I started this newsletter mostly to force myself to keep up with all the new AI marketing news. Things are moving fast! I figured other people might want to learn about it too, so here we are. If there are topics or companies you’d like me to cover, please send them over. I’m a team of one person, so I’ll do what I can. If you want to connect, you can find me running the fractional CMO arm of Foxtown Marketing on most days.

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 IAB NewFronts kick off Monday in New York City, running through March 26, and the calendar shift from their traditional late April/early May slot is not a scheduling technicality. It is a signal about how fundamentally video advertising has changed.

IAB CEO David Cohen framed it plainly: "I cannot remember a more dynamic time in the industry. Every facet of the business is being reinvented and the days of impressions as a proxy for results are fading. Streaming and CTV are now performance-driven channels, directly accountable for business outcomes. AI is now embedded across the entire value chain, reshaping how content is created, how media is bought and sold, and how performance is measured."

The reason for the earlier date is structural. As Cohen explained, digital video buying has become a year-round exercise, and the old May timing no longer made sense for how buyers actually plan. "I remember back in my agency days, seven years ago, that the upfront conversation started around Christmas," Cohen said. "CES was the kickoff to upfront conversations. So there was nothing magical about May for the NewFronts."

The four themes framing this year's event tell you where the industry is placing its bets. The 2026 NewFronts program is built around convergent video, the blending of streaming, social video, and CTV; AI-powered measurement; commerce media; and creator-driven content.

The AI angle is particularly concrete this year. The shift is toward AI moving from a novel concept to the technical and operational layer that brings consistency to an increasingly complex video marketplace, powering contextual relevance, measurement, and creative all at once. Scene-level and multimodal context technology that reads signals from inside content to inform targeting, suitability, and creative decisioning is expected to become a reality. AI-powered measurement and normalization is being positioned as critical to addressing fragmentation and enabling faster insights. Creative automation, variant testing, resizing, and iterative creative that responds to content and audience are all expected to surface prominently in presentations.

For smaller advertisers, there is a specific access story worth watching this week. Programmatic access is expanding in live streaming, following the same path once only seen in search and social. Self-serve platforms, AI-powered video activation tools, and lower spend minimums are allowing small and mid-size advertisers to access premium streaming inventory and target effectively. Live streaming is increasingly expected to surface in programmatic environments, positioned as part of the broader video inventory pool rather than a separate, inaccessible offering.

This case landed last week and has not gotten enough attention in the marketing press given what it signals. A federal class action lawsuit against Grammarly is now making its way through the courts, and the core legal theory is one that applies to a staggering range of AI products being built right now.

In August 2025, Grammarly launched an "Expert Review" tool where, for $12 a month, users could upload their writing and receive real-time feedback and comments attributed to well-known journalists and authors including Julia Angwin and Stephen King, among others. However, as the lawsuit alleges, Grammarly never sought or obtained consent from Angwin or the other experts before using their names and publicly available work to generate writing advice attributed to them.

Angwin discovered the feature the way a lot of people discover that AI tools have been trained on their work: someone else wrote about it. When using the tool, paying customers were told the program was reading their text and "finding experts to review it." After picking a "relevant expert," Grammarly told customers it was "applying ideas from" that expert, provided a short bio, and attributed specific editing suggestions to them. The suit says Grammarly used Angwin's publicly available work to generate advice she never gave and that she would not have given.

The feedback attributed to Angwin was also, by her own account, bad. "The ones they were attributing to me were making the sentences worse, more complex," Angwin said. "The idea that my name would be in there giving people terrible advice is actually really appalling."

Grammarly disabled the feature after the backlash and before the lawsuit was filed, but the legal theory remains. What makes this case especially significant for the AI industry is the precedent it could set. As companies race to differentiate their AI products, many are attaching real human credentials to machine-generated outputs. If Angwin prevails, it could force a reckoning across the sector about consent, attribution, and the boundaries of how AI can leverage human identity.

The term that stuck from this story came from writer Ingrid Burrington, who called the fake versions "sloppelgangers," a portmanteau of sloppy and doppelganger. The uproar over what Burrington memorably dubbed Grammarly's "sloppelgangers" was fairly universal. Featured experts were outraged their likenesses were used without their consent. Others were specifically annoyed at the generic, anodyne advice the borrowed identities were producing.

For marketing and AI tool developers, the checklist coming out of this case is straightforward. If your product surfaces a real person's name, likeness, or attributed expertise, you need documented consent. AI-generated advice attributed to a named expert is not a neutral feature. It is a commercial use of that person's identity, and the law in at least 25 states treats it that way.

The Grammarly case is a useful lens for auditing the AI tools you already use or recommend to clients, whether you built them or bought them.

The question to ask about any AI tool that surfaces real people: does the product present output as being from, by, or inspired by a named person? That includes AI coaching tools that claim to offer advice "in the style of" a known figure, AI writing assistants that attribute suggestions to named editors or authors, and AI training programs that use named experts' methodology or voice without licensing it. If the answer to any of these is yes and you cannot confirm documented consent exists, the tool has the same exposure Grammarly ran into.

For your own content and products, the same principle applies in reverse. If you are a marketer, consultant, or professional services firm building an AI product or training a custom AI on specific people's work, you need consent documentation before you monetize it. "Publicly available" does not mean "free to commercialize." Angwin's work was all publicly available. That was not a defense.

The practical step this week: pull up the AI tools your team uses that involve content generation or coaching, and check whether any of them name real people in their suggestions or feedback. If they do, find out how the vendor obtained consent. You do not want to discover the answer the way Angwin did.

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