Put agents to work today
Transform your campaign workflows with powerful AI that delivers measurable results.
Book a meeting
There's a quote that's been circulating in tech circles that cuts right to the heart of where the media industry stands today. The best coders using AI aren't reporting 2x productivity gains — they're reporting 10x. And the gap between people who use AI and people who are elite with AI is widening, not narrowing.
That's not a coding story; that's the story for every role across media, advertising, and the agencies that serve them.
It was also the provocation that opened our recent webinar, The New Way of Working: Human + AI Collaboration in Modern Media, and it set the tone for an hour of unusually candid conversation between three leaders who are living this shift in real time: Jake Abraham, Head of Strategic Partnerships at Experian; Maggie Zak, EVP of Analytics and Engineering at Havas Media Network; and Jon Reilly, CEO and co-founder of Akkio.
Here's what they had to say.
One of the first things this panel made clear is that organizations waiting for a definitive AI roadmap are already behind. The technology is moving faster than any blueprint can keep up with.
"The capability is an exponential curve," said Reilly. "What you can do with a language model is changing faster than anyone can keep up, and it's only going to accelerate from here. Whatever you build needs to keep that in mind."
For Havas, which has embedded AI into its global operating system — Converged.AI — powering how 23,000 people work across the group, the journey is well underway. But Zak was quick to note that scale doesn't make the human question any easier.
"Our people are front and center," she said. "It's not about AI working side-by-side with humans. It's about how AI makes us smarter, better, faster, more insightful, for our clients and for the way we work."
Abraham echoed the importance of getting the foundation right before the fireworks. At Experian, a company built on deep data in highly regulated spaces, governance and trust aren't afterthoughts; they're the starting point.
"How do we ensure that all of the safety and trust that has been built at Experian over the years continues to follow us through the AI journey?" he asked. "That's a primary component."
A perspective that surfaced again and again was the fact that AI isn't replacing jobs but reshuffling the tasks within them.
Zak made this theory concrete with a challenge she's issuing to her own teams: stop thinking about delivering data, and start thinking about answering questions.
"Even junior team members should be learning more about how a brand manager or marketer is tackling their challenges — what data would help them make a smarter decision on where the next dollar goes," she said. "AI takes the data-pulling and chart-making off their plates. That gives them the chance to think. And that's going to be a critical reframing."
For Reilly, the hierarchy of tasks is what to watch. Today, high-volume, low-judgment tasks are automatable with relative ease. Tomorrow, higher-judgment tasks will follow. But the human layer — validation, expertise, strategic accountability — doesn't disappear.
"Nobody out there is proposing you spend $50 million on a campaign that nobody actually looked at," he said. "We may get there, but there's a long path of proof establishment, and probably a lot of landmines on the way."
What does it mean for AI to be enterprise-ready in a media context? The panel pushed past the standard checklist of security and compliance to get at something more nuanced.
Abraham pointed to role-based customization as an underappreciated dimension. The guardrails an LLM applies to a junior analyst querying a dataset should look very different from those applied to a senior data scientist. Building once and making it relevant across an entire organization — at different seniority levels, across different client relationships — is a genuine design challenge.
"We've always thought about what level of permissions different roles have," he said. "But now we're talking about a two-way street, where we're actually querying and getting responses, and those responses become part of the knowledge base of a particular client. You really want to have great controls."
Reilly framed the infrastructure prerequisite more bluntly: you cannot scale until you solve context containerization. Data isolation, information architecture, observability, enterprise security — these aren't optional features. They're the foundation.
"The thousand flowers being planted in the field aren't connected," he said of early AI adoption patterns. "Practically speaking, you need an information architecture that is secure and considers the fact that you have different clients and different data permissions."
Near the close, the panel was asked: in one word, what becomes possible when humans and AI truly collaborate?
Zak: Acceleration. Abraham: Scale of intelligence. Reilly: Leverage.
Three different words, the same idea.
The panel closed with four key takeaways that are worth sitting with:
The media companies succeeding with AI are moving most deliberately — building foundations that are secure, flexible, and designed for a target that won't stop moving.
As Zak put it in her closing remarks: "This is really an amazing turning point in our industry. It should be met with excitement and curiosity."
Want to learn more about the new way of working from our panelists? Check out the full webinar.
Transform your campaign workflows with powerful AI that delivers measurable results.