Jonah Goodhart has a long track record of identifying major industry shifts early. He was the founding investor and first board member of Right Media, the first scaled digital ad trading platform, which was later acquired by Yahoo, before going on to co-found Moat, a measurement and attention analytics platform acquired by Oracle. Jonah currently runs Mobian, an AI powered platform building a contextual graph for an AI first world, using new contextual signals to help brands understand not just what worked, but why, and to systematically improve future marketing decisions through measurement, intelligence, and optimization. One of the industry’s most trusted advisors and an Attain board member, Goodhart recently shared his top five predictions for 2026. Unsurprisingly, AI sits at the center of all of them.
AI Slop—low-quality, sensational, and repetitive content generated at massive scale—is quickly becoming one of the most serious risks in digital advertising. This type of content thrives on cheap engagement and volume and spreads easily across major platforms. As a result, brands increasingly find their ads appearing alongside material that undermines trust and dilutes impact. In 2026, identifying and avoiding AI Slop becomes essential not just for brand protection, but for preserving media effectiveness and ensuring advertising dollars support environments that actually drive outcomes.
As AI-powered feeds, summaries, and assistants reshape how people consume information, brands no longer control visibility the way they once did. Exposure is increasingly mediated, interpreted, and contextualized by systems brands don’t own. In this environment, simply showing up isn’t enough -- how and where a brand appears matters just as much as whether it appears at all. Advertisers will begin to focus less on raw exposure and more on association, perception, and presence in moments that actually influence decision-making.
In an ecosystem reshaped by AI, context becomes the connective tissue that gives advertising meaning. As identity fragments and content scales endlessly, context helps determine relevance, credibility, and interpretation. It influences how messages are received, how brands are perceived, and how signals translate into outcomes. Rather than treating context as a tactical layer or a safety check, leading marketers in 2026 will elevate it to a strategic input that complements audience data and performance measurement.
The problem is that for years, much of the data behind audience targeting has been inconsistent at best and flat wrong at worst. Who a brand is trying to reach remains the starting point of every marketing conversation, but the future of audience targeting depends on higher-quality inputs. Purchase-based signals, real behavioral evidence, and AI that understands context will steadily replace guesswork and proxy traits. In 2026, audience targeting will only succeed when it is grounded in context and backed by data that reflects how people actually behave.
As AI automates more media decisions, advertisers grow less tolerant of opaque systems and black-box scores. It’s no longer enough to know that something was flagged, included, or excluded -- brands want to understand why. Transparency is essential for confidence, governance, and optimization, enabling marketers to learn from their media rather than blindly trust it. In a world where algorithms increasingly shape outcomes, explainability will become a prerequisite for trust.
