Next in Media: How Sam Garfield Is Building Adobe's AI Operating System for Advertising
Date: March 10, 2026
Host: Mike Shields
Guest: Sam Garfield, Head of Digital Strategy for CMT Data and AI Platforms at Adobe
Episode Overview
This episode explores Adobe's ambitious move to create a comprehensive AI-powered "operating system" for advertising and marketing. Mike Shields and guest Sam Garfield discuss how advances in creative automation, generative AI, and data have the potential to revolutionize content creation, campaign optimization, and brand strategy. The conversation addresses industry readiness, creative intelligence, changes for agencies, concerns about brand presence in generative environments, and the future integration of creative and media technologies.
Key Discussion Points & Insights
1. Adobe's Evolving Role in the Ad Industry
- Adobe’s offering: Not just Photoshop and PDF—now an end-to-end operating system for marketers, covering creative tools, workflow orchestration, and marketing data (02:11).
- “You essentially have an operating system for a marketer. That’s really where Adobe has been leaning in—how do you put that all together?” — Sam Garfield [02:40]
- Who are their customers? Brands, agencies, and publishers. Adobe maintains touchpoints across the entire marketing ecosystem (04:14).
2. Creative Automation & Challenges of Asset Production
- The “math problem” of creative production:
- Brands must create exponentially growing numbers of assets to fit various formats, languages, and channels (05:39).
- Emphasizes the necessity for automation using AI to produce, adapt, and localize content efficiently (06:12).
- “Think about that math formula... There has to be some level of automation in that process and efficiency that’s going to push us into that next stage.” — Garfield [06:12]
- Parallel to data evolution: Automation is at step one on the creative side, similar to early developments in audience data 8-10 years ago (07:01).
3. From Reactive to Intelligent, Always-On Creative
- Current state: Most brands are reactive with creative, sending assets out and waiting to see how they perform (07:48).
- Near-future state: Pre-scored content intelligence, modular assembly, and predictive scoring will allow for more proactive, dynamic creative optimization (08:09).
- “There’s going to be a lot of pre-scored content intelligence… Some level of modular assembly, predictive scoring and automation.” — Garfield [08:12]
- On letting AI “run wild”: Most brands still want significant control—full automation (like ceding budget to Meta or TikTok) unlikely (11:06).
- “I don’t see a world where a CMO just goes, ‘Oh, I’m just going to hand over my whole budget to Meta and let them figure it all out for me.’” — Garfield [12:06]
4. Integration vs. Platform Dependency
- Distinction from big ad platforms: Adobe’s tools are for brands/agencies to retain control and integrate creative automation into broader marketing strategies, rather than outsourcing everything to individual platforms (11:06).
- Workflow integration: Key challenge is embedding new AI/automation tools into existing processes to avoid adding complexity (09:37).
5. Creative Intelligence: A New Performance Driver
- Research with Winterberry Group: Focused on understanding why consumers engage preemptively, capturing creative effectiveness data, and turning creative into a performance lever (13:44).
- “Creative isn’t a fixed cost, it can actually be a performance driver.” — Garfield [14:36]
- 23% increase in investment in creative intelligence as brands and agencies seek to make content effectiveness more systematic (14:36).
- Application: Works across walled gardens, CTV, retail media networks, and traditional channels. Each channel may require tailored creative (15:04).
6. The Creative Agency Perspective
- Threat or opportunity?: Agencies are embracing automation as it enables them to focus on strategy and ideation rather than repetitive work (16:29).
- “If I have an operating system that can do [auto versioning], then I can really do the work that I want to do, which is how do I come up with the next best creative idea?” — Garfield [17:07]
7. Convergence of Creative and Media/Ad Tech
- Future of creative OS: Must integrate with media buying and audience data for optimal performance (18:49).
- “If I only have the creative side and I don’t have the data or the audience intelligence, I’m missing a huge piece.” — Garfield [19:30]
- ‘Always-on’ campaigns: Shift from set campaigns to ongoing, real-time personalization, managed like a 24/7 network operations center (20:08).
- “You can think of a marketing world where there’s personalized campaigns happening all across the board, being automated.” — Garfield [20:38]
8. Agentic AI in Advertising (Early Days)
- Agentic AI: Still nascent—often siloed within platforms, not yet an end-to-end solution (21:13).
- Adobe Strategy: Incorporate Agentic AI into existing workflows to accelerate tasks without demanding full operational overhauls (22:01, 22:33).
9. Impact on Media and Creative Agencies
- Shift in talent: Automation enables agency staff to focus on high-value strategy vs. repetitive production and trafficking (23:20).
- “I think the people are going to be doing higher value tasks… strategic. Start thinking about… What’s this audience?… How do we do this at scale?” — Garfield [23:21]
10. The Generative Search and Brand Visibility Challenge
- Brand concern: Traffic to brand and publisher sites is dropping as users shift to generative engines (24:03).
- Adobe solution: “Generative Engine Optimization”—tools to monitor and improve how brands appear in LLM (Large Language Model) environments (24:03–25:15).
- “We’re really leaning into Generative Engine Optimization… monitor how you’re showing up… restructure your content in a way that is going to be picked up by an LLM.” — Garfield [24:48]
- Adapting search ad strategies: Remains an open question; uncertain how advertising will fit into generative results (26:03, 26:27).
Notable Quotes & Memorable Moments
- “You essentially have an operating system for a marketer. That’s really where Adobe has been leaning in—how do you put that all together?” — Sam Garfield [02:40]
- “Think about that math formula… there has to be some level of automation in that process and efficiency that’s going to push us into that next stage.” — Sam Garfield [06:12]
- “There’s going to be a lot of pre-scored content intelligence… Some level of modular assembly, predictive scoring and automation.” — Sam Garfield [08:12]
- “I don’t see a world where a CMO just goes, ‘Oh, I’m just going to hand over my whole budget to Meta and let them figure it all out for me.’” — Sam Garfield [12:06]
- “Creative isn’t a fixed cost, it can actually be a performance driver.” — Sam Garfield [14:36]
- “If I have an operating system that can do that [auto versioning], then I can really do the work that I want to do, which is how do I come up with the next best creative idea?” — Sam Garfield [17:07]
- “If I only have the creative side and I don’t have the data or the audience intelligence, I’m missing a huge piece.” — Sam Garfield [19:30]
- “You can think of a marketing world where there’s personalized campaigns happening all across the board, being automated.” — Sam Garfield [20:38]
- “We’re really leaning into Generative Engine Optimization…monitor how you’re showing up…restructure your content in a way that is going to be picked up by an LLM.” — Sam Garfield [24:48]
Important Segment Timestamps
- 02:11 — Sam Garfield introduces Adobe’s end-to-end marketing stack
- 05:39 — The “math problem” of asset production and the need for automation
- 07:48 — From reactive to intelligent, predictive creative
- 13:44 — The rise of creative intelligence and new research findings
- 16:29 — Agency reactions: augmentation, not replacement
- 18:49 — Convergence of creative and media technologies
- 21:13 — Early adoption of Agentic AI
- 24:03 — Brand strategies in the age of generative engines and LLMs
Conclusion
This episode offers a comprehensive look at how Adobe is uniquely positioned to unify creative, workflow, and data into an AI-powered “operating system for marketers.” The conversation serves as a guide for brands, agencies, and publishers seeking to future-proof their creative output, understand the growing necessity for automation and intelligence-driven campaigns, address the organizational impact of these changes, and adapt to shifts in consumer discovery fueled by generative AI.