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The creative brief has been one of the foundational documents of the marketing industry. A strategist spends weeks researching an audience, distills it down to a single "target persona," and writes a two-page document that attempts to summarize the hopes, fears, and buying triggers of millions of people. 

The brief was about an imagined average customer, and the entire downstream production process was built to serve that fiction.

But this model doesn't work when a brand needs to produce thousands of content variations across dozens of markets in near real time.

The "one brief to rule them all" approach bleeds efficiency, relevance, and speed until teams are buried in revision cycles and campaigns launch two weeks late with creative that lands for maybe 40% of the intended audience.

What IBM and Monks figured out through different paths and for different reasons is that the brief itself needs to become dynamic.

AI turns the creative brief into a system that generates multiple briefs from a single input, each calibrated to a specific audience, channel, or market context.

In this issue, we're looking at how two organizations on opposite ends of the brand/agency divide both arrived at the same conclusion that the future of creative production starts before the brief is written, and AI is what makes it scale.

Let's go! 🚀

IBM Creative Assistant and unified search: How IBM uses watsonx tools to manage marketing assets and search institutional data. The scale and scope of customized omnichannel marketing campaigns and the breadth of company data that marketing teams draw on in their work create challenges that demand the implementation of AI to augment the work of the marketing team. [Source: IBM]

AI Gets Right Message to Right User for 62% CVR Boost. Mental health is not one-size-fits-all. Generative AI gets the right message to the right user at the right time. Persona.Flow gathered consumer research insights about the seasonal stressors that impacted the target audience’s mental health during the holidays. That process was completed in a matter of minutes rather than the days or weeks required by a traditional research program. [Source: Monks]

GPT-5.5 is OpenAI’s most capable agentic AI model yet. OpenAI launched GPT-5.5 on April 23 as what it calls “a new class of intelligence for real work and powering agents,” and the framing is deliberate. OpenAI says it’s the most capable agentic AI model to date, built from the ground up to plan, use tools, check its own output, and work through tasks independently. [Source: AI News] 

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The creative brief was designed to align a team on what a campaign should accomplish and who it should reach. The alignment function is still valuable, but what's broken is what happens after the brief is approved.

A single brief historically produced a single campaign concept, which was then manually adapted: different sizes for digital display, different copy for different markets, different headlines for A/B tests.

That adaptation work is where creative teams spend enormous amounts of time, and where the quality of the original strategic thinking gets diluted by production pressure.

IBM and Monks approached this problem from different angles, but arrived at the same structural answer: separate the strategic layer of a brief from the production layer, and let AI handle everything in between.

The Challenge

IBM's marketing team produces content at a scale that strains even large creative departments. Designers were spending hours adapting single campaign assets across multiple media formats. Copywriters were tailoring messages for diverse audience segments while maintaining brand voice and compliance standards. The volume of content required for personalized experiences across IBM's global markets made the traditional brief-to-asset workflow a challenge.

The Solution

IBM built IBM Creative Assistant on top of its own watsonx platform. The tool gives marketing teams access to a comprehensive database of IBM product information, pre-approved brand templates, and AI-assisted copy generation within a single interface.

Non-designers can generate on-brand assets without waiting for a designer to be available, and designers can focus on building the master templates and creative governance structures that the AI draws from.

IBM then integrated Adobe Firefly into its content supply chain for campaigns that required image generation at scale. Rather than a designer receiving a creative brief and spending days producing variations, IBM's system now works like this: customer data from IBM's watsonx data platform (segment, location, purchase history) triggers a content request, the AI generates a highly specific creative prompt based on that data then the asset is generated and delivered without a human needing to act as the intermediary between the data brief and the finished creative.

The Results

In a pilot campaign, IBM generated over 1,000 marketing asset variations in minutes using Adobe Firefly, and engagement increased. IBM is now scaling toward multimodal production of video and image alongside text as it completes an AI-powered auto-tagging project to make its entire digital asset library usable as training and retrieval input.

The Key Insight

IBM's Director of Brand Marketing, Joe Prota, described the AI's role in the creative process plainly: it accelerates the path to the big idea and improves clarity between all parties involved. The brief becomes more precise because the production cost of any given creative direction drops significantly, allowing teams to explore more concepts within the same time budget.

The Challenge

Most agencies treat personalization as a post-production problem, where you create the campaign, then figure out how to adapt it for different audience segments.

Monks saw this as the wrong order of operations in that if the creative brief describes only one audience, all the AI in the world can't make the downstream output feel genuinely personal. It makes the generic version faster to produce.

The Solution

Monks built Monks.Flow, an AI-powered managed service that connects trained talent, AI tools, and automated workflows into a single production pipeline. In Monks.Flow, segmented audience intelligence isn't applied after the creative concept is developed, it shapes the brief itself.

Using Monks.Flow, the agency's teams can generate targeted imagery and social copy directly from audience segment data before a single asset goes into production. The brief becomes a template as a strategic input that generates multiple executions calibrated to distinct audience signals, rather than a document describing one imaginary average customer.

Monks tested this approach at scale with the Boomtown music festival (Boomtown Unboxed), where first-party event data captured throughout the festival dynamically assembled personalized video recap content for each attendee. 

Monks.Flow integrates with Salesforce and Adobe Firefly, with the explicit goal of connecting the data layer (who the customer is) directly to the creative layer (what they see) without a manual brief-writing step in between.

The Results

For Headspace's holiday campaign, Monks used its AI-powered personalization approach to move past a single consumer persona and into multiple distinct audience profiles.

With over 460 original ad assets produced for personalized testing, AI-assisted campaigns ultimately drove 10% more conversions at a 13% better cost-per-signup compared to the control campaign. 

Boomtown Unboxed was a key driver in helping the festival achieve its most successful sales month in history for the next year's event. The engagement with the videos was exceptional: they boasted an 88% average completion rate, and over 40% of viewers downloaded or shared their personal video, turning attendees into powerful and authentic brand advocates.

The Key Insight

Monks has primarily operationalized the order of inputs, and when audience data shapes the brief before production begins, personalization is structural, and you build a system that produces five campaign directions from one strategic input.

Strip away the different tools and contexts, and IBM and Monks reached the same conclusion through different paths:

Use this prompt with your preferred LLM to turn your standard creative brief into a modular, AI-ready brief system for multi-segment campaigns.

The Scenario: You are the Head of Content Strategy at a B2C brand preparing to launch a product campaign across three audience segments. Your team is about to write a traditional single-page creative brief, but you want to design it so that AI can generate distinct campaign directions for each segment without losing strategic coherence.

The Prompt:

"You are a creative strategy consultant helping me redesign my campaign brief process. I want to move from a single creative brief to a modular brief system that can generate AI-personalized campaign directions for multiple audience segments. Help me build this system."

Current Situation:

Questions:

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The creative brief is evolving into something more interesting as a strategic architecture. For the brief to work in an AI-powered production environment, it should encode intent clearly enough for a system to execute against, while leaving room for human judgment to govern quality and direction.

What IBM and Monks show us is that brands and agencies ought to restructure the creative process itself by moving audience data upstream, turning master templates into production infrastructure, and redefining what it means to be a creative professional.

The average marketing team won't build IBM's Creative Assistant or Monks.Flow from scratch, but any team can adopt the underlying logic by treating personalization as a brief design problem because it’s where everything downstream gets determined.

Until next time, keep exploring the horizon. 🌅

Alex Lielacher

P.S. If you want your brand to show up in Google AI Mode, ChatGPT, and Perplexity, reach out to my agency, Rise Up Media. That's what we do.