GenAI transforms advertising's core pillars. It enables hyper-personalized creatives at scale, democratizes ad production for smaller businesses, and fundamentally enhances the two most critical functions of any ad platform: predicting user behavior and measuring campaign outcomes.

Don't view generative AI video as just a way to make traditional films more efficiently. Ben Horowitz sees it as a fundamentally new creative medium, much like movies were to theater. It enables entirely new forms of storytelling by making visuals that once required massive budgets accessible to anyone.

While generative video gets the hype, producer Tim McLear finds AI's most practical use is automating tedious post-production tasks like data management and metadata logging. This frees up researchers and editors to focus on higher-value creative work, like finding more archival material, rather than being bogged down by manual data entry.

AI can now analyze video ads frame by frame, identifying the most compelling moments and justifying its choices with sophisticated creative principles like color theory and narrative juxtaposition. This allows for deep qualitative analysis of creative effectiveness at scale, surpassing simple A/B testing.

While competitors focus on subscription models for their AI tools, Google's primary strategy is to leverage its core advertising business. By integrating sponsored results into its AI-powered search summaries, Google is the first to turn on an ad-based revenue model for generative AI at scale, posing a significant threat to subscription-reliant players like OpenAI.

While today's focus is on text-based LLMs, the true, defensible AI battleground will be in complex modalities like video. Generating video requires multiple interacting models and unique architectures, creating far greater potential for differentiation and a wider competitive moat than text-based interfaces, which will become commoditized.

AI is creating a fork in marketing strategy. It disrupts traditional demand acquisition channels like search, making it harder and more expensive to get measurable traffic. Simultaneously, it provides powerful new tools to monetize existing demand more effectively. This forces a strategic shift from a volume-based to a value-extraction model.

As AI enables founders to build products in a week for under $500, the need for traditional seed capital for engineering will diminish. The bottleneck—and therefore the need for capital—will shift to winning the intense battle for user attention. VCs will fund marketing war chests instead of just development.

When analyzing video, new generative models can create entirely new images that illustrate a described scene, rather than just pulling a direct screenshot. This allows AI to generate its own 'B-roll' or conceptual art that captures the essence of the source material.