AI Enablement For B2B Marketers

In this insightful episode of The B2B Growth Show, Paul Slack is joined by AI and marketing expert Christopher Penn to tackle one of the biggest challenges facing B2B teams today: how to move from experimenting with AI to actually operationalizing it across the organization.

While most marketers are already using AI in some form, many are still stuck at the individual-use stage—testing prompts, trying new tools, and searching for repeatable use cases. Christopher breaks down what it takes to turn that experimentation into scalable business value, from choosing the right problems to solve to building better workflows, agents, data practices, and definitions of success.

Key Takeaways:

• Using the 5P framework, start with the business problem, not the AI tool: Purpose, People, Process, Platform, and Performance
• Identify high-value AI opportunities by evaluating tasks based on time, repetitiveness, importance, pain, and sufficient data
• Stop treating AI like a “texting buddy” and start treating it like a junior team member you can delegate clearly defined work to
• Build measurable definitions of “done” instead of simply trusting AI to produce the right answer
• Scale AI adoption through team knowledge-sharing, experimentation, and practical peer-to-peer learning
• Understand the shift from prompts and projects to agentic AI, and why strong management and delegation skills will become increasingly important
• Give AI only the context it needs rather than overwhelming models with unnecessary documents and data
• Prioritize trustworthy data sources instead of waiting for a massive, company-wide data cleanup project

One of the session’s biggest themes is that successful AI enablement isn’t really about chasing the latest model or tool. It’s about building better processes around AI.

Christopher explains that as AI becomes more agentic, marketers will increasingly move from being individual contributors to becoming managers of AI-powered workflows. That means clearly defining tasks, supplying the right context, establishing quality gates, and giving AI measurable criteria for success.

The session also explores how marketers can improve the quality of AI-generated content by creating more precise, measurable context around writing style, brand requirements, customer insights, and desired outputs, rather than dumping massive amounts of information into every prompt or project.

The session provides practical guidance on:

• Finding AI use cases that create meaningful organizational value
• Moving from prompts and custom GPTs to AI agents and autonomous workflows
• Running AI-powered customer focus groups to test ideas and messaging
• Determining which company data is reliable enough to use with AI
• Creating smaller, more useful “knowledge blocks” for AI context
• Managing the rising cost of AI usage and understanding token economics
• Adapting SEO and AI visibility strategies as AI search becomes increasingly agentic
• Making websites more accessible and easier for both people and AI agents to navigate

Christopher also challenges some of the conventional thinking around Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO). As AI models increasingly rely on live search, external tools, and personalized context rather than static training data, he argues that many AI visibility strategies will ultimately converge with strong SEO fundamentals.

Whether you’re a B2B marketing leader building an AI roadmap, a team trying to scale beyond one-off experiments, or a marketer wondering how agents, data, context, and AI search fit together, this session offers a practical framework for turning AI enthusiasm into measurable business value.

Catch the next B2B Growth Show live by registering here.