Podcast Summary: AdExchanger Talks

Episode: Making Your Brand Matter To The Models
Host: Allison Schiff
Guest: Tracy Morrissey, SVP of Media & Performance, Innocean USA
Date: November 25, 2025

Episode Overview

This episode dives deep into how generative AI and large language models (LLMs) are shaping the future of marketing, advertising, and media buying. Host Allison Schiff interviews Tracy Morrissey, SVP of Media & Performance at Innocean USA, about practical strategies for integrating AI into marketing, how brands can influence LLMs, the challenges with unified measurement, and the evolving role of media professionals in an AI-driven world.

Key Discussion Points and Insights

Tracy Morrissey's Backstory & Perspective

• From Media to Tech to Agencies
  Tracy has zig-zagged between agency and tech roles, stating her career is happiest when it isn’t linear and brings new challenges (07:13).
• Dog Training & Leadership
  Tracy’s passion for dog psychology during COVID shaped her leadership style:

  “Do I project what I’m feeling...on the people on my team...or do I take a minute to go, okay, I’m going to go in with confidence, I’m going to be clear about what I want, and I’m going to make the appropriate boundaries.” (05:00)

Integrating AI and LLMs in Marketing Strategy

• AI Integration as a Team Sport
  Tracy emphasizes the necessity of cross-team input:

  “It takes a, a world of different perspectives to be able to bring it all together and, and really orchestrate that so that we can make the best recommendation for our clients.” (13:12)

• Assessment Framework for AI Adoption
  The process must start with business challenges—the tech is not for tech’s sake:

  “You don't do Gen AI for Gen sake. You really need to understand... what are your business challenges? Does AI solve for that or doesn't it?” (14:24)
  Key factors for evaluation:

  • Define business challenges first
  • Know your data strategy and infrastructure
  • Test with low-risk pilots
  • Realize AI is often already in existing martech stack

Evaluating Vendors & Unified Measurement

• Vendor Wild West
  The explosion of AI vendors is reminiscent of the earlier tech booms, and Tracy’s method is:
  • Start with a use case rooted in business need
  • Demand a proof of concept (POC) (21:34)
• What Breaks Through the Noise?
  Unified measurement—with tools that bridge data gaps across the consumer journey without heavy lifts—is the primary attractor:

  “The most interesting vendors...are the ones that can really connect the dots without the marketer having a heavy lift and resourcing again. Efficiencies. Efficiencies. Efficiencies.” (22:01)

The Changing Nature of Search

• Search Behaviors in the Generative AI Era
  Tracy now uses multiple GenAI tools to cross-check answers, noting she doesn’t always trust first outputs (24:37).

  “If it’s a question, more in-depth response, then absolutely I’m using gen AI tools, all of them, all of the time to see what kind of differences and responses I get.” (24:37)

• Loss of Trust Is a Looming Issue

  “My hypothesis is they will become less trustworthy once consumers or users start to see the nuances between the different tools or the responses that they get that may not really answer the question that they were asking.” (25:45)

Fragmentation & Orchestration of AI Tools

• Fragmentation Is Real, Orchestration Is Emerging
  With a flood of AI tools, marketers risk needing to manually manage fragmented agents:

  “It is fragmented. I wouldn’t be surprised if we go through the buying up game where bigger companies are buying the smaller gen AI companies...” (32:38)

  • The key is robust, unified data infrastructure rather than chasing flashy new tools

Influencing Large Language Models (LLMs)

• Generative Engine Optimization (GEO)
  While brands can’t yet buy ads in LLM answers, they can:

  • Publish factual, prompt-relevant content
  • Use LLM ranking tools (like SEMrush, Profound) to understand what gets surfaced (38:15)

  “Understanding how LLMs pick up their responses is really important. And some of these tools can help with that.” (38:40)

  • Trusted sources (Wikipedia, retailer sites) get higher ranking

• Handling Negative Content & Brand Protection
  Close coordination with PR is vital. The effect of negative mentions depends on prompt specificity and scale. Brands should focus on getting accurate, trusted info out through credible sources (42:03).

The Future of Content & Brand Presence

• Content for LLMs
  Effective content will be highly specific and answer real user questions, not just be general information dumps.

  “If LLM rankings and prompts is important and is a business goal...answering those questions is really important instead of just talking about something very generally.” (45:55)

• The Zero Click Search Problem As generative search experiences deliver answers directly, publisher site traffic drops and brands must ensure owned channels are trusted, comprehensive, and up-to-date (50:31).

The Evolving Media Role in the Age of AI

• Will Media Buyers Become Obsolete?
  Full automation is unlikely; the human layer remains crucial for context and interpretation:

  “Maybe it’s not the media planners sitting there, you know, hands on keyboard. It’s going to be a different level of expertise that’s going to be required than we’re used to seeing...But I think there’s trade offs at the end of the day.” (53:22)

  • The future skillset is about understanding and leveraging GenAI, not just campaign execution.

Notable Quotes & Memorable Moments

• On GenAI and Business Value:

  “You don't do Gen AI for Gen sake.” (14:24, Tracy Morrissey)

• On Vendor Overload:

  “It’s the wild west right now.” (19:39, Tracy Morrissey)

• On Search Trust Issues:

  “My hypothesis is they will become less trustworthy once consumers or users start to see the nuances between the different tools or the responses...” (25:45, Tracy Morrissey)

• On the Future of Media Buying:

  “I don’t think you’ll ever have a role where you could just drink coffee and set it and forget it.” (53:22, Tracy Morrissey)

• On Brand Responsibility in Search:

  “It’s the sum of the parts that will help you with the LLM result and making sure that it’s delivering from trusted sources.” (51:29, Tracy Morrissey)

Timestamps for Important Segments

• [05:00] Tracy discusses how dog training and work leadership intersect
• [07:13] Tracy’s career path and agency perspective
• [14:24] How to evaluate GenAI/LLM for marketing use—don’t do AI for its own sake
• [19:39] Evaluating vendors in the GenAI wild west
• [22:01] What makes a vendor stand out: unified measurement and efficiency
• [24:37] Tracy on her own changing search habits and trust in GenAI answers
• [32:38] Fragmentation of AI tools and orchestration challenges
• [38:15] Generative Engine Optimization (GEO) and influencing LLMs
• [42:03] Handling negative content and LLM results
• [45:55] Content strategies for LLM visibility
• [50:31] The zero-click search trend and adapting to a generative search world
• [53:22] The future of media buying roles in an AI-driven context

Summary Takeaways

• Don’t implement GenAI just to keep up with trends; use it to solve real business problems, backed by a solid data strategy.
• The vendor landscape is chaotic; root tool selection in business use case, demand proofs, and seek demonstrable efficiency gains.
• Fragmentation in AI tools will persist; prioritize sound data infrastructure and thoughtful orchestration over shiny new platforms.
• Brands seeking to influence LLMs’ responses must create trusted, specific, and prompt-responsive content, and monitor their LLM "rank."
• The skill set for marketers and media buyers is rapidly evolving—AI won’t fully automate people out of a job, but human expertise in QA, insights, and strategy is more critical than ever.
• The “set it and forget it” dream of AI is a myth—there will always be a vital human layer for judgment, curation, and connecting dots across complex datasets and channels.

The conversation is candid, practical, and urges marketers to be smarter about AI—not just jumping on new tools, but focusing on business problems, data, and substantive content that will future-proof their brand in a generative, model-driven world.