AI Isn’t Replacing Marketing Basics, It’s Making Them Matter More: LiveRamp’s Ted Flanagan
CANNES, France — AI may be moving at warp speed but Ted Flanagan, vice president of customer success and solution engineering at LiveRamp, thinks marketers should resist the urge to chase every shiny new model. Instead, they should do something far less glamorous: make sure their data isn’t a dumpster fire.
Speaking with Beet.TV contributor David Kaplan at the Cannes Lions International Festival of Creativity, Flanagan argued that AI’s biggest contribution may be reminding marketers that the fundamentals never went away. The interview is part of a Beet.TV video series produced in collaboration with the New York Stock Exchange.
“I think the influx of AI into the industry is really putting an emphasis back on the fundamentals,” Flanagan said. “With so much changing so rapidly, what is important for all of us in marketing and advertising is just focus on quality inputs and quality outputs.”
It’s hardly the sort of futuristic vision that gets venture capitalists reaching for their checkbooks. But as companies rush to bolt AI onto nearly everything with a login screen, Flanagan’s message was refreshingly old school. If the data going in is questionable, the dazzling charts coming out probably deserve a healthy dose of skepticism too.
Quality beats quantity
Asked by Kaplan how brands should evaluate an expanding universe of AI vendors, platforms and data partners, Flanagan said marketers shouldn’t confuse having more options with making better decisions.
“It still comes down to… quality over quantity,” he said.
He urged companies to examine where a partner’s data comes from and whether it reflects “an authentic relationship with the consumer.” As AI systems become increasingly opaque, understanding the lineage and provenance of data becomes even more valuable.
In other words, before trusting an AI model that promises marketing enlightenment, it might be worth asking whether it learned from solid customer relationships or from the digital equivalent of a guy selling watches from the trunk of his car.
Experiment often, but don’t improvise
Flanagan also argued that AI should encourage more experimentation, not less. The catch is that experiments need discipline.
“The best forms of measurement are experimental by design,” he said. “That’s how we can really understand what is working and what’s not working.”
He said marketers should run as many experiments as possible while maintaining consistent design and rigorous implementation. Otherwise, organizations risk making decisions based on results they can’t fully trust.
The emphasis, he said, is less about finding one perfect AI model than building a repeatable system for testing what actually delivers results.
Humans still get a vote
For all the excitement surrounding autonomous AI, Flanagan doesn’t believe marketers should hand over the keys and head out for coffee.
“I think this is why we constantly hear about putting a human in the loop,” he said.
Human judgment remains essential for deciding whether AI-generated recommendations are accurate, appropriate and worthy of real marketing investment, he said. Brand safety, governance, privacy and security all become even more important as AI takes on larger roles across marketing workflows.
That may disappoint anyone hoping AI would eliminate meetings. Instead, it appears AI has simply created new reasons to schedule them.
Build a foundation instead of rebuilding everything
With AI capabilities evolving almost monthly, Kaplan asked how marketers can avoid rebuilding their technology stacks every year.
Flanagan’s answer was to invest below the surface instead of chasing every new feature.
He recommended maintaining governed, secure and interoperable data that can work across new applications while also investing in people who understand experimentation and can adapt as technology evolves.
“I think kind of the data foundation and then the people foundation are the two critical pieces that most of our customers are looking at,” Flanagan said. “That’s how we’re investing in our own business.”
His advice offers a useful reality check in an industry where every product launch claims to reinvent marketing. Sometimes the most valuable AI strategy isn’t buying another tool. It’s making sure the data, the people and the process underneath are strong enough that the next tool actually has something worthwhile to work with.
From Compliance to Competitive Edge: Lyft, Kroger, Intuit LiveRamp on Trust in Marketing
You’re watching The Beet.TV Leadership Sessions at Cannes Lions 2026, presented by LiveRamp. For more videos from this series, please visit this page. You can find all of our coverage from Cannes Lions 2026 here.
CANNES, France — AI may be moving at warp speed but Ted Flanagan, vice president of customer success and solution engineering at LiveRamp, thinks marketers should resist the urge to chase every shiny new model. Instead, they should do something far less glamorous: make sure their data isn’t a dumpster fire.
Speaking with Beet.TV contributor David Kaplan at the Cannes Lions International Festival of Creativity, Flanagan argued that AI’s biggest contribution may be reminding marketers that the fundamentals never went away. The interview is part of a Beet.TV video series produced in collaboration with the New York Stock Exchange.
“I think the influx of AI into the industry is really putting an emphasis back on the fundamentals,” Flanagan said. “With so much changing so rapidly, what is important for all of us in marketing and advertising is just focus on quality inputs and quality outputs.”
It’s hardly the sort of futuristic vision that gets venture capitalists reaching for their checkbooks. But as companies rush to bolt AI onto nearly everything with a login screen, Flanagan’s message was refreshingly old school. If the data going in is questionable, the dazzling charts coming out probably deserve a healthy dose of skepticism too.
Quality beats quantity
Asked by Kaplan how brands should evaluate an expanding universe of AI vendors, platforms and data partners, Flanagan said marketers shouldn’t confuse having more options with making better decisions.
“It still comes down to… quality over quantity,” he said.
He urged companies to examine where a partner’s data comes from and whether it reflects “an authentic relationship with the consumer.” As AI systems become increasingly opaque, understanding the lineage and provenance of data becomes even more valuable.
In other words, before trusting an AI model that promises marketing enlightenment, it might be worth asking whether it learned from solid customer relationships or from the digital equivalent of a guy selling watches from the trunk of his car.
Experiment often, but don’t improvise
Flanagan also argued that AI should encourage more experimentation, not less. The catch is that experiments need discipline.
“The best forms of measurement are experimental by design,” he said. “That’s how we can really understand what is working and what’s not working.”
He said marketers should run as many experiments as possible while maintaining consistent design and rigorous implementation. Otherwise, organizations risk making decisions based on results they can’t fully trust.
The emphasis, he said, is less about finding one perfect AI model than building a repeatable system for testing what actually delivers results.
Humans still get a vote
For all the excitement surrounding autonomous AI, Flanagan doesn’t believe marketers should hand over the keys and head out for coffee.
“I think this is why we constantly hear about putting a human in the loop,” he said.
Human judgment remains essential for deciding whether AI-generated recommendations are accurate, appropriate and worthy of real marketing investment, he said. Brand safety, governance, privacy and security all become even more important as AI takes on larger roles across marketing workflows.
That may disappoint anyone hoping AI would eliminate meetings. Instead, it appears AI has simply created new reasons to schedule them.
Build a foundation instead of rebuilding everything
With AI capabilities evolving almost monthly, Kaplan asked how marketers can avoid rebuilding their technology stacks every year.
Flanagan’s answer was to invest below the surface instead of chasing every new feature.
He recommended maintaining governed, secure and interoperable data that can work across new applications while also investing in people who understand experimentation and can adapt as technology evolves.
“I think kind of the data foundation and then the people foundation are the two critical pieces that most of our customers are looking at,” Flanagan said. “That’s how we’re investing in our own business.”
His advice offers a useful reality check in an industry where every product launch claims to reinvent marketing. Sometimes the most valuable AI strategy isn’t buying another tool. It’s making sure the data, the people and the process underneath are strong enough that the next tool actually has something worthwhile to work with.
From Compliance to Competitive Edge: Lyft, Kroger, Intuit LiveRamp on Trust in Marketing
You’re watching The Beet.TV Leadership Sessions at Cannes Lions 2026, presented by LiveRamp. For more videos from this series, please visit this page. You can find all of our coverage from Cannes Lions 2026 here.
