Why “Context Window” Is the Most Important Concept in AI for Marketing

When ChatGPT first hit the headlines, it sparked curiosity but left many marketers underwhelmed. It could write emails, maybe a blog post—but it couldn’t truly work with a marketer. The reason? Context window.

In simple terms, a context window is how much information an AI model can hold in its "working memory" at once. It defines how much data the system can consider when solving a problem or generating a response. You might think of it as a model’s short-term memory, limiting or enabling how much insight it can provide in any given task.

When GPT-3.5 launched, its context window was just 4,096 tokens—roughly 3,000 words. That’s a few pages of content. By the time GPT-4 arrived, this had grown to 32k and 128k tokens. Now, we have models like Claude and Gemini supporting over 1 million tokens. The next generation will treat this as the baseline.

To put that shift in perspective: using GPT-3.5 was like asking someone to solve a problem after reading the first chapter of a book. With a million-token model, it’s like giving them the full novel, footnotes, research papers, and your marginal notes—all at once. Visually, it’s the difference between solving a puzzle with a few scattered tiles versus having the entire picture laid out in front of you.

For marketing, this breakthrough is transformational. Why?

Because marketing is a data-rich, context-heavy discipline. Planning a campaign might require analysing media mix modelling, linear performance data, demographic segments by channel and geography, historic brand lift studies, budget limitations, and more. Just a year ago, AI models couldn’t meaningfully hold and process all that. Today, they can—and do.

The explosion in AI-powered media planning is a direct result of this expanded context window. Now, systems can read and reason through massive datasets in one pass. Combined with smart prompt engineering, planning frameworks, and machine learning forecasts, planners are co-creating sophisticated plans that were unimaginable 12 months ago.

It’s not just about media. The dramatic leap in image and video generation—from Midjourney to Sora to Veo 3—can also be traced back to context expansion. These models don’t just "see" pixels; they “remember” entire scenes, prompts, even brand guidelines, maintaining coherence across frames and edits. This memory is what enables cinematic output from a text prompt.

But this isn’t about machines replacing humans. It’s about raising the floor and the ceiling.

A planner today, armed with AI tools, can work across vastly more data while retaining their judgment and creativity. It enables iteration and collaboration—strategy and creative now evolve together, in near real time. A planner and a planning agent, working with a creative director and a generative tool, can shape a campaign with shared insight and adaptability.

And this shows the growing need for training. If we want better tools, smarter workflows, and more powerful campaigns, we need to empower planners and creatives to instinctively understand these foundational AI concepts. When creative and strategic minds fully grasp what’s now possible, we don’t just optimise—we reimagine. This isn’t a race to the bottom of bland content. It’s a race to the top of revolutionary quality.

A better world for marketing is emerging. And it starts with memory.

Want to understand what your team could do with a million-token AI model? TAU offers hands-on AI literacy workshops and custom experimentation roadmaps.