GrowthPath Partners LLC

Empowering Purpose-Driven Growth

Posts

Evolving AR: Managing Signals in the Age of AI

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AI decides which vendors buyers see and evaluates them before buyers ever do.

Analyst Relations teams now manage signals that influence both people and the AI systems they rely on. This is different from managing analyst relationships alone.

I’m keynoting at ARInsights’s Engage Live in San Francisco on November 12 to talk about how AR is evolving in the AI era. We’ll cover:

  • ➡︎ How analysts and buyers are using AI to evaluate vendors faster

  • ➡︎ Which signals AI systems pull from and which ones you can influence

  • ➡︎ Why consistency across every touchpoint drives visibility and trust

  • ➡︎ How AR becomes a strategic insight engine for your business

If you’re leading AR or marketing strategy, I’d love to see you there.

See link in the comments to learn more and register.

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We Spent $309B on AI. Why Aren’t People Ready?

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We’ve spent $309 billion training AI. Only $11 billion training people to work with it.

I joined Julie Williamson, PhD on The Failure Gap podcast to dig into what happens when leaders agree they need to move on AI but can’t get aligned on how. Perfect for background listening (links in comments) this weekend while you’re doing meal prep or putting up your Halloween display (We got that done yesterday. 🎃)

The conversation balances the why behind AI transformation with real steps to take action. We covered everything from why legal at Moderna was one of the first teams to hit 100% AI adoption to how naming your AI teammates can change how teams engage.

Here’s what you’ll walk away with:

  • ➡︎ Three critical mindset shifts that move teams from AI as a tool to AI as a teammate

  • ➡︎ How to protect confidential information while still getting started with AI

  • ➡︎ Why using multiple AI platforms makes your thinking stronger and reduces hallucinations

  • ➡︎ Real techniques for pressure-testing your strategies using AI from different perspectives

  • ➡︎ Why AI literacy is foundational regardless of your title or technical background

Thanks to Julie and the Karrikins Group for creating space for this kind of conversation. Their focus on closing the gap between agreement and alignment is exactly where most organizations get stuck with AI adoption. And thank you Kerrie Luginbill for thinking about me and introducing me to Julie.

The most expensive infrastructure purchase is the one people can’t use well. This conversation gives you a path forward.

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Marketing AI Assessment: Build Your Roadmap

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Here’s what a few minutes of honest assessment showed one marketing team:

Strong AI adoption in social and sales enablement. Zero in demand gen, analytics, and paid media. 19 pilot-ready opportunities worth exploring.

They knew they were early in their AI journey. The data confirmed it and showed them exactly where to focus.

51 potential AI use cases across their marketing org. 15 actively used. 36 still awaiting action.

We mapped their current state, then guided AI to analyze where they stood against the 4 mindset shifts I wrote about a few weeks ago (link in comments):

  • ➡︎ Answer engine → Thought partner

  • ➡︎ Faster → Better → Different

  • ➡︎ Tool → Teammate → Systems

  • ➡︎ Org charts → Work charts

The analysis turned gut feelings into an initial roadmap. Not just “we need to do more AI” but ideas for where to expand, which current tools to leverage, and which gaps to close first.

I used Claude to create an interactive dashboard that visualized the analysis (see video of the dashboard in action below). You can ask other AIs like ChatGPT and Gemini to do the same with your data.

Here’s the approach:

  • ➡︎ List potential AI use cases across your GTM functions

  • ➡︎ Mark what you’re actually doing (be honest)

  • ➡︎ Note which tools, which teams, what value

  • ➡︎ Look for patterns like adoption clusters, tool overlap, missing areas

  • ➡︎ Ask AI to analyze it against the 4 dimensions: “Where am I on each shift? What should I prioritize?”

Wherever you are on this journey (crawling, walking, or running) clarity on where you’re standing gives you a roadmap forward.

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Filipino Women in AI: Seeing What’s Possible

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Asianna Danielle J. Junge, a junior at Rice University, came up to me after my keynote at AMA Houston – American Marketing Association’s Marketing Edge conference today.

She told me she’d learned a lot and wanted to know more about the research I referenced showing women use AI 16-20% less than men at work. (See link in the comments to a post I shared on this topic last week.)

“I was inspired to see an Asian woman executive leading a discussion on AI. I’ve never seen a Filipino woman do this. I’m Filipino too.”

We don’t talk enough about representation in AI and tech. I’ve decided to speak up more in rooms that stay quiet on this.

In my talk, I mentioned that I worry about my aging mother in Manila. Although my daughter is only a few miles away at Colorado University – Boulder, I miss her dearly. I get sick, exhausted, distracted. I’m affected by my environment in ways AI isn’t. But AI doesn’t have a moral compass, so I guide it so it knows right from wrong.

We have different strengths. We can overcome each other’s limitations.

Meeting Asianna reminded me why this matters. If showing up and doing work I care about helps someone see what’s possible for them, that’s enough.

To anyone who wonders if their voice is too small… it isn’t. The vision for AI is to benefit all of humanity. We need your perspective at the table.

Thank you to Sheana Hamill, Henry Adaso, Joel Luks, and the AMA Houston team for inviting me and creating space for these conversations.

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GTM AI Stack: Start Smart, Innovate, Specialize

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One question I hear constantly from GTM leaders is “What should our AI tech stack look like?”

I generally provide this guidance:

1. Start with what you already have.

Your CRM, marketing automation platform, CMS, and analytics tools already have AI built in or coming soon. Use those first. You’ll stretch your budget further, adoption is easier, and you’ll see results faster. Don’t buy new when you haven’t squeezed value from what you’re already paying for.

2. Use foundational models to innovate.

Pick one or two of the foundational models like ChatGPT, Claude, Gemini, and Copilot. Go deep. These platforms are where the real innovation is happening. They show you what’s possible. And they let you build custom GPTs, agents, projects, and workflows for integrated campaigns, enablement programs, customer research, competitive analysis.

3. Only then look at specialized AI tools and be strategic.

If 1 and 2 above don’t solve it, then consider niche tools. But evaluate carefully. Who’s the team? The investors? What’s the competitive moat? Can you trust them with your data?

A tool doesn’t need a 10-year moat to be worth using. If it solves a real problem today and delivers ROI, that’s valuable. Just go in eyes open.

Know that some of these tools may get absorbed into foundational models, acquired by larger platforms, or become irrelevant as the tech evolves. Address the problem now, but stay flexible. Don’t sign long-term contracts. Don’t build your entire strategy around a tool that might not exist in its current form in 18 months.

Want to go deeper on specialized AI tools? Both Tahnee Perry and Justin Parnell have spent a lot of time understanding and getting their hands dirty with various tools from creative to automation platforms. They share insights generously and are worth following.

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