In this episode, Ryane Bohm and Nathan Thompson from Copy AI sit down with Emily Pick, Lead Product Marketing Manager at Clari, to explore the real-world impact of AI in product marketing. Emily shares her journey from AI experimentation to advocacy, highlighting how AI tools are reshaping product marketing management (PMM) roles and workflows.

Key Themes & Takeaways:

1. Adoption of AI in Product Marketing
   • Emily describes her transition from “ad hoc ChatGPTing” to intentionally scaling AI across her team.
   • Quote: “If you’re not using AI now, like you’re behind...there’s maybe a little bit of foresight, a bit of career future-proofing, kind of reading the tea leaves.”
   • She’s become an internal AI evangelist, helping others see practical use cases.
2. AI Use Cases for PMMs
   • Updating Marketing Assets: AI is leveraged to update core materials like one-pagers, highspot assets, and sales decks—saving weeks of manual work.
     • Quote: “It would update the copy for me…I still think AI is at like 75 to 80% as far as output…that 75 to 80% lift is huge.”
   • Competitor & Market Research: Tools like Glean and ChatGPT help mine internal data and public forums like Reddit to surface real customer conversations.
   • Custom Asset Generation: AI enables sales and field teams to generate tailored one-pagers with the click of a button, freeing PMMs for higher-value work.
3. Challenges & Considerations
   • Accuracy & Hallucinations: AI output isn’t perfect; manual review and careful prompting are essential to avoid “confidently wrong” results.
     • Quote: “Can you imagine co-signing your name to an AI report that’s just so wrong…then they’re like, ‘Did you even check this?’”
   • Prompting & Guardrails: Success depends on specific, thoughtful prompts and ongoing trial and error as models evolve.
   • Data Privacy: Emily stresses not to input proprietary data into public AI tools without an enterprise license.
     • Quote: “‘Free is never free’—you might not be paying money, but you might be paying with your data.”
4. Career Impact of AI for PMMs
   • AI helps PMMs “future-proof” their roles and scale themselves, especially as teams shrink and expectations rise.
   • Quote: “AI won’t replace you, but somebody who uses AI will.”
   • Offloading repetitive work opens opportunities for more strategic, analytical tasks.
5. Getting Started with AI as a PMM
   • Emily recommends beginning with AI features in existing tools, then experimenting with general tools like ChatGPT.
   • Always be mindful of what data is being shared, especially in free or non-enterprise environments.

In this episode of Future Proofed, Ryane Bohm and Nathan Thompson break down the stages of AI adoption in marketing, exploring how companies move from basic chat tools to full-scale AI integration, and what it really takes to operationalize AI for messaging, workflows, and strategy. They share hands-on advice, candid pitfalls, and a future vision for AI as the marketer’s ultimate assistant.

Key Themes & Takeaways:

1. AI Marketing Maturity: From Crawl to Run

• Companies typically move from using basic chat tools (“crawl”), to building workflows and agents (“walk”), to aiming for near-full automation (“run”).
• Most teams are still in the early “chat tool” stage, with few reaching advanced integration.
• “I thought it would be a little bit further along by now… I think we're still seeing people in figuring out how to do things with tools like chat.”

2. The Documentation Dilemma

• Implementing AI reveals how many workflows are undocumented or based on intuition.
• Codifying processes is essential before scaling with AI.
• “People have been doing their jobs a lot more intuitively than they've understood or admitted, and now they have to put all that on paper.”

3. Small vs. Large Companies: Speed and Scale

• Small companies can rapidly design new AI processes without red tape, gaining agility.
• Larger organizations benefit from resources and formal documentation but move slower.
• “You have so much more freedom in designing the pipes… If it doesn't work, do it different next time.”

4. Automation Needs a Human Touch

• Full automation is not the goal—humans must own strategy, final decisions, and quality control.
• AI should augment, not replace, human judgment.
• “I don't think there should ever be full automation on strategy… AI is not the one pushing publish. The poor content problem is a human problem.”

5. Messaging & Brand Consistency Risks

• AI can scale the right message—or misinformation—very quickly.
• Unified messaging and oversight are critical as teams scale AI-generated content.
• “Then you're scaling either misinformation or incorrect positioning 10 times faster.”

6. The Future: AI as Proactive Assistant

• Envision AI dashboards that proactively deliver insights, competitive research, and content ideas—before marketers even ask.
• “I have this dream… AI has synthesized everything the competition is doing and suggested next best content.”
• AI as an “invisible assistant with a photographic memory that makes me look awesome.”

In this episode of Future Proofed, Nathan Thompson and Ryane Bohm dive deep into how AI is shaping the future of content marketing. They explore the intersection of creativity, strategy, and ethics—offering actionable insights for marketers building an AI content marketing strategy.

Key Themes & Highlights:

1. AI as a Creative Assistant, Not a Replacement
   • AI is a powerful tool to enhance creativity, but human input is essential. “AI at this point is only as good as the person that's really powering it.” (Ryane)
   • The real risk? Outsourcing your thinking entirely to AI. Human guidance prevents content from becoming “super dull and everything is the same.” (Ryane)
2. The Human-in-the-Loop Process
   • Effective AI content starts with humans “training” the AI—feeding it brand voice, context, and examples.
   • Editing and refinement are non-negotiable: “Once you do the prep work, then you just give it a lot of information ... then it knows how I speak and can give me a little bit back.” (Ryane)
   • Brainstorming with AI sparks new ideas, but the best results come from back-and-forth collaboration: “It wouldn’t have existed without AI, but AI didn’t think it up either.” (Nathan)
3. Prompting & Brand Voice
   • Prompts matter. Vague requests yield generic results.
   • “The most clever way of prompting that I’ve heard is prompt yourself, essentially.” (Ryane)
   • Prepping AI with examples ensures outputs align with your brand’s personality and goals.
4. Future of Content Marketing: Personalization & Multimedia
   • Hyper-personalized content experiences are the future: “I want to log into a website and it’s just about me ... hyper-personalized to an extreme.” (Ryane)
   • Expect a shift toward audio and video, with AI enabling new creative formats: “People with original thinking [will] do some really cool stuff with video and audio.” (Nathan)
5. Ethical Considerations in AI Content Creation
   • Transparency is key: “Being straightforward with what you're doing and you're not trying to trick someone.” (Ryane)
   • Always check for accuracy and brand alignment before publishing.
   • Beware of IP theft and misuse of AI-generated video/audio content.
   • Ethics are a human responsibility: “The ethics question, again, is not an AI question. The ethics question is a human one.” (Nathan)