The ‘Is a Hot Dog a Sandwich’ Problem in AI Advertising

The Digiday Podcast
Published: November 18, 2025
Host: Kamiko McCoy & Tim Peterson
Guests: Seb Joseph (Executive Editor of News, Digiday), Ronan Shields (Senior Ad Tech Reporter, Digiday)

Episode Overview

This episode unpacks the explosive evolution of AI agents within digital advertising, focusing on emerging standards designed to bring order to a rapidly automating, increasingly complex programmatic ad ecosystem. The hosts and guests dive into the practical, ethical, and technological challenges of integrating AI agents—from arbitrage and agency transparency issues to new protocols (Ad Context Protocol—ADCP and Agentic RTB Framework), all while expressing skepticism and hope in equal measure (“Is a hot dog a sandwich?” becomes the metaphor for the ambiguities and debates embedded in these new technologies).

Key Discussion Points & Insights

1. Ad Agency Arbitrage & Transparency

• The episode starts by exploring a recent eyebrow-raising move from Paramount, who revealed that agencies like Publicis and IPG are not only handling their media buying but also selling their ad inventory (01:00–05:00).
  • This sparked industry concerns about arbitrage: potential kickbacks, savings guarantees, and whether agencies push inventory from their media-owner clients onto other advertiser clients.
  • Tim: “This Paramount example seemed to, I think why it stood out so much is because it seemed to initially confirm that. Now again, the companies have walked that back and said, that's not going on here.” (06:19)

Notable Moment:

• Kamiko: “I feel like there was this Whitney Houston meme... somebody on that earnings call who whipped their head around to say, ‘Did everybody else just hear what I just heard?’” (03:49)

2. Rise of AI Agents in Ad Operations

• Major tech companies (Amazon, Google, Meta) are rolling out new AI ‘ad agents’—essentially chatbots or tools for campaign planning and optimization (09:41–12:00).
  • These agents promise to speed up routine tasks (ad buying, analytics, etc.), but questions remain about control and oversight.
  • Meta’s Advantage+ tool, for example, auto-generates ad creatives, sometimes with questionable results because of a default setting many didn’t know about.

Notable Quote:

• Kamiko: “If you don't also have your human standing by with a leash and a collar now, you end up with weird AI generated ads... AI sheen happening here.” (12:18)
• Tim: “One of the challenges with these AI tools is it makes it super easy for people to be really lazy.” (13:14)

3. Guardrails, Prompt Engineering, and the Future of AdOps Skills

• The need for guardrails is a recurring theme—ensuring AI agents don’t go rogue requires new skills (like ‘prompt engineering’) and diligent oversight:
  • Everyone in marketing may need a basic ability to “prompt engineer,” similar to everyone once needing basic typing skills (14:42).
  • Human oversight remains vital: “The humans are going to need to stay in the loop.” (14:31)

Industry Frameworks: ADCP & Agentic RTB

4. What Is the Ad Context Protocol (ADCP)?

• Explained by Ronan Shields: “It is an open source standard designed... to bring more accountability and structure into Programmatic Trading.” (24:09)
  • Acts as a common language or set of rules for AI agents to communicate across the programmatic ad supply chain (27:46).
  • Developed by industry players like Yahoo, PubMatic, Scope3, Optable, Swivel, and Triton Digital.
  • Metaphors abound: ADCP is described as pipes, a standardized language, or even “the slang” of advertising AI agents.
• The ‘Hot Dog’ Metaphor:
  • Tim: “...that’s similar to me saying to an AI agent, make me a sandwich... it could come back to me with a hot dog. In which case then we're getting into the conversation of is a sandwich a hot dog?” (29:00)

Key Viewpoints:

• Seb: “Better to think of it as a language, a standardized, common language for AI agents...” (27:46).
• Concerns around data quality: “If the data driving these… workflows is kind of weak, then the protocol is just going to move the mess differently.” (32:21)

5. Agentic RTB Framework (ARTF) & Speed Concerns

• Tim explains the IAB Tech Lab’s ARTF, which sets a specification for enabling AI agents to participate in the Programmatic Bid Stream (15:43).
  • Designed to address the latency problem: traditional real-time bidding takes ~400–600 ms, which is much faster than current AI chatbot response times.
  • Solution: “containerization”—moving AI agent code closer to servers processing ad auctions to accelerate responses (16:36–18:08).
  • Potentially could speed up RTB by up to 80% rather than slow it down.

6. Is the Industry Ready? Adoption, Fragmentation, and Data Cleanliness

• Much debate over whether these protocols are arriving too early given messy, incomplete, or inaccurate data at many publishers (33:05–34:36).
  • Many major players (Amazon, the “walled gardens”) haven’t signed on, risking fragmentation and standards wars.
  • “It’s almost just as interesting who isn’t backing ADCP as it is who is.” — Seb (34:36).

Memorable Analogy:

• Tim: “It feels like AI agents are kind of like the flying cars of advertising… Maybe a monorail system [is safer].” (51:49)

Challenges and Cautions

• Brand safety: There’s industry worry that early mistakes will lead to outsized brand-safety blunders as “AI agents learn on the job” (31:48–33:05).
• Lack of inclusivity: Protocols are being steered mostly by vendors, with little input so far from advertisers, publishers, and broadcasters—mirroring early mistakes in the last era of programmatic standards (50:28).

Foresight Warning:

• Kamiko: “It seems like guardrails, safety and things like this have taken a backseat when it comes to AI. The focus is on efficiencies, curbing costs, faster—not necessarily better...” (46:14)

Timestamps for Key Segments

• 00:10–05:09 – Arbitrage, agency kickbacks, and the Paramount Publicis/IPG deal
• 09:41–14:31 – Rise of AI ad agents; pitfalls with Meta’s Advantage+; the blessing/curse of automation
• 15:43–18:08 – Agentic RTB Framework explained (containerization and speed)
• 24:09–30:28 – Deep dive: What does ADCP actually do? (plumbing/language metaphors)
• 33:05–37:05 – Adoption challenges: Brand safety, data quality, and why the “walled gardens” might not play ball
• 39:07–42:51 – Standards “dialects”: MCP, ADCP, and whether mega-platforms will standardize or fragment the ecosystem
• 44:51–47:34 – Human oversight, optimism vs. pessimism, and guardrails in an agentic future

Notable Quotes & Soundbites

• Tim (on AI agency laziness):
  “One of the challenges with these AI tools is it makes it super easy for people to be really lazy.” (13:14)

• Kamiko (on loss of brand control):
  “If you don't also have your human standing by with a leash and a collar now, you end up with weird AI generated ads.” (12:18)

• Ronan (on protocols):
  “It is an open source standard designed... to bring more accountability and structure into Programmatic Trading…” (24:09)

• Seb (on future risks):
  “If the data driving these… workflows is kind of weak, then the protocol is just going to move the mess kind of differently.” (32:21)

• Tim (on standards wars):
  “If Google and Amazon come in with their own pigeon, that wrecks things a little bit.” (39:14)

Conclusion & Takeaways

• The rapid rollout of AI agents in advertising is already exposing old wounds around transparency, control, and data cleanliness.
• There’s cautious hope new protocols like ADCP and ARTF can introduce order and guardrails, but only if major platforms and all key stakeholders, not just vendors, agree to participate.
• Much of the industry still feels unprepared for this transition—echoing the “is a hot dog a sandwich?” debate, foundational definitions and standards remain unsettled.
• The next 12–18 months will be critical in determining whether AI agents can deliver both speed and safety—or simply automate old problems in new ways.

For more insights and a ringside seat at the digital advertising transformation, check out the upcoming Digital Programmatic Marketing Summit and keep an eye on Digiday’s explainer content for ongoing updates.