I, we've done a bunch of lunch and learned and various training to help people get better and better at using the tools, because I don't think that really existed when we started in 23, 24 with this stuff. But it is a challenge. I, I think about it, there are people on my team who cannot live without it for various tasks. Is it worth 20 bucks a month? That's a different question.
We'd have to ask that. So I get where you're getting with that. I'm curious also though, as you see this, there's a lot of companies that have been around for five, ten, 20 years. They have a lot of legacy that want to be AI first. What does that mean to be an AI first?
Now, is it reinventing your whole architecture?
Peter Kornberg: 25:04
So I guess my first answer to that is I've seen these paradigm shifts before, you know, digital first, AI first. I suppose you're setting an intention for the company with that. Not in every case, knowing that that actually means. So I can't speak on behalf of all the companies that say it. Looking back on digital first, it was a promise to meet customers where they were, which was increasingly in the digital space.
To make it less cumbersome. You didn't have to go to the bank branch. If you didn't want to. You could do it online, which you preferred. You didn't have to go to the store.
It could be delivered, whatever. There's that promise there. I think some companies were born digital first. That's just how they are. Others successfully understood what that actually meant and migrated, which is a massive job even for small companies.
Others just said it and then just dabbled. It's the same thing. So I think AI is exactly the same way. I think the difference though is again, like the internet, you know, 30 some years ago, 40 years ago AI is going to be. I do believe it's such a powerful paradigm shift that you can't just say AI first.
You have to actually begin thinking top to bottom, how your business is going to exist in an AI first world, because it's changing how you search, how you buy, how you think about everything you do. There are certainly legacy brands, or I would say there are companies that are more physical in nature, either selling hardware or selling construction materials or whatever else have a little bit less to think about with AI, but we'll still be thinking about it. How to manage inventory, you know, how to manage invoicing, whatever it is. So I think for most companies, at a minimum, they should be at that top layer of the FOMO in our, in our, in our framework of what should I be doing? What does it actually mean for my business in the future?
How do I even think about this as a shift for the business? How do I future proof my business? Because someone could emerge, an AI tool could emerge. It could replace your business tomorrow. Someone can code something that would make your business obsolete, potentially in a matter of minutes.
Right? So I think you have to start thinking about the tangibility behind that statement of AI first. What does it actually mean? Because I think it's lip service right now, which is we'll put an AI chatbot on our website. I don't mean I don't mean to be condescending to companies that do that.
Right? I'm just saying it's a typical reaction if we'll put an AI chatbot. We checked the box, right? We've gone AI for some reason, but it's not. It's not meaningful for the customer or for the business.
Richard Walker: 27:44
I think a lot about it from the customer experience of how, how your decisions end up affecting the customer. And I love talking about one of my prior guests, Katie DeFeo from SunWest Credit Union. And she told a story where they put out one of these chat bots, these AI bots, and it immediately was rejected by their customer base because they're a very in-person type of company. And suddenly it felt like you're distancing us. So they stopped.
They pulled it. They rebranded it, they trained it to be different. And the AI interactions are now, hey, you can talk to a human at any point. We're here. We're just helping you go faster.
Yeah. And I love that story because I think a lot about the experience is the outcome that you're looking for. So I look at how I reduce friction inside my company and outside the company. So everything goes faster and smoother for our customers. So it can come back to should I reinvent our skill sets?
Should I reinvent our processes or our technologies to get there? But it is a really hard thing because you can only do so much at once. And I, I keep I love that you brought up digital first, by the way, because who's heard that term recently? Like it's gone. And I keep wondering, when are we going to stop saying AI first?
When is that going to evaporate? So maybe I can ask you about your view of the future. Where are you seeing things go? Do you believe in the naysayers that it's going to pull all people out of business or kill all the humans, all the crazy talk that's out there? Where do you see this going?
Peter Kornberg: 29:14
I don't know. I don't know, that's the magic question, right? I would say I've several points of view, but no one knows. I also think that no one on earth knows where this is going. Really.
Even those that are building it at scale, you know, the frontier models, I would say that part of me feels like it is like the internet 30, 40 years ago, which is super powerful. A lot of hyperbole, a lot of noise and so on. And then that will dissipate a little bit into more normalcy of life, it just becomes something we have to work with and adopt over time. You know, digital first companies are still transforming into digital companies 40 years later. So I can imagine that the companies will still be adopting AI ten, 20, 30 years for the first time.
I would also say that it has the potential to go so fast and be so transformative that that wave will be very, very short. And for a lot of companies, if they don't transform immediately or even if they do, they might become obsolete. So I don't know. I think it's important to take things in steps and be smart about it and, and try and make incremental improvements and then ride, ride the changes as they come. That is one thing we recommend very often with any investments into AI. You don't want to put all your eggs in one basket because the basket changes tomorrow, right?
So you want to, you know, we tend to work in more isolated, you know, workflows and isolated engagements where we can solve those specific problems. But a new tool could emerge tomorrow. A new solution. It can make it easier. So it's, you know, take it in steps and see. Hedge your bets a little bit.
But I would definitely recommend everyone to be very proactive. Again, you know, have a strategy, look at the business, see where you can make improvements. Always now and forever.
Richard Walker: 31:06
So again, because I spend most of my time in software, I think the future of AI is software that has judgment capability, where right now the problem with AI is it's this wild West. You can go build an agent if you want to do anything you want, but is it constrained? Is it controlled? Is it governance controlled? Do you know what it's doing?
And software enables you to do that. Close the loop around it and control it better. So I think one of the biggest trends is to build software that now includes the ability to make judgment and decisions or, or help you make better decisions faster because AI is in that mix, but highly constrained. We'll see. I mean, it's a fascinating time to be alive, isn't it?
Peter Kornberg: 31:47
It's incredible. And I have to say, for me and for my partner, it was the emergence of AI that gave us the juice and gas in the tank to really go for business again. Right? We had legacy businesses. And I wouldn't say we were coasting, but it didn't feel exciting anymore.
It felt more routine. And this we had this epiphany of, it's not something to be afraid of. It's actually super exciting. It is daunting and challenging, but it's such an exciting thing to be a part of and has so much potential. And it frees us to try new things.
And we're seeing that. It's nice that the rest of the world feels the same way, because we're finding people that want to have that conversation with us and do work together and solve problems together. So it's incredibly exciting, I think. And I, and I, by the way, just to your point about intelligent software, reactive software, we, I don't know if that's I hadn't thought of it that way as like the future necessarily, but certainly an intelligent partner is how we think of it as well. Our smart partner tool is designed to be that, and it's based on our own proprietary rag layer.
You know, our content is our content. So it's not just pulling stuff from the internet. It's designed to be like your sidekick as a business leader is. I need to answer questions about problems, needs, and solutions. I can use this tool.
I can, I can have a conversation with it and will give me advice and guidance based on real information. And then I can, I can take that and do something with it. It's pretty cool.
Richard Walker: 33:18
Man. Yeah, I agree with you. I think that it's a boon for entrepreneurs and founders. I mean, I have had my business for decades and yeah, I've gone through burnout and stuff. This reinvigorated all of us with so much more ideas and speed to do things and capabilities we didn't have or couldn't afford.
Oh man, it's so much fun. Look, I have to wrap up the show before I get to my last question. What is the best way for people to find and connect with you, Peter?
Peter Kornberg: 33:45
I can be reached at peter@cypherworks.co, and that's cypherworks.co. That's the easiest way.
Richard Walker: 33:55
Awesome. We'll put the link in our show notes as well. All right. I love to ask this question, who has had the biggest impact on your leadership style and how you approach your role today?
Peter Kornberg: 34:07
So I would say my former partner Mona Patel, was a big influence on me. We were really strong partners for a long time in our previous business. And her impact on me was that we were so opposite in how we looked at business and looked at the world in many ways, but I learned so much from how she looks at things in terms of. The openness, the rapid iteration, the inventiveness, the boldness, the tough love approach to running a business, never saying no, you know, even when you should just have a whole mindset. It was a, you know, a very influential and powerful person in terms of impact on me for sure.
And a lot of fun to work with.
Richard Walker: 34:55
I love that. I love it when people challenge you in the right ways. All right. I want to give a big thank you to Peter Kornberg, managing partner of CypherWorks for being on this episode of The Customer Wins. Go check out Peter's website at cypherworks.co.
And don't forget to check out Quik! at quickforms.com, where we make processing forms easier. I hope you've enjoyed this discussion. We'll click the like button, share this with someone, and subscribe to our channels for future episodes of The Customer Wins. Peter, thank you so much for joining me today.
Peter Kornberg: 35:25
Thanks. I appreciate it. A lot of fun.
Outro: 35:28
Thanks for listening to The Customer Wins podcast. We'll see you again next time, and be sure to click subscribe to get future episodes.
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