Welcome to today's edition of AI Marketing Geek, your daily dose of the latest AI developments, tools, trends, and actionable insights shaping marketing in 2026. As AI shifts from experimental hype to pragmatic, ROI-driven reality, we're seeing agentic AI take center stage. Autonomous agents are handling media buying, personalization, and commerce, which is wild to watch.

The advertising world is not waiting around. A new open-source initiative called the Ad Context Protocol (AdCP) launched late last year and is already gaining serious momentum in 2026, with more than 20 companies signed on including Yahoo, PubMatic, Scope3, and Magnite.

The idea is straightforward but the implications are massive. AdCP is designed to be the OpenRTB for the AI era. Where OpenRTB standardized real-time bidding a decade ago, AdCP standardizes agent-to-agent communication, the kind of back-and-forth negotiation that precedes a buy or audience activation. Digiday

In plain terms: right now, humans still sit at dashboards and make media buying decisions. AdCP defines a schema for expressing campaign intent, audience parameters, pricing structures, and performance goals in a way AI agents can directly interpret and execute against. pymnts You brief an agent in plain language, and it handles the rest.

The protocol allows AI agents to reason about budgets and outcomes over weeks or months, rather than bidding on individual impressions in milliseconds. Think of it as the difference between day-trading and long-term portfolio management. Equativ

For marketers, the practical upshot is significant. AdCP changes the dynamic around media diversification by collapsing execution costs. It eliminates the need for dozens of different negotiations, allowing a single team to manage 20+ publishers without increasing headcount. Equativ

The protocol is built on Anthropic's Model Context Protocol and is governed by a neutral working group representing publishers, advertisers, agencies, and ad tech platforms. It is not owned by a single vendor and is designed for open contribution and broad adoption. Samba TV

The window to shape this standard is narrow. If AdCP catches on the way OpenRTB did, the companies who engage now will have a voice. Everyone else will just adapt to whatever gets built without them.

HR and workforce platform Deel recently released a full ad campaign featuring lifelike AI-generated actors, created primarily using video tools Runway, Pika, and Luma. Ad Age The spot drew attention not just for the quality of the visuals but for what it signals about where ad production is heading.

This is not experimental anymore. Brands like Deel have already created commercials featuring lifelike AI actors and dreamlike scenarios, opening creative possibilities unimaginable a decade ago, and for fewer resources. Mean CEO's BLOG

The production workflow has flipped. Instead of booking talent, reserving studios, and waiting weeks for editing, teams can drop a script into a browser, select from hundreds of AI-generated performers, and render a 90-second clip ready for TikTok, Instagram Reels, Facebook, or YouTube Shorts. Techpresso

The real advantage is iteration speed. Growth marketers can test 10 different hooks across 5 different actors with 3 different CTAs, producing 150 unique ad creatives in the time it would take to shoot one traditional video. That volume of testing was previously impossible for all but the largest advertisers. Techpresso

The quality bar has cleared the threshold where audiences can tell the difference, which is precisely why it matters. The brands paying attention are not using AI actors to cut corners. They are using them to run more experiments, find winners faster, and scale what works before competitors finish their production cycle.

If your team is typing out the same instructions to ChatGPT or Claude over and over, you're burning time you don't have. Spend 30 minutes this week building a simple prompt library. It doesn't need to be fancy, a shared Google Doc works fine.

For each task your team repeats (writing subject lines, summarizing client calls, drafting social posts), write one prompt that actually works and save it with a label. That's your template. Next time someone needs it, they copy, paste, and customize the variable parts.

Here's the format to use for each entry:

Task: What it's for (e.g., "Summarize a sales call")

Prompt: The full working prompt with brackets around the parts that change, like [client name] or [main objection raised]

Output to expect: One sentence on what good looks like

Last tested: Date, so you know if it needs a refresh

Four prompts that are worth building first: a client recap template, a "write three subject line options" prompt, a competitive research brief, and a first draft blog intro. Those four cover the tasks most marketing teams repeat most often.

The goal is not to build a massive library. It's to stop starting from zero. A prompt that already works is a real asset. Treat it like one.

2026 is the year AI moves from "cool demos" to real and measurable business use cases. Expect more agentic tools, voice-powered targeting, and a focus on privacy-first data.

Stay ahead of the game by treating your AI reputation like your website. It would behoove you to make your brand easy for agents to understand and cite.

What AI experiment are you running this week? Reply and let me know. I'll feature top stories in future editions! (Everybody loves a good story)

Stay sharp,
Jon
@mistersterling
Chief AI Marketing Geek