Companies spend years building expertise that rarely appears on a balance sheet. It lives in the decisions people make, the markets they understand, the customers they know, and the mistakes they have already paid to learn from.
Multicultural marketing makes that easy to see. A new dataset can tell you about an audience, but cultural understanding takes years to build. It comes from working with different communities long enough to understand what resonates, what doesn’t, and why the same marketing decision can work for one audience and miss another entirely.
Businesses build that understanding over time. They hire experienced people, develop customer relationships, enter markets, test assumptions, and eventually figure out which ones actually hold up.
AI gives us a way to make more of that accumulated knowledge usable.
That's become increasingly important to how I think about what we're building at RAD. Earlier this year, we laid out our Artificial Intelligence Buyout, or AIBO, strategy for evolving RAD from an AI marketing platform into an AI-driven holding company.
The idea was never to collect companies under the same corporate name. We wanted to bring together specialized operating businesses, connect what they know through shared technology, and find ways for the entire organization to get smarter as a result. Now we're getting to the part that matters: making it work.
Multicultural Expertise Adds Another Dimension
RAD now has five operating businesses spanning enterprise marketing, creator intelligence, multicultural marketing, applied intelligence, and vision care.
Our acquisition of AVC in June added something particularly interesting to that portfolio. AVC has spent more than 20 years building expertise in multicultural marketing and working with major brands to understand and reach diverse audiences.
Twenty years of operating experience contains a lot more than what appears in a customer list or income statement. You learn things.
You learn where cultural context changes the way a message lands. You see campaigns perform differently than expected. You make assumptions that turn out to be right and others that don't. You build relationships and judgment along the way.
A competitor can buy similar software. It can access many of the same public datasets. It can't go out and buy 20 years of experience overnight. And I think AI makes that experience more valuable, not less.
Technology is very good at identifying patterns across enormous amounts of information. Experienced people understand the context behind those patterns. In multicultural marketing, that context matters because two people who look similar in a demographic profile can behave very differently based on culture, community, and lived experience.
Put those capabilities together and you can make a better marketing decision. We now have a real-world opportunity to test that idea inside RAD.
What One Business Knows Shouldn't Stay There
Traditional holding companies have familiar ways to create value. They can allocate capital, consolidate infrastructure, share services, cross-sell capabilities, and improve operations. AI gives us another lever.
Knowledge developed inside one operating company can become useful somewhere else in the portfolio. RAD has been building toward that idea through our technology.
We're developing our technology to connect more of what our businesses know across the portfolio and make that knowledge useful across the organization.
AVC brings multicultural expertise and decades of operating experience. RAD Amplify brings creator intelligence, enterprise relationships, and campaign experience. Our technology brings audience intelligence and the ability to identify behavioral patterns at scale. Each brings value independently. Put them together and the decision gets better.
A team working on a multicultural campaign can bring those capabilities together instead of treating them as separate workstreams. What that team learns can then inform the next audience, campaign, or customer problem. That's when the portfolio itself starts becoming part of the technology strategy.
Acquisitions Can Bring Knowledge With Them
Most acquisitions are understandably evaluated through financial performance, customers, talent, market position, and potential synergies. Those things are fundamental. But in an AI-driven holding company, there’s another asset worth considering: what the business has already spent years learning.
Every established company has paid to develop that knowledge. A multicultural agency learns how culture changes consumer behavior. A creator business learns which relationships and audience characteristics translate into results. A sales organization learns which customers stay, expand, and become valuable over time.
None of that learning was free. It came from salaries, campaigns, technology investments, customer relationships, mistakes, and successful bets.
Historically, a surprising amount of it stays trapped inside the business where it originated. Some lives in systems and presentations. Some exists in processes. A lot of it lives in people's heads.
AI gives us a credible way to keep more of it, connect it to outcomes, and make it useful when another team is facing a similar decision.
This doesn't mean buying more companies automatically makes an AI system smarter. I wish it were that easy. The businesses still have to fit. Their expertise has to be relevant, the technology has to connect it in useful ways, and, most importantly, people have to put it to work. That's why integration matters as much as acquisition.
From Strategy to Operating Model
AVC is one of our first major opportunities to demonstrate that model. Since closing the acquisition, teams across RAD have begun collaborating on opportunities that bring together AVC's multicultural expertise, RAD Amplify's enterprise and creator capabilities, and RAD's audience intelligence.
At the same time, we're continuing to invest in the technology and operating infrastructure that supports those businesses. That includes the systems that can connect what our companies know, as well as the people, processes, and relationships required to make that knowledge useful.
Technology can help surface patterns, retain institutional knowledge, and put more information in front of the person making a decision. People still have to make the call, see what happens, and carry that learning forward. That’s how experience starts to compound.
The first phase was building the technology. Then we started assembling the portfolio around it. Now the work is connecting those pieces so expertise from one part of RAD can strengthen decisions somewhere else.
We're still early. There is plenty left to prove. But the pieces we once described as a strategy are increasingly becoming an operating model: specialized companies, experienced people, proprietary knowledge, and technology built to make more of what those companies know useful.
That's what an AI-driven holding company means to me. The portfolio gets more valuable when what one business has already paid to learn can improve decisions across the others.
What Marketers Should Know Now
Creators are increasingly being treated like businesses worth investing in. Steven Bartlett and Authentic Brands Group launched OBSN, a new venture that plans to invest up to $400 million in creators while providing infrastructure, brand-building expertise and distribution support. It's another sign that the creator economy is moving well beyond one-off sponsorships toward building durable businesses around talent and audiences. Read Business Insider's coverage
Creator services are driving M&A activity. A recent analysis of 84 creator-economy acquisitions found that services and representation businesses accounted for nearly 74% of deal volume. Agencies, talent management companies and creator services are attracting buyers looking to add capabilities and assemble broader platforms around a rapidly growing market. Read the M&A report
Agency contracts are starting to catch up with AI. As agencies automate more marketing work and develop proprietary AI tools, some are adding AI-specific language to client agreements and reconsidering how traditional staffing and cost structures translate to an increasingly technology-driven model. Read Digiday's analysis
AI is changing the skills companies want from marketers. While overall marketing job postings remain below pre-pandemic levels, demand for roles requiring AI skills is growing. As execution becomes easier to automate, business judgment, data literacy and the ability to interpret information in context become more valuable. Read Business Insider's take
