AI, Data, and the Future of Omnichannel Ads: Key Takeaways from RampUp 2025

This week, I had the chance to escape Toronto’s winter chill and head to San Francisco for my first-ever RampUp—an event I’ve always considered the big leagues of data. Hosted by LiveRamp, the conference brought together the brightest minds in ad-tech, AI, and data-driven marketing.

What stood out to me at RampUp 2025 wasn’t just the discussions around agentic AI, evolving measurement frameworks, and ad-tech’s shifting power dynamics—it was a quote from Adomni's CEO, Jonathan Gudai, that perfectly captured my own perspective:

“The shift from search-based advertising to AI-driven conversational experiences is reshaping marketing strategies. The next challenge? Proving its effectiveness at scale while making cross-channel advertising seamless, personalized, and natural for both consumers and advertisers.”

This insight encapsulates the seismic shift happening in digital advertising. AI isn’t just optimizing ad placements anymore—it’s fundamentally transforming how brands engage with consumers. The key question now: How do we ensure AI-driven advertising is not just powerful, but truly effective at scale?

Here are my biggest takeaways from RampUp 2025.

Cross-Media Intelligence Is Here—Refinements Will Drive Even Faster Adoption

Cross-media intelligence is no longer just a concept—it’s here and ready to transform media planning and buying. Thanks to platforms like LiveRamp and Adomni’s new SVE backend infrastructure, the foundation is in place to drive meaningful change. While legacy platforms like DV360 and Amazon’s AMC still face challenges with seamless data-sharing, progress is on the horizon.

For example, if a tech partner needs access to a brand's Amazon transactions without importing all associated Amazon advertising data, the process remains cumbersome. Some traditional marketing teams may be reluctant to untangle these fragmented systems, slowing adoption. That’s where tech providers must step in—by streamlining integration and delivering ready-to-use cross-channel insights, they can remove the friction and accelerate adoption for their clients.

But technology alone isn’t enough—transformation must also happen at the buyer level. For omnichannel to truly scale, ad buying teams eventually need to break down silos. Consolidating planning, buying, measurement, and optimization within a unified workflow will unlock the full potential of cross-media intelligence, ensuring seamless execution and more impactful campaigns.

Enhancing 1st-Party Data is Simplifying Deduplication

LiveRamp is unlocking new potential with your first-party data, offering insights like where your audience is distributed across CTV streaming platforms (e.g., 60% Netflix, 20% Prime, 20% Paramount, etc). This enables more efficient omnichannel activation while minimizing duplication which historically has been a concern, even if buyers are blind to it they know it is happening. However, these insights still rely on permissions from streaming services—even for LiveRamp customers. Smaller advertisers may face hurdles in gaining access, and without key platforms in the mix, the data becomes less actionable. While progress is being made, removing these barriers will be crucial to achieving seamless cross-channel marketing with greater accuracy.

Agentic AI Systems: The Next Frontier in Ad-Tech

Agentic AI systems—AI agents that don’t just generate tasks but actually complete them—are going to transform ad-tech. By leveraging hierarchical AI structures, they enable more advanced automation across several key areas:

• Automated Campaign Optimization: AI dynamically adjusts bidding strategies, creative variations, and audience targeting in real time, improving ROAS without manual intervention. This reminds me of AdEspresso, which I first saw in 2016 while living in the Valley while participating in the 500 startups accelerator program and met the Founder Armando Biondi. It made buying Ads on Facebook incredibly easy for non-tech buyers. I think it was called “auto-optimization” back then, it didn’t even use the modern AI buzzwords! Hootesuite quickly acquired them, and now we’re seeing AI-powered automation becoming standard across ad-tech. This is going to make buying ads so much easier and efficient.

• Creative Generation & Testing: AI generates ad creatives, runs A/B tests, and iterates based on performance, reducing human workload and creative fatigue. A standout demo at the conference was from Rembrand, which showcased AI-powered product placement within videos in a way never seen before. It was pretty crazy.

• Cross-Channel Orchestration: AI can manage ad placements across multiple channels (display, social, search, etc.), ensuring a cohesive strategy. If combined with omnichannel measurement reporting, this would be the holy grail—a fully AI-planned, optimized, and measured omnichannel campaign. We’re not there yet, but I estimate we’re less than five years away from realizing this vision.

Challenges of Agentic AI

Despite its rapid advancements, Agentic AI is far from perfect. It still requires human oversight to avoid mistakes, and while it reduces workloads, it cannot yet be fully trusted. Over time, AI will improve, but don’t worry folks we have not reached singularity and won’t for some time. As AI becomes more autonomous, concerns around control, accountability, and unexpected AI-driven decisions that could violate brand guidelines or regulations will grow.

A major challenge is Agentic AI connectivity—right now, proprietary AI systems struggle to integrate with each other. If every company develops its own closed AI ecosystem, we risk future fragmentation similar to what we see with legacy ad-tech platforms today. A critical takeaway from the conference was that interoperability is a must—companies need to collaborate and create seamless AI integrations rather than siloed systems. This was a point that nearly all presenters agreed on.

Diverging Opinions on AI’s Role in Ad-Tech: Have the Ad-Tech Wars Begun?

The conference also highlighted different perspectives on how AI should be used and how it will reshape the ad-tech industry:

• Publishers want AI to enhance audience targeting and drive better monetization.

• Tech providers see AI as a tool for creative automation and value-added services, which directly conflicts with agencies’ role in creative strategy.

• Agencies are in a defensive position, needing to stay ahead of AI’s impact to prevent disintermediation in certain departments.

• AI providers (like Perplexity) are embracing the tech-led vision—predicting AI will automate large portions of the industry, a viewpoint that received mixed reactions.

These differing priorities highlight the tug-of-war between automation and human expertise, which will shape the industry’s evolution over the next decade.

Perplexity’s Advertising Strategy: A New Challenge to Google?

One of the most talked-about moments was Perplexity unveiling its ad strategy, which signals direct disruption to Google Search Ads.

In Perplexity, when a user asks a question, the AI predicts the next question they are likely to ask—then presents a sponsored link beneath the original answer.

For example:

1. User asks: What are the best shoes for hiking in the snow?

2. AI responds: Sorel and Nike are great options for winter hiking.

3. AI suggests a follow-up question brought to you by a sponsor: Where can I find Sorel shoes on sale (not sure if it includes a URL link or not - TBD).

This predictive approach to sponsored search advertising could be a game-changer, creating a new paradigm for intent-based marketing.

LiveRamp’s Strategic Position: The AI Era’s Data Connector

LiveRamp is taking a smart, agnostic approach to the evolving AI landscape. Rather than competing in AI development, they aim to be the connective tissue between various Agentic AI systems, ensuring seamless data flow between them.

This strategy mirrors NVIDIA’s role in the AI boom—while others chase AI dominance, NVIDIA profits by selling the infrastructure (GPUs) that power AI models. Similarly, LiveRamp is positioning itself as the backbone of AI-driven marketing, enabling interoperability across systems.

Many at the conference haven’t fully realized the scale of this opportunity yet, but in a world where data fuels AI just like chips fuel machine learning, LiveRamp stands to benefit more than most.

In summary, RampUp 2025 provided an eye-opening look at the future of advertising, with AI driving the evolution of how brands connect with consumers. The road ahead is filled with exciting possibilities, but it’s clear that collaboration, interoperability, and strategic integration will be key to unlocking its full potential.