AI Turns Brand Valuation Into a Quarterly Management System

GovernanceData
Written by Christina Ellwood

Episode Summary

Hampton Bridwell, co-founder of CorebrandAI and CEO of Tenet Partners, explains how his team used AI to turn brand valuation from an annual report into a management system leaders can use quarter in and quarter out. Brand valuations tend to be delivered in a PowerPoint and shown to the board once a year; CorebrandAI turned 30 years of phone survey data into a statistical model and synthetic personas by industry, moving from 400 survey responses per company per year to daily coverage of more than 1,000 companies. He walks through the four ISO-aligned valuation methods the platform weights by industry and by client, why the valuation engine stays deterministic while AI generates the insights built on it, and how the platform turns the valuation into a playbook for management. He also explains how the platform bounds its AI, and why familiarity, discoverability in AI platforms and every member of the C-suite drive brand value.

Key takeaways

  • Start with the data you already hold and a business objective. Hampton Bridwell says getting a handle on what data you have, and then reimagining how it might be used with AI’s compute power, is really the best place to start, and that it always begins with a business objective.

  • Value a brand through more than one method. He compares it to a home appraisal, where one method is okay but looks through probably too narrow a lens, and CorebrandAI uses four ISO-aligned methods.

  • Give brand value the kind of management system other assets already have. He says most assets on and off the balance sheet have a mechanism within management for overseeing their value, the capital put into them and the returns expected, and that brand has never had one.

  • Keep the valuation deterministic and use AI around it. He says CorebrandAI’s valuation engine is not a guessing engine and does not use AI to render the valuation; AI-based methods are among those that generate some of the data, and the inference is built on top of the valuation.

  • Bound the AI inside your product, and flag when it is asked to step outside. CorebrandAI’s chat lets clients work with the platform’s data on their own valuation and their competitors, and he says the system puts up a flag whenever it is asked to go outside and use the LLM to generate insights.

  • Isolate the agents that gather outside data from the application your clients log into. He says the systems that scrape and search the web are kept apart from the application because attacks can come in through those data sets, and that the agents within those systems do not interact at all.

  • Point AI at a specific business problem and build the context around it. He says it is hard to solve a complex problem by going straight into Claude or ChatGPT, and that you need a system and an approach focused on the business issue you are grappling with.

  • Treat discoverability in AI platforms as a driver of brand value. He thinks discoverability is one of the new features of brand, where a tremendous amount of value can be created, and says discoverability in AI platforms is now the number one issue everyone is grappling with.

  • Recognize that every member of the C-suite drives brand value. He says marketing plays a huge role, and so do the quality of a company’s people and the quality of its operations and execution.

  • Track reputation alongside brand, because it moves faster. He says reputation can be destroyed much faster than brand, which is a fairly slow-moving asset, and that this is one of the reasons CorebrandAI includes reputation in the platform.

About Hampton Bridwell

Hampton Bridwell is co-founder of CorebrandAI, where he leads AI engineering, product design and market development for the platform, and CEO of Tenet Partners, the brand consulting firm he has been with since 1994. CorebrandAI builds on the brand valuation work of Jim Gregory, whose company he went on to buy. He has worked in brand strategy and brand valuation for 30 years and, for the past 8, in machine learning, natural language processing and generative AI. He was formerly CEO of SkyReserve and a board member of Brandlogic.

 

In this episode

00:00 Welcome and introduction
01:54 From phone surveys to a statistical model and synthetic personas
03:58 Where to start with the data you already have
05:45 Brand value as the basis of a management system
06:31 Why use four brand valuation methods
08:57 Why brand has never had a management system
11:36 How AI generates insights from about 20,000 to 30,000 data points a quarter
12:47 Connecting the platform to company systems through an MCP server
13:51 Building the first version with AI in about a month
15:00 From an annual PowerPoint to a playbook for management
15:53 A deterministic valuation engine, not a guessing engine
17:20 Why the platform runs on public data
19:10 Governance: bounding the AI and protecting personal data
22:24 Isolating the agents that gather outside data
23:06 Advice for executives building their own AI systems
24:56 What drives brand value: familiarity
25:16 Discoverability in AI platforms
25:56 Everyone in the C-suite drives brand value
28:16 Where AI is taking brands, from recommendations to agents interacting with agents
30:11 How reputation differs from brand
31:27 Reputation can be destroyed faster than brand
31:50 Strategic foresight at scale
33:32 Resources, the Reuters event and 51 industry reports
36:53 An open, curious mind

In his words

“We really see brand value as the basis of a new management system for management teams.”

Hampton Bridwell

“It is a deterministic engine. So it is not a guessing engine. It is not using AI to render the brand valuation.”

Hampton Bridwell

“Many folks have seen brand valuations, but that tends to be delivered in a PowerPoint and it’s something you put on a shelf or hold up as a trophy in the room and at a board meeting annually and then it’s put away.”

Hampton Bridwell

“It’s hard to just go into Claude or ChatGPT and solve a complex problem right out of the gate.”

Hampton Bridwell

“The other message from our team is that everybody in the C-suite drives the value.”

Hampton Bridwell

 

Resources

The guest

Ideas and terms discussed

  • Capital premium method: The original CoreBrand methodology, which assigns a percentage of market cap to brand value

  • Royalty relief: A brand valuation method that asks what a company would pay to license its brand back to itself. Hampton Bridwell says Brand Finance created it, and that David Haigh, along with others, shepherded it in the early days of brand valuation

  • Earnings attribution and demand attribution: The other two of CorebrandAI’s four valuation methods, which look at how a brand drives cash flow and how it drives demand

  • Corporate Branding Index: The measure of favorability, familiarity and other brand dimensions that CorebrandAI continues to update for every company it covers

  • Synthetic personas: Models of executive sentiment by industry, built from 30 years of phone survey data, that let CorebrandAI continue the survey at a scale it never had before

  • STEEP plus G: The futures framework Hampton Bridwell names for strategic foresight, which AI can now run at scale. He lists social, technological, environmental and political issues, and governance

Also named on air

  • The CorebrandAI industry reports: Snapshot reports on all 51 industries CorebrandAI covers, available through corebrand.ai or by email to Hampton Bridwell

  • Reuters Events: Strategic Marketing 2026: The one-day event for CMOs and senior marketing leaders in New York on 16 November 2026, where Hampton Bridwell says CorebrandAI will be showcasing its work and hosting roundtable discussions

  • Jim Gregory: Hampton Bridwell met him 25 years ago and went on to buy his company

Related AI Realized episodes and events

 

Frequently Asked Questions

  • CorebrandAI values brands with four methods, each an income-based or market-based approach: capital premium, royalty relief, earnings attribution and demand attribution. Hampton Bridwell, co-founder of CorebrandAI, compares this to a home appraisal, where his father, a real estate appraiser, used multiple methods: one method is okay, but it looks through probably too narrow a lens. Capital premium, the original CoreBrand methodology, assigns a percentage of market cap to brand value; royalty relief asks what a company would pay to license its brand back to itself; earnings and demand attribution look at how the brand drives cash flow and demand. All four are ISO aligned, and the platform weights them by industry and by client.

  • Companies have not managed brand value like other assets because there has never been a system of management associated with it, and brand valuation has not been well understood. Hampton Bridwell of CorebrandAI says most assets on and off the balance sheet have a mechanism within management for overseeing their value, the capital put into them and the rates of return expected. He says ISO standards over the past 10 years have changed how brand valuation is understood, but a gap remains between valuing a brand and knowing which components to invest in and at what hurdle rates. CorebrandAI’s answer is an engine, which he says the company has put a patent on, that turns the valuation into a playbook management can use quarter in and quarter out.

  • No, CorebrandAI does not use AI to calculate its brand valuations: they come from a deterministic engine, though some of the data feeding that engine is generated with AI-based methods. Hampton Bridwell, co-founder of CorebrandAI, says it is not a guessing engine. After the valuation, the engine pulls the valuation forward into an inference system with modules for reputation and image, the Corporate Branding Index, foresighting, and crisis simulation for the value at risk if an issue hits the company.

  • CorebrandAI values brands from public data because it is easy to access, and clients are challenged when it comes to giving firms access to their own data. When Christina Ellwood describes the platform as running on public data, Hampton Bridwell of CorebrandAI gives ease of access as the reason, and says that for a company of CorebrandAI’s size, doing brand valuations with lots of client data is too difficult. He says public data also gives clients a more real-time view of their companies, rapidly and at a scale they have not had before. He agrees when she adds that brand is by nature an external measure.

  • One way to govern AI in an enterprise application is to bound what the AI can do, strip personal data before it enters the system, keep core outputs deterministic, and isolate the agents that gather outside data from the application users log into. Hampton Bridwell of CorebrandAI says the platform’s chat lets clients work with the platform’s own data and flags any request to go outside and use the LLM to generate insights. CorebrandAI is hosted in Ireland to meet EU standards, follows GDPR and scans incoming data, such as its real-time sentiment scrape, to strip out names and other personal information. Its valuations are deterministic, so the number does not change each time the system runs, and the systems that scrape and search the web are isolated from the application clients log into, because attacks can come in through those data sets.

  • Familiarity is the main contributor to brand value in the view of Hampton Bridwell of CorebrandAI, who calls advertising, communications and building exposure the single greatest lever a company has. He thinks discoverability is one of the new features of brand, where a tremendous amount of value can be created, and says discoverability in AI platforms is now the number one issue everyone is grappling with, because problems are being solved and recommendations made there. He says everyone in the C-suite drives brand value, not only marketing: the quality of a company’s people, its operations and execution, its financial controls and governance, and its leadership and voice in its markets all play a role.

  • One difference between brand and reputation is speed: reputation, which describes what a company stands for, can be destroyed much faster than brand, which is a fairly slow-moving asset. Hampton Bridwell of CorebrandAI says the two are slightly different but deeply interrelated, and that a well-managed reputation makes a difference in finding talent, operating in communities and giving people confidence in a company’s oversight and governance. He says this is one of the reasons CorebrandAI includes reputation in its platform, so clients can see how reputation and brand interact.

  • Companies can use their proprietary data with AI by first getting a handle on what data they have and then reimagining how it might be used with AI’s compute power, beginning from a business objective. Hampton Bridwell, co-founder of CorebrandAI, says rich data sets offer a tremendous opportunity to train AI and to analyze new sources of data or change how data is collected. CorebrandAI took 30 years of phone survey data from corporate executives and managers, built a statistical model and synthetic personas by industry, and moved from 400 survey responses per company per year to daily coverage of every company in its database, more than 1,000.

 

  • [00:00] Christina Ellwood: Welcome to AI Realized, the podcast for enterprise executives leading AI adoption. From tackling security, data, and operational challenges to navigating organizational transformation, AI deployment offers a unique opportunity to redesign organizations from the inside out. I’m Christina Ellwood, your host for today’s episode. Brand is one of the most valuable assets a company owns and one of the hardest to measure. Today’s guest and his co-founder took 35 years of brand valuation methods, data, and expertise and built an AI platform that expands the valuation models and data sources behind them for deeper insights into what a brand is worth and what drives it. He’s gonna share how they architected it, what that means for leaders building AI systems of their own, and what the platform reveals about brand value. Hampton Bridwell is co-founder of CorebrandAI and CEO of Tenet Partners. Hampton, welcome to AI Realized.

    [01:00] Hampton Bridwell: Nice to be with you, Christina

    [01:02] Christina Ellwood: Well, CoreBrand has 35 years of brand valuation, methods, data, and expertise behind it. What did AI let you do with that foundation that you couldn’t do before?

    [01:12] Hampton Bridwell: That’s a great question good place to start. I would say that, starting February this year, we really saw a difference in what the compute power associated with AI was gonna provide to us specifically for the work that we were doing. And it’s really about generating a level of contextual understanding about a company, its competitors, its industry, at a scale that we just have never been able to do before. So primarily, brand valuations were done in Excel spreadsheets and using survey data that was fairly static and now AI gives us compute power that we just frankly never had before.

    [01:50] Christina Ellwood: And it sounds like some new data sources too.

    [01:54] Hampton Bridwell: Very much the data sources that drove our models for the past 30 years were primarily, of all things, phone surveys with corporate executives mid-level managers in companies across the US. And what we did was move from this whole concept of, using a telephone-based survey, but we did take all that data, 30 years of data, built a statistical model, and then synthetic personas by industry that allows for us to go way deeper and gain a better understanding of what’s happening in the industry at any particular point in time, how executives have sentiment towards their own industry as well as others, and the companies within those industries. And so using the statistical model and machine learning, it allows for us to essentially continue the survey quotient, if you will, behind our model and but do it at a, again, at a scale that we just haven’t been able to have before. So as an example we moved from, doing 400 responses per company per year to doing every single company in our database, over 1,000, on a daily basis.

    [03:07] Christina Ellwood: Wow. That’s a huge difference, isn’t it? But that foundational data is really important, and a lot of enterprises are holding decades of proprietary data and methods that they might wanna know how they could leverage their data sets as well. What do you advise for them?

    [03:24] Hampton Bridwell: Yeah, it’s it is a challenge because I think a lot of people see AI as the shiny object and just using training data alone will solve, what they’re trying to do from a data perspective. And I guess we really saw it from a dif-different angle, and that, companies have rich data sets. They offer a tremendous opportunity to train AI and to then use that compute, compute power to analyze new sources of data or to even reorient how you’re collecting data than, that you have been before. So I, I-- Just getting a handle on what data you have available to you and then reimagining how it might be used in the context of this compute power is really the best place to start. It always begins with a business objective a deeper understanding of, what you’re trying to accomplish. But if you have rich data sets, it’s really a, it’s a great place to start.

    [04:23] Christina Ellwood: And you r- are right to use this term of reimagine because that’s really what-- From what I can tell I’m familiar with the original CoreBrand brand corporate branding index and the work- ... that was done under Jim Gregory in the original instantiation of CoreBrand, and it seems as though you have really reimagined how it can be done, what should be included how to rationalize the different methods, ’cause you actually use multiple valuation methods now, don’t you? In fact, I was reading your analysis of SpaceX the IPO the pre-IPO work and the pre-IPO work for Anthropic. And your analysis of the SpaceX, as I recall gave of the trillion seven, $1.7 trillion valuation that was the pre-IPO valuation for SpaceX, you attributed, as I recall, about 91 billion to their brand. But it was across four brand valuation methods, and I’m not familiar with all four of them, and my guess is that most of our listeners aren’t either. Most industries have some type of benchmarking method that is used, so I’m curious about the methods that you’re using and why you pick those, and how blending or combining, four of them into some kind of meta-analysis is changing what you’re able to provide for guidance on brand value to companies.

    [05:45] Hampton Bridwell: Sure. I-- There’s an important arc here, and I’ll start with that first, is that, we really see brand value as the basis of a new management system for management teams. And in order to facilitate that conversation across the whole C-suite and with the board There needs to be an approach which makes sense to management teams, and to have deterministic values that can be relied upon quarter in, quarter out, and then translate those into such a way that you can look at the components that drive brand value through different lenses, different valuation models, and then pull those through into deeper insights, and then all the way through to action on what should a management team do. So why four different brand valuation models? And I always like to say it’s no different than getting a valuation done on your home, an appraisal. My father was a real estate appraiser, and he used multiple methods. And so he-- It’s no different here in that using just one method is okay, but it looks at it from probably too narrow of a lens. And so the four methods are a little different from each other in as much that they are all ISO aligned but they look at it from either an income or market-based approach. And so the four methods that we actually call capital premium method, which is the original core brand methodology that assigns a percentage mark-- of market cap to a brand value and and to, to arrive at that that, that number. And then the, the second is royalty relief, which was created by Brand Finance out of the UK, and super high quality firm, and David Haigh shepherded that along with others in the early days of brand valuation. And that really looks at if you had to license your brand back to yourself, what would you pay? And so royalty rates handle all kinds of transactional activity and is a very good method for that. And then other methods are earnings attribution and demand attribution. And so Looking at your brand through different lenses, what’s the premium that the market is putting on your company? What it, what your brand might look like from a licensing standpoint? How is it driving cash flow, and how is it driving demand? So we use those four methods and a weighting system that allows for us to essentially derive values in real time using those four methods, and then weight them according to what we think is best for that industry as well as the client.

    [08:30] Christina Ellwood: Yeah that’s a great explanation. And I think there are parallels for other industries. So you couple these deep repositories of proprietary data with standard methods for doing analytics, and you create some new ways of gen-generating decision criteria inside of the company. So you mentioned that you envision management teams, the s- the C-suite and the board using the, these brand valuations as a management tool. Can you say a little bit more about that?

    [08:57] Hampton Bridwell: Yeah. You know what? The, the primary gap that’s been missing from this whole area of brand value is that there’s really never been a system of management associated with it. So if you think about all the assets on the balance sheet and the things that are off the balance sheet, like a brand most of them have a mechanism within management to oversee the base value of those, how much capital are you gonna put into it? What do you expect to get out of rates of return and so forth. And the brand is, an asset that typically represents anywhere from, on average seven and a half to 10%, and it can go up, dramatically from there for consumer brands and be much lower for companies like that might be a utility, for example. The-- That gap that’s existed is primarily been because of a, a lot of hesitation around what bra- brand valuation is all about, and it’s not well understood. And that’s really changed over the past 10 years with ISO standards coming into place, both at valuation, evaluation methodologies. And but there’s still a gap that goes from how do you actually take the system of brand valuation and then move it into a deeper understanding of how you drive growth, how you actually oversee it, what are the components that you should invest in, what would be reasonable rates of return and hurdle rates associated with making those investments and what you can get out of it. So we know, quite clearly that brand is a contributor to cash flow, and the cash flow multiple is a really good component of that. So Jim Gregory did a lot of this work with Brad Puckey and, in ironing out a lot of these kinds of concepts. And what we’ve been able to do now with this platform is bring in a much richer data set as well as the methodology that ties it all together from the brand valuation and understanding the components of it, and then moving it into a deeper intelligence that helps to understand the industry, the company, and where the opportunities lie, and then distill it into a playbook that management can use quarter in and quarter out. So that, that entire engine, and that’s what we put a patent on and, so The premise there was, how do you tie all that together? And that was really the basis of building CoreBrand.

    [11:27] Christina Ellwood: I see. And is-- does AI play a role in that operationalization and in that brand or in that corporate di- decision guidance too?

    [11:36] Hampton Bridwell: It does, actually. So much of the insights that we’re generating across the platform are using inference. And so the data that we’re pulling in for that company and its competitors that’s probably between 20 to 30,000 data points per quarter. And when that allows f- along with all the training of the LLMs, that allows for us then to use the brand valuation as the cornerstone, and then understand the corporate from a corporate branding index perspective, all the components that drive into favorability and familiarity and culture of innovation. We use Google data to give us an understanding of search and search trends as well as AIO and visibility across the search eng- or excuse me, across the LLMs, and price premiums and price differentiation in the marketplace. And so all of those we can essentially then move through the engine pull it apart, understand what’s driving the value, and then from there, the engine actually can pull and create inference for each of those attributes on what management teams should do.

    [12:47] Christina Ellwood: So if I were thinking about this from a, a operational point of view Hampton would this-- would the CoreBrand platform be connected, say, through an MCP server or something like that to the systems of record for marketing sales and maybe finance?

    [13:05] Hampton Bridwell: Yeah, that’s exactly how we’ve architected it. And so companies can basically take their systems that they have available to them, many, implementing their own internal LLM Claude or, OpenAI, ChatGPT, similar. And and so they s- teams across the company essentially can ask questions of CoreBrand and be able to get answers back that relate to the brand. And so that corpus of knowledge we actually pull into a, a cache and sit that into memory, and then it’s available through the m- MCP to, anybody across the whole company. So that’s-

    [13:44] Christina Ellwood: That’d be a goldmine for product too. So walk us through how you architected the platform.

    [13:51] Hampton Bridwell: It started in a kind of a classic sense both from an entrepreneurial perspective as well as like a, a innovation and engineering approach. So I sat down with the team this past, December, January timeframe, and from there we built an MVP. We used AI to essentially do the prototyping of the application itself. So we fed in all of the valuation models that we have available to us. We c- took the datasets that we have. We built the machine learning and synthetic models, and we did all that basically in a matter of a month using Claude to basically help us build up the MVP. From-- Once we had the MVP, we started to share it with clients. We sat with clients, we showed them what we had built, and in, in particular one client we were in the middle of doing brand valuations for, and they were just completely blown away. And in subsequent conversations with clients, people just had never really seen anything like this before. They had-- Many folks have seen brand valuations, but that tends to be delivered in a PowerPoint and it’s something you put on a shelf or hold up as a trophy in the room and at a board meeting annually and then it’s put away. This idea of moving from understanding your company at this level and understanding the asset at this level, and then pulling it all the way through a, a playbook for management, that had never really been created before. So folks got really excited, cus- our clients were super excited about it, and that convinced us to move to the next level of the build. So from there it was, a very stringent build process to make a multi-tenant application and using the tools of AI to accelerate that build process and then understanding where we were gonna use AI and where we weren’t. One key thing with our application is that the brand valuation components, while it uses data that is generated using a, a variety of methods including AI-based methods and data sources it is a deterministic engine. So it is not a guessing engine. It is not using AI to render the brand valuation. It is fully deterministic. What happens though from there is that the engine does, as I made mention, pull all that forward into, a full inference system. The modules that move across this include reputation and image the corporate branding index with all of its dimensions that are there. We also have a foresighting module which helps us understand futures for a company and what scenarios might play out. Scenario system where it has crisis simulators from a PR standpoint and looking at what might happen if there’s an issue associated with the company and what kind of br- value risk is there. And this, this idea of pulling both value as well as risk management and opportunity forward into the management system that comes out of it. So all of that is from an architecture standpoint, fairly complicated. Many hundreds of thousands of lines of code to build it, all hosted on AWS and in a multi-tenant environment that’s fully secure and GDPR compliant as well.

    [17:20] Christina Ellwood: And the platform runs entirely on public data, as I understand it. And what does that make possible for your client?

    [17:27] Hampton Bridwell: It’s easy to access. That’s really what it boils down to. Clients, I think, are challenged when it comes to their own data and allowing firms access to that data. And really, for a company that is relatively, small for in the context of, say, Microsoft or Oracle or companies of that nature that have access to client data, for us to be able to do a brand valuation and use lots of client data is just too difficult. And as well as the other insights. And then the other reason that’s really great here is that it gives clients a perspective on their companies that in more real time that they just have never been able to access before. And so they can do it rapidly, it’s easy to access, and it’s scale that’s, again, that’s not been available to them in this-

    [18:21] Christina Ellwood: Yeah, ’cause they don’t have to integrate internally. But also brand by nature is an external measure. It’s not an internal measure anyway. So in some ways it’s more naturally suited to using that external data, isn’t it?

    [18:35] Hampton Bridwell: It is, very much and, it’s making it, again, this easy for them to access and to be able to quickly have this as a tool in their toolkit and helping, stakeholders across the organization understand the asset and really move it forward rapidly. As a management system, again, this is what people are excited about.

    [18:55] Christina Ellwood: You built CoreBrand with governance as a first principle, so you architected from the beginning for it to be a a governed and compliant system. What does that look like in practice?

    [19:07] Hampton Bridwell: There are a couple of dimensions to that. The first is understanding of the AI compliance and essentially what we would allow and not allow to happen on the platform itself. And so there are boundaries that we set from an AI management system perspective where, we have a chat service inside of the platform that allows for you to in- interact with the corpus of data around the competitors and your own valuation. But we don’t allow the system to go outside and use the LLM to, just randomly generate insights. And so anytime that happens, our system actually puts up a, a flag and says, “Hey, I’m being asked to step outside of the system. I’m gonna let you know that’s happening and then we’ll, go from there.” So making sure that clients have confidence in the system and that the AI that they’re interacting with in the system is bounded was an important first step. So that level of governance is incorporated into the system. And then the, the other areas that we focused on was privacy and GDPR compliance. So this-- we, we’re hosted in Ireland to meet with EU standards. And then we adhere to all the GDPR requirements. So we look, we scan all the data coming in for any sensitive personal identification or PII, and then, making sure we strip any of that out that might come into the data. And so our-- for example, our pulse goes out and does a, a scrape for real-time sentiment across the industry and the companies that we’re, you know, reviewing. And when we come across any names of people or anything of that nature, we strip all that out before it ever enters into the system. So that kind of, scanning and data quality really matters in protecting privacy. So those are a few examples. It probably goes deeper than that, but we’re, very interested in that part of it. And then the last part from a governance standpoint inside the company is making sure that the valuations themselves were deterministic. So that is you can’t get a different number every time you open the system and run it.

    [21:23] Christina Ellwood: Yeah. That’s probably the most critical component of your governance model from a value to the customer point of view. But- ... these other elements are i- important from a, guardrails sort of concept, right? So how do you govern the agents themselves given that they have some autonomy?

    [21:40] Hampton Bridwell: The we actually have s- a whole separate set of systems that are isolated from the application itself that clients log into daily and are using to gather in- insights and look at the data. Those systems actually are the ones that go out and do the scraping and are pulling information into the system. We also keep it separated for the brand index as well and the ongoing corporate branding index data that we’re pulling forward on every company. And so that goes through a rigorous quality check month in, month out. So we’re looking at essentially how that data looks, how the synthetic personas are performing, and making sure that the quality controls are associated, just bounded around that specific activity. And the same when we’re doing web searching as well, ’cause you can have attacks that come in through those data sets, and we didn’t want to allow for any of that to get close to, a client and them logging into their own system. So those are isolated and and the, the agents within them don’t interact at all.

    [22:45] Christina Ellwood: So what does the way you architected and built CorebrandAI mean for executives who are building their own AI systems? What are the takeaways for the listeners on the podcast that- ... that are trying to build their own systems?

    [23:00] Hampton Bridwell: I think that the, the key is all about experimentation and having an innovation mindset. So that, for me, I think is where you have to begin. And that’s, identifying where there’s a problem, where you can use this kind of compute power to solve a problem that perhaps you’ve never been able to tackle before. And just, it’s hard to just go into Claude or ChatGPT and solve a complex problem right out of the gate. You need to be able to build a system and an approach that takes that compute power, uses what’s there but really is focused on the business issue that you’re grappling with. And the reason why that matters, I think, so much and why our system performs the way it does is because of context. We use machine learning and lots of data and all the, you know, aspects of like building off evaluations and everything, but really even the evaluation’s a very thin part of this. It’s the, the context that we’re building that’s so specialized in this area that, that makes it, really special and perform at a high level. So that would be the last, part of advice that I would give folks is that when they walk through the door looking how do you solve a business problem, but then from there, using AI in the way that it really does perform best and for us, understanding the context of the the material that we’re sorting for, the issues that we’re sorting for really made the difference.

    [24:36] Christina Ellwood: So you’ve been in brand your entire career. Your work at Tenet is about helping companies to build and shape their brand and value their brand, keep their brand value up, elevate that. And your work at CorebrandAI is, of course, in helping people to operationalize the brand and make better decisions. What are the main contributors to brand value?

    [24:56] Hampton Bridwell: Yeah. I think one of the things that, the main contributor is familiarity. People that know your brand that drives a great deal of value. And the role of advertising, the role of communications and building exposure for your company is the single greatest lever that you have available to you, period. And what’s interesting now is that discoverability is actually, I think, one of the, the new features of brand and where a tremendous amount of value can be created. And where brands are really, it is a tough battle out there because in just about a year, discoverability in AI platforms is, the number one issue that everyone is grappling with because problems are being solved there and recommendations are being made on how to solve those problems, including, the solutions that lots of companies put out there in the market, or products or services or all kinds of things. Along with, helping people to see that you’re there, discoverability is one of the big drivers. The other message from our team is that everybody in the C-suite drives the value. And I think there’s a l- been a long, long tail on the point of view that it’s just marketing. And yes, marketing plays a huge role in what happens with creating brand value and driving growth and revenue and profitability and differentiation in markets and all those things. But the other folks in the C-suite have a role to play, too. The quality of the people that work at the company, the quality of operations and execution day in, day out. Its financial controls and governance. Its leadership and its voice in markets and within its industries. So these things they play also key and central roles in how well a brand performs and sustains value over time. And what we’re, driving towards is helping everybody in the management team see the role that they play and what kind of value they specifically can contribute to the growth of brand value.

    [27:05] Christina Ellwood: That’s fantastic. And I couldn’t agree with you more that it is it has been underplayed in the C-suite. And so I think it’s great that you’re giving them the decision tools to be able to understand that and to make better brand decisions. It even goes all the way to the customer experience, of course, and AI commerce- is coming into play in a big way. I think in the next 12 months, that’s gonna be the biggest shift that we’re gonna see from a brand perspective. In fact we’re launching a AI commerce podcast special series just to address some of these newer issues. And I think the opportunity to provide a new type of experience and establish a new relationship to the brand is possible, because it’s now possible for brands, particularly consumer brands, that otherwise were only experienced in the product or service that people consumed- They now can have a direct experience with the brand. What are you seeing on that side of the-- Be a little future-oriented for me and predict where you see that taking brands.

    [28:16] Hampton Bridwell: Sure. I think, it’s a, it’s an interesting opportunity for companies, and I think it’s changing and moving very quickly. So the, the stage that we’re in now is, recommendations and exposing, a brand in the context of a question, a thought exploring, discovering something. And so where most AI usage today is really geared around, what that, that’s all about. When you move to more, predictive analytics incorporated into your daily work and into your daily life and those are actually merging with the LLMs around each individual interaction, again, day in, day out with the, with their elec- digital devices around them. I think this the pursuit of being able to help people to live their lives in a more frictionless way is really where this is driving towards. And so many of the things that we have as repeat task in our life that, create, waste time, create friction those things will actually become easier and easier for us. And so I see the promise not in a lazy way, but it ends up making life just more enjoyable and making, and giving an opportunity to, the companies that are building brands that operate like this an incredible economic frontier. And my view is that there’s a lot of innovation ahead of us. People have to, build this but, the agents that we have for ourselves will be interacting with other agents. That’s already happening, and I think that this continues scaling from where we are today.

    [29:57] Christina Ellwood: Yeah. Great. Beyond the valuation question of brand, your platform also covers reputation intelligence and strategic foresight. What does each of those tell a leader about what that, that valuation alone doesn’t tell them?

    [30:11] Hampton Bridwell: Yeah. To, to some degree, the valuation is sensitized to these things, and so your reputation is slightly different than brand in, in many ways. But but they have a, a deep interrelationship with each other. And so a company’s, reputation stands out in front of it and describes to people, what it stands for. And a well-managed reputation, does make a difference, especially when finding talent, operating in your communities people having confidence in your oversight and governance principles. Those things are critical for companies to get right and really pay attention to. I did a lot of work in the, on the 2010s to 2015 e-era around sustainability, and it’s still very passionate about it, and it, it makes a difference in the world. And in m-many ways it’s, turned into a conversation around resilience. And so a company’s ab-ability to sustain its performance over long periods of time is a reflection of its sustainable capability and as well as its resilience in markets that it serves and its ability to perform. That for me, I think reputation is a key component and, clients have to pay close attention to that. And reputation can actually, be destroyed much faster than brand in which is brand is a fairly slow-moving asset from a value standpoint, but reputation can be much faster. So I, that was one of the reasons why we included it in the platform, so that clients can see the interaction between these things, and it’s an important part of the engine. And then when it comes to foresighting innovation, brand innovation thinking about futures is important from what, just knowing what’s on the horizon. And if you’re going to be building your own horizons in your company in terms of products and services and thinking about, where you’re gonna play and compete you have to have a view on futures. And, for the longest time, getting futures organized was an activity that required a lot of workshopping, a lot of data discovery and synthesizing, and AI now can really do that at scale using, STEEP plus G type frameworks. And understanding social issues, technological issues, environmental, political, all those things that, governance, seeing those things a- at scale is one of the, the-- one of the things that AI does extremely well. So having that in our system allows for people to understand concretely where they are today to see the market around them and how things are moving, and then have a projection forward one to five, seven years about where things are going and what might reshape their own business. And I think that helps from that management perspective and understanding what risks you’re managing as well as what the opportunities are.

    [33:12] Christina Ellwood: Yeah. Brand has become in- increasingly important and your system is a very powerful way for management teams to factor that into their decision process. So before we wrap up, let me ask you a few closing questions. What resources would you recommend for listeners who wanna learn more about you and CorebrandAI?

    [33:32] Hampton Bridwell: Sure. corebrand.ai is our site of destination, and that’s a good place to start. It’s pretty simple when we get right down to it in terms of what we do. And then y- we are hosting an event coming up with Reuters in middle of November 16th, and that’s gonna have 250 CMOs at it. And, we’ll be there, really showcasing what we do and helping drive the dialogue around moving brand from an episodic event that happens from, just a, a research standpoint to it becoming a part of an overall management system. So that’s what we’re doing here this fall and and getting ourselves out into the market.

    [34:13] Christina Ellwood: And how might a CMO look to attend that event or maybe get a readout from the event or something like that? What could a listener who’s a CMO benefit from that event?

    [34:25] Hampton Bridwell: Sure. We’re having round table discussions and this is really a chance for us to stimulate the dialogue between these professionals. Everybody has a, a different situation that they are faced with day in and day out inside of their companies, and the questions that their CEOs and CFOs and their board have for them, and the way that they have to basically justify the work that they do. And first and foremost for us is those conversations between these executives. And our job is to open, the ideas and get people, talking about the potential and then, from there, y- you know, helping people to see that the, the approach that we’re using is a great approach and a, a way to be able to implement it rapidly across their enterprise.

    [35:13] Christina Ellwood: Will you be sharing the results of those conversations after the event?

    [35:17] Hampton Bridwell: We will be. Part of what we’re gonna be providing are 51 industry reports that give you mentioned the SpaceX and Anthropic, reports that we did. We’re gonna be actually doing something similar on every single industry that we cover. So all 51 industries will have snapshot reports that we’re, providing, and then we’re gonna, basically take what we are hearing from folks and bring that forward as part of our ongoing content and and, m- message development. So we incorporate what we hear into our platform as well, and and so we’re, we’ll be sharing, in a two-way environment with all that. So-

    [35:55] Christina Ellwood: And how would people find those report, those insight reports and those, those conclusions?

    [36:00] Hampton Bridwell: So the best way to get access to those, they’ll be available in the second half of November. And and if you just come to our website and drop us a line or you can drop me an email at hampton@corebrand.ai, and that is an easy way to, get in touch, and we’re happy to share.

    [36:20] Christina Ellwood: And if somebody wanted to attend the event, can they do the same, or is it a closed event?

    [36:26] Hampton Bridwell: It it is an open event. They are looking for folks that are CMO level and director level within their organizations, and there’s, there’s still room.

    [36:35] Christina Ellwood: Excellent. Okay. So we’ll make sure that in the show notes we have the information to connect people to the event and to your your website for getting access to these insights post-event. And in the AI revolution, what leadership skill do you personally find most valuable in your work today?

    [36:53] Hampton Bridwell: You have to have an open mind You, and you have to have a curious mind. I think that, for me, those are the two traits that allow you to not be fearful of what’s coming, but to embrace, what is here now and what is coming over the horizon. It’s moving fast. It makes people nervous. There’s things that are gonna go wrong and things that’ll go right. But I think a curious, open mind is really the quality that wins the day.

    [37:25] Christina Ellwood: If our listeners remember just one thing from today’s conversation, what should it be and why?

    [37:32] Hampton Bridwell: I think it is to be curious. That’s what led me to first meeting Jim Gregory, 25 years ago and shaking hands and learning about the work that he was doing to eventually buying his company and incorporating that into everything that we do from a brand strategy standpoint at Tenet Partners and providing consult to clients. And and then from there, really, again, moving this forward and just knowing that things are always changing and you have to look out onto the horizons and think about where you wanna play and where you can win. And the last thing I’ll say is that, for folks like myself who have been in the business for 30, 30 years now, th-this is an opportunity to bring that knowledge forward and do things with it that were just unimaginable. And it is a time of great acceleration and great experimentation but it is exciting. And so I, I think it’s the moment is now to jump in headfirst and really, start exploring.

    [38:38] Christina Ellwood: Fantastic. We will also make sure that we cover the outputs from your upcoming event on the AI Realized Now newsletter. And in the meantime, Hampton Bridwell, co-founder of CorebrandAI and CEO of Tenet Partners, thank you for sharing your experiences with us today.

    [38:56] Hampton Bridwell: Thank you so much, Christina. It was a pleasure to be with you.

 
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