From Crawl to Run: A Practical Guide to AI Maturity in Marketing

When it comes to implementing AI in marketing, many teams believe they're further along than they actually are. Nathan Thompson, Head of Content Strategy at Copy.ai, states: "I think people's processes were a lot less clear than they had hoped or thought... and now that we are trying to codify processes, they're realizing I need a more firm process in place."

In this episode of Future Proofed, Nathan Thompson joins co-host Ryane Bohm, Head of Product Marketing at Copy.ai, to discuss the "Crawl, Walk, Run" framework for AI adoption. This practical model helps marketing leaders identify their current stage of maturity and provides a clear path to advance their teams' capabilities without sacrificing quality or strategic oversight.

Throughout the conversation, Ryane Bohm and Nathan Thompson explore the common challenges holding teams back in the "Crawl" phase, the risks of scaling AI without a solid foundation, and what a truly AI-powered marketing operation looks like at the "Run" stage. They emphasize the importance of codifying intuitive processes, maintaining unified messaging, and keeping humans in the loop for strategic decisions.

This framework offers valuable insights for navigating the AI adoption journey responsibly and effectively. Use it whether you're just starting to experiment with AI chat tools or looking to fully integrate AI into your marketing workflows. Let's dive in and discover how to take your team from crawling to running with AI.

"I thought I was much more documented than I was."

This admission from Ryane Bohm, Head of Product Marketing at Copy.ai, captures a truth that's hitting marketing teams across the industry: the processes we think are well-defined often exist more in our heads than on paper—and AI is exposing this gap with uncomfortable clarity.

Many companies rushing to implement AI tools find themselves stuck at the starting line, unable to move beyond basic chatbot interactions. The culprit? Years of intuitive, undocumented workflows that worked fine when humans were the only ones executing them, but now fail to translate to AI systems.

In this conversation from the Future Proofed podcast, Ryane Bohm joins co-host Nathan Thompson to explore the "Crawl, Walk, Run" framework for AI adoption in marketing. Drawing from her experience leading product marketing at AI-powered revenue platforms like Copy.ai, Clari, and Gong, Bohm offers a refreshingly honest perspective on why most teams remain trapped in the "crawl" phase—and more importantly, how to break free.

What emerges is a practical roadmap for marketing leaders who want to effectively tap into AI's power without sacrificing quality or strategic oversight. From codifying hidden processes to maintaining unified messaging at scale, Bohm and Thompson tackle the real challenges teams face when moving from individual AI experiments to organization-wide transformation.

This guide will help you diagnose where your team stands—and chart a clear path forward. Start here whether you're just beginning with ChatGPT or ready to build automated workflows.

The Crawl Phase: Why Most Teams Are Stuck in the Chatbox

The Core Challenge: Turning Intuition into Process

The majority of companies currently rely on basic AI chat tools to complete one-off tasks, placing them in the "Crawl" stage of AI adoption. But these tools often fail to deliver transformative results, providing only a marginal boost in efficiency. Individual workflows frequently based on intuition and lacking documentation present the primary hurdle preventing teams from advancing to the next stage.

Codify what your team knows implicitly before you can effectively scale your marketing efforts with AI. Turning intuition into clear, documented processes provides the foundation upon which to build more advanced AI capabilities.

The Walk Phase: Moving from Siloed Tasks to Unified Workflows

The Risk of Speed: Scaling the Right Message

Teams can begin transitioning from the Crawl phase to the Walk phase once they have successfully documented their core processes. A shift from using AI for individual task completion to automating cross-functional workflows characterizes this stage. Establishing a unified messaging strategy becomes absolutely critical at this point.

Prioritize the creation of unified content briefs and style guides to feed into AI tools. This mitigates the risk of scaling inconsistent or off-brand content. Marketers can tap into the speed and scale of AI without sacrificing quality or accuracy by making sure all automated content adheres to a consistent brand voice and messaging strategy.

The Run Phase: What True AI-Powered Marketing Looks Like

Beyond Automation: The Proactive Human-in-the-Loop System

The Run phase focuses on creating a sophisticated human-in-the-loop system. In this model, AI handles the heavy lifting but human marketers always retain control over strategy and final publishing. Aiming for 100% automation is not the goal.

As Ryane Bohm succinctly puts it, "AI is not the one pushing publish. The poor content problem is a human problem. It's not an AI problem. They are not publishing it, you are."

Bohm's vision for a "product marketing dashboard" perfectly illustrates what an advanced, human-led Run system might look like. The AI proactively synthesizes competitive intelligence, identifies potential gaps or opportunities, and suggests high-impact content ideas—all before the marketer even thinks to ask. This frees up the human expert to focus on high-level strategy and creative direction, while the AI handles the time-consuming legwork.

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Ryane Bohm and Nathan Thompson provided a practical roadmap for marketing leaders looking to advance their teams' AI capabilities. They've offered valuable insights on how to navigate the challenges and opportunities at each level by breaking down the adoption journey into three clear stages - Crawl, Walk, and Run.

At the "Crawl" stage, focus on codifying intuitive processes and turning individual knowledge into documented workflows. As teams move into the "Walk" phase, shift the emphasis to unifying those processes across functions and ensuring consistent messaging at scale. Finally, at the "Run" stage, AI becomes a proactive assistant, handling tasks like content creation and competitive analysis, but always with human oversight on strategy and publishing.

Throughout the discussion, Ryane Bohm and Nathan Thompson emphasize that the goal of AI adoption isn't to replace human marketers but to augment their capabilities. AI can free up marketers to focus on higher-level strategic thinking by automating repetitive tasks and providing data-driven insights.

Ryane Bohm succinctly states: "The poor content problem is a human problem. It's not an AI problem. They are not publishing it, you are." Speed and scale with AI are only valuable when built on a foundation of clear processes and human judgment.

Marketing leaders can unlock the full potential of AI while maintaining the quality and integrity of their brand messaging by following the "Crawl, Walk, Run" framework.

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