How we're building a Marketing AI strategy that actually works

Like many marketing leaders, my journey with AI began with excitement and experimentation. Our team explored various tools, with each member finding their own way to incorporate AI into their workflows. We witnessed productivity gains, but also encountered challenges: conflicting outputs, disconnected workflows, and uneven adoption across the team.

This fragmented approach—what I've come to call the "AI Wild West"—is where many organizations find themselves today. While this exploration phase is valuable, it's time to evolve from ad-hoc experimentation to strategic integration.

From experimentation to intentionality

The "Wild West" phase is tempting. Teams move fast, test freely, and feel empowered to explore. But that freedom, unchecked, quickly creates duplicative work, inconsistent outputs, and an increasingly brittle tech stack. 

We started to see signs of this ourselves: one team member used ChatGPT for blog posts while another preferred Claude, leading to wildly different brand voices. Our SEO specialist had their own set of prompts that never made it to the content team. These small inconsistencies seemed harmless at first, but quickly led to misalignment. It was a preview of what could happen on a large scale if we didn't put shared standards in place.

As the pace of experimentation accelerated, it became clear to me that we needed a unified approach—one that could support innovation without sacrificing structure.

Introducing our Marketing BrAIn Trust

To move beyond the Wild West stage, we've developed a Marketing BrAIn Trust approach that transforms how our team leverages AI. At the heart of our strategy are the goals of hands-on learning and upskilling: creating space for every team member to experiment, share discoveries, and build the AI skills they need to grow. Rather than viewing AI as a collection of individual tools, we're creating a coordinated AI ecosystem where standardized prompts and processes emerge from real experiences and shared knowledge.

The BrAIn Trust serves as our foundation for hands-on learning, AI governance, and skills development.. By building AI directly into everyday workflows, we're not just enabling adoption—we’re shaping it. This approach creates consistency and addresses the key challenges of fragmented experimentation.

Bringing the team along for the journey

From the beginning, we knew this transformation had to be people-first and learning-centered. Before introducing the BrAIn Trust to our team, we aligned closely with our People Ops partners to ensure the intent was clear: This isn't about replacing roles—it's about supporting people in developing new skills and doing more strategic, high-impact work. That alignment gave us the clarity and confidence we needed to scale.

The BrAIn Trust turns that vision into action.  We’re starting with Asana as our customer zero and seamlessly integrating AI into the tools and workflows our team already uses every day— making AI usage inevitable.

Our philosophy centers on three principles that guide everything we do:

• Make it obvious: We demonstrate immediate value through hands-on practice. No abstract promises—team members experience firsthand how these tools save time and improve quality from their very first learning session. We provide clear governance and documented use cases so everyone understands not just how to use AI, but when and why.

• Make it easy: We start with Asana before expanding to other tools, meeting teams where they already work. Our prompts fit into existing workflows, making AI adoption feel natural, not disruptive. We provide simple templates, guided practice sessions, and regular office hours where anyone can get help at their own pace.

• Make it enjoyable: We co-create solutions with the team, not for them. Weekly prompt-sharing sessions have become learning workshops where team members experiment with AI, share discoveries, and learn from each other. We're building personified AI assistants with friendly tones that feel like helpful teammates, not intimidating technology.

This isn't just a tooling upgrade. It's an intentional shift in how we learn and grow as a team. Our BrAIn Trust helps us balance two priorities that often feel at odds: Giving teams the freedom to experiment while ensuring the results of those experiments are useful, scalable, and shareable across the organization.

Our BrAIn Trust addresses several challenges that many teams face:

1. Adoption variability: We meet people where they are in their learning journey, providing support for beginners through advanced users.

2. Inconsistent quality: Standardizing through shared learning helps everyone improve together and achieve consistent results.

3. Wasted time: Our collective knowledge base means no one has to learn in isolation or recreate solutions others have already developed.

4. Duplicated efforts: Regular sharing sessions ensure learnings spread quickly across the team.

By centralizing our approach, we're delivering:

• Hands-on learning opportunities tailored to every skill level

• Prompt and workflow libraries built from team experimentation

• Regular office hours for personalized support and guidance

• Support for technical integrations and guidance for customizing prompts 

• Best practices that emerge from collective learning and experience

Making AI work for everyone

Rather than attempting a complete transformation overnight, we've selected high-impact use cases that demonstrate value while building team confidence through practice. Each session strengthens buy-in as team members see firsthand how AI can transform their work. These workflows are evolving alongside our platform capabilities, with team members actively contributing improvements based on their daily experiences.

We've already successfully launched two major workflows that emerged from experimentation:

Advanced Team Leadership Assistance System (ATLAS): A comprehensive set of AI-powered workflows for leadership support that I developed through a few hours of trial and error, including templates for:

• Team metric tracking and analysis

• Task completion monitoring

• Capacity report generation

• Status update generation

• Calendar optimization (through Asana <> Claude MCP connection)

These workflows allow me to focus on strategy while AI handles administrative overhead, saving 4–5 hours weekly.

Project Intelligence & Prioritization Planning Assistant (PIPPA): A prompt library for program management that our PMs built through collaborative learning sessions, with templates for:

• Request intake and evaluation

• Task prioritization

• Timeline risk identification prompts

This workflow, which continues to evolve as PMs share new discoveries, enables them to concentrate on stakeholder relationships while AI manages the admin-intensive aspects of project tracking.

Our goal is for each role across our marketing team, from content creation to SEO and email marketing, to build AI expertise through practice with specialized prompt libraries and workflows designed to complement their specific function. This targeted approach ensures that AI enhances, rather than disrupts, existing workflows while building lasting skills.

Scaling with the right infrastructure

We knew from the start that if we were going to scale this learning initiative, we couldn't rely on scattered tools or short-term fixes. We needed a strategic foundation: something that could evolve with us, connect to our existing systems, and empower non-technical teams to learn and contribute directly.

That's why our implementation strategy is centered around using Asana's no-code AI Studio functionality. Since our team already lives in Asana, starting there makes AI adoption feel natural.

This strategic choice provides several advantages for our learning-first approach:

• Reduced consolidation risk: By building on our core work management platform rather than multiple point solutions, we're mitigating the risk of future vendor consolidation.

• Integrated data sources: We're connecting information from our various systems (Contentful, SkillJar, GitHub, Tableau, etc.) directly into our AI workflows.

• Scalable development: The no-code approach allows team members to rapidly learn, iterate, and deploy new prompts and workflows without specialized development resources.

• Consistent experience: Building on a familiar platform lowers adoption barriers and creates a comfortable environment for learning and experimentation. When AI capabilities are woven into daily workflows, adoption becomes automatic.

This approach keeps our AI strategy aligned with the way our teams already work while creating a safe space for learning, reducing barriers to experimentation, and making AI usage an inevitable part of everyone's workday rather than an optional add-on.

Measuring outcomes over outputs

While we track time savings, our definition of ROI extends beyond efficiency. We’re measuring whether AI is enabling:

1. Reductions in administrative workload

2. Improvements in output quality and consistency

3. Increases in strategic thinking time

4. Acceleration of time-to-market

5. Enhanced team satisfaction and engagement

6. Growth in AI literacy and confidence across all skill levels

These metrics show that AI integration isn't just about doing things faster; it's about fundamentally improving how we work and learn together.

The future isn’t more tools; it’s more teamwork

As we continue our AI journey, I believe we're witnessing the beginning of a profound shift in how marketing teams operate. The organizations that thrive won't be those that deploy the most AI tools but those that strategically integrate AI into their teams in ways that complement and enhance human capabilities.

The future belongs to teams that can move beyond the AI Wild West to build coordinated, thoughtful approaches to human-AI collaboration. By creating a strategic framework now, we're not just preparing for this future—we're actively shaping it.

Stay tuned for our next article where we'll explore how we're evolving these shared workflows and prompt libraries into personified, role-based AI assistants that act as true teammates for every member of our marketing organization.