Ex-Intel Marketing Expert Shares How To Use AI In Content Strategy (And How Not To Use It)
Discover how former Intel marketing leader, Pam Didner, uses AI to speed up research, content creation, and AEO analysis while keeping strategy, editing, and audience judgment firmly human-led.
Pam Didner
B2B Marketing Consultant
AI Impact: AI cannot save a flawed marketing strategy; execution is crucial for success.
Content Workflow: Pam Didner uses AI to enhance content workflow with specific tools for drafting and automation.
Human Oversight: Despite AI's role in content creation, human judgment is essential to maintain credibility and quality.
Inconsistency Issues: AI output varies; it’s important to plan for inconsistencies and approach AI as a starting point.
Ongoing Investment: Successful AI implementation requires ongoing time and effort to adapt processes and maintain relevance.
Pam Didner is a B2B marketing consultant, Copilot speaker, and author focused on sales and marketing alignment. She previously worked at Intel as Senior Director of Marketing Operations.
We caught up with Pam to talk about AI in content strategy and execution. Here's what she had to say.
AI will not save a bad strategy
Hi, I’m Pam Didner. I’m a B2B marketing consultant, keynote speaker, and author who has spent my career helping companies connect marketing to revenue, sales alignment, and practical execution.
Want more from The CMO?
Sign up for a free membership to complete reading this article:
Have an account? Log In
At the same time, I serve as a fractional CMO for select clients. In those roles, I step into their existing organizations and work with the teams they already have, often across marketing, sales, and leadership. That means adapting to different team structures, systems, cultures, and levels of marketing maturity.
My journey started in corporate roles long before AI was the hot topic. I worked across finance, operations, supply chain, sales support, and global marketing. That mix of experiences taught me something important early on: Strategy means nothing if teams cannot execute. Fancy slides do not create a pipeline. Clear processes, aligned teams, and measurable outcomes do.
I now help organizations use AI and tools like Microsoft 365 Copilot in ways that matter: faster research, stronger content, smarter sales enablement, and more productive collaboration. Not theory. Not fluff.
Because AI will not save a bad strategy. It will not fix unclear positioning. It will not replace critical thinking. But it can reduce friction, accelerate execution, and give smart teams more room to think strategically. That is why I focus on marketing leadership transformation, not just AI tools.
How AI powers end-to-end content marketing workflows
My content production workflow uses three tools:
- Notion serves as my command center, where I manage every project, brand voice guideline, and audience profile.
- Claude writes the content. It reads the relevant skill.md files and specific prompt guidance, then drafts the content. I built separate skill.md files for blog posts, LinkedIn posts, and Instagram posts. I learned you can't have one brand skill.md. To achieve specificity, you need different skill.md files for different audiences on different channels.
- Manus automates the process. It connects Notion, Claude, and my publishing channels.
Once the draft is ready, my team and I review and edit. We take time to make the content sound human. AI saves you time on the first draft. You still spend real hours editing — if you want a human touch. I do.
How AI can support content strategy and creation
So, I use AI as a strategic assistant to inform decisions, accelerate execution, and surface opportunities, but final judgment remains human.
Let's take an example of content strategy. I rely on AI to scan my website, existing curriculum, service offerings, and past content to identify topic gaps, recurring themes, audience interests, and opportunities I may be overlooking. AI is excellent at pattern recognition and speed. It helps generate possible content directions faster than doing everything manually.
But humans make the final decision on what to write.
As far as content creation, AI helps draft outlines, headlines, first drafts, repurposed versions, and channel variations. That saves time and reduces blank-page syndrome.
But humans always edit before publishing.
Why? Because content still needs judgment, clarity, nuance, examples, fact-checking, and personality. AI can draft. Humans make it credible and worth reading.
I also use AI to help codify and apply my brand voice across channels such as website copy, blogs, video scripts, LinkedIn posts, and email content. AI can adapt tone and structure based on channel needs while staying aligned to my positioning.
Why AI output is still too inconsistent
That’s the honest reality, and more marketers need to say it out loud: AI content recommendations and drafting are inconsistent.
Sometimes the output is sharp and surprisingly useful. Sometimes the output is generic, off-target, bland, or completely disconnected from what the audience cares about. And sometimes, it gives you something usable, but only after a serious rewrite.
Ugh! That's why I treat AI as a starting point, not a finished product. AI can save time, but only if you know what good looks like first.
Plan for inconsistency, and you stop being surprised by it.
How AI can help with AEO strategy
Instead of treating my website like a traditional SEO project focused on keywords and rankings, I treated it like a source that AI systems needed to understand, trust, and recommend.
Here's something else I did recently with AI. I used Claude and ChatGPT to evaluate my website through the lens of AEO (Answer Engine Optimization). Instead of treating my website like a traditional SEO project focused on keywords and rankings, I treated it like a source that AI systems needed to understand, trust, and recommend.
I asked AI tools to assess my website's structure, messaging clarity, authority signals, topic coverage, speaking pages, service pages, FAQs, and how clearly my expertise was communicated. AI helped identify gaps such as vague positioning, thin topic pages, weak proof points, and content that humans might understand, but AI systems could not easily interpret.
Then came the important part: I did not blindly follow every recommendation. I reviewed the suggestions, applied business judgment, and chose what aligned with my brand and goals.
This resulted in significant growth in AI visibility and authority.
AI did not fix my website. It acted like a sharp analyst. It identified blind spots, patterns, and opportunities faster than I could manually. My role was still critical. I decided what mattered, what fit my positioning, and what to ignore.
That is how AI creates value in marketing. It gives direction. And together, we improved outcomes.
Why AI falls short in presentation development
AI still isn't there in presentation development, especially when I need a deck that exactly matches what I see in my mind.
It can help generate slide titles, summarize ideas, suggest layouts, and draft content. It provides a useful rough starting point. But AI still falls short when building a "keynote" and "training" presentation with the right narrative flow, pacing, emotional buildup, transitions, and audience energy.
Why regular AI use in marketing is essential
My advice to marketing leaders during this moment of change is simple: Start using AI regularly, not occasionally.
Do not wait until you feel fully ready. Do not wait for the “perfect strategy.”
Prompts matter, but do not let prompting become a barrier. If your organization has tools like Microsoft Copilot with prompt coaching features or similar helpers, use them. They can help refine instructions and show better ways to ask. Just work at it.
Many people overthink AI. Start simple, then improve.
Why AI cannot replace marketers
When I started with AI, I thought it could run the whole process without human oversight.
I tried to automate end-to-end. It didn't work. You can't leave it 100% to AI.
Management has been told that AI will replace people. It can't. Not entirely. AI takes the first draft off your plate. It does not take the editing, the strategy, the emotional read of your audience, or the call on what to publish. That work is still human.
So automation does not equal replacement. It just means redistribution of your team's workload. AI handles the volume. Humans handle the judgment.
Why AI requires upfront and ongoing time investments
Redesigning your workflow matters. You need to give much thought to what goes into your skill.md files. You need to decide which tools to use and how to connect them. You need to be deliberate about the whole process.
You also need to allocate time for testing. AI takes more time than you think to build right. Even after you build it, you still need to tweak it frequently.
It takes time! AI doesn't come quickly or easily.
And it is not set-and-forget. I revisit those skill.md files often. Your customers are living beings. They are constantly changing. Your content needs to adjust to that. Your AI process should adjust accordingly. The leaders who treat AI workflows as living systems, not one-time builds, will get the most out of them.
Follow along
You can follow along with Pam Didner's work on her website and LinkedIn.
More expert interviews to come on The CMO Club!
