The biggest challenge in AI adoption isn’t the technology. It’s managing change–bringing people along on the journey.

In my work with go-to-market teams, I’ve noticed a pattern in how people respond to AI. People tend to fall into three groups when it comes to embracing AI responsibly:

• ▶︎ Trailblazers (First Third) – These are your enthusiasts who instantly see AI’s potential. They’re eager to dive in and experiment. Love their energy, but the key is channeling it to help others, not just racing ahead. They’re brilliant at spotting new ways to work smarter with AI.

• ▶︎ Fast Followers (Second Third) – They’re practical folks who want to see it work before jumping in. Show them how AI can be a helpful teammate in getting projects started faster, making ideas better, and handling the repetitive work. Once they see real results, they become your best advocates for wider adoption.

• ▶︎ Later Adopters (Last Third) – They ask the tough questions about jobs and ethics – and honestly, we need that perspective. For them, AI needs to earn its place as a partner, not a replacement. Some will come along gradually or carve their own path. For others, success might mean thoughtful conversations about evolving roles that better align with their strengths, whether within our org or beyond.

It’s important that we meet people where they are while keeping the momentum going. Inspire them with real AI examples that matter to their daily work, and give them space to learn without overwhelming them.

Part of compassionate leadership is helping each person find their best path forward with dignity and support.

Remember that adopting AI is about changing mindsets and behaviors, not just using new tools. We’re all figuring this out together, balancing it with everything else in our lives. A little empathy goes a long way.

What patterns have you seen in your company’s and team’s AI journey? Has your experience with these thirds been different? How are you driving change?

#AIAdoption #ChangeManagement #Leadership #ResponsibleAI #Empathy GrowthPath Partners Xapa

I’ve compiled what I believe are 10 of the most underrated, yet effective, ways to guide AI. View the slide carousel below.

These are underrated because:

• Most of us still use AI like a fancy search engine. Type a question, get an answer, move on.

• We don’t think of AI as a thinking partner. Most people just give it tasks instead of engaging in back-and-forth dialogue.

• We often settle for “good enough” first drafts. Few people realize how much better results can get by iterating with AI.

• We want quick answers. Taking time to plan or analyze first feels like extra work even though it leads to better results.

What makes this particularly interesting is that these approaches aren’t new. They’re how we work with colleagues, consultants, and mentors. But most haven’t realized we can use these same powerful techniques with AI.

We’re still in the early stages of understanding how to truly work with AI. It’s like having a smartphone but only using it to make calls. There’s so much untapped potential.

Which of these will you try? What other underrated approaches have you uncovered?

For more insights on effective AI prompting, check out Ethan Mollick’s excellent post here: https://lnkd.in/g7t9fj2P

#AI #ThoughtPartner #AICollaboration #PromptEngineering #Strategy GrowthPath Partners

Hello go-to-market leaders, strategists, and innovators! 👋 Thank you for dropping by to learn practical AI applications and gain strategic insights to help you grow your business and elevate your team’s strategic value.

Quick Take

Most AI teams are optimizing their prompts. The best are redesigning how they think.

If your AI work feels decent but underwhelming, you’re not alone. Most teams are spending time perfecting AI conversation mechanics while competitors gain real advantages by asking fundamentally different questions.

What you’ll discover:

• Why teams with solid prompting skills still hit walls

• The one shift that separates AI tools from AI thinking partners

• Seven thinking moves that uncover insights your competitors miss

• Why mastering strategic questioning now determines who wins with AI agents later

• Real examples of teams turning AI limitations into breakthrough opportunities

The difference isn’t better prompts. It’s the courage to question what everyone else takes for granted.

How are you really using AI right now? Take 60 seconds for personalized insights and guidance on how to get more out of AI.

Take your AI Working Style Assessment here.

Prefer to Listen? Try the AI-Generated Podcast

For those who prefer to consume information through audio, I’ve used Google’s NotebookLM to transform this newsletter into a short podcast episode, featuring a natural conversation between two AI hosts. You can listen to the 15-min podcast here while driving, walking the dog, or doing chores. Once you hit play, give it just a few seconds then it will start.

What I Keep Seeing

A few months ago, I worked with two SaaS companies.

Company A had given up on AI for strategy work. “We tried it for competitive analysis and market research. The outputs were generic. AI just isn’t there yet for complex thinking.”

Company B was satisfied with their AI usage. “We use it for email drafts, call summaries, and content outlines. Saves us 5 hours a week. We’ve got this figured out.”

Both teams were using solid prompting techniques. Good structure, clear context, examples. But both were treating AI like a better search engine instead of a thinking partner.

But the problem isn’t AI’s capabilities. It’s the depth of your questions.

The Missing Piece in Every Prompting Framework

OpenAI, Anthropic, and Google have published excellent prompting guides covering structure, examples, and parameter tuning. I use a framework called GRACE – inspired by Christopher Penn‘s RACE framework, adding G for Goal because stating the objective upfront keeps both you and the AI focused.

Here’s what this looks like in practice:

Same mechanics. Completely different results.

Prompting techniques are getting easier. As AI advances with better memory, reasoning, and context understanding, the technical mechanics will become simpler.

The thinking layer – how deep your questions go, what assumptions you challenge – that’s the human advantage that matters more as AI advances. AI can’t push you to think deeper. It can only work within the cognitive framework you provide.

From AI Tool to AI Thinking Partner

Most teams ask AI: “Help me write a sales email.”

Strategic teams ask: “Challenge my assumptions about why prospects aren’t responding.”

This shift changes everything. Jason Cormier, Founder of AI Marketing Forum, sees this pattern across the marketing community.

“I see teams master the mechanics of prompting but still hit walls. They’re missing what I call “directive intelligence.” It’s the ability to guide AI toward what you don’t already know.

Most people use AI to confirm what they think. The best use it to discover what they’re missing. If you’re working through this, you’re not alone. We have hundreds of marketing leaders sharing what’s working in the AI Marketing Forum.”

More teams are starting to build AI teammates (using custom GPTs, Claude Projects, Gemini Gems, etc.) that work alongside them to do specific work. You can read more about a human-AI powerhouse team case study and step-by-step playbook here.

The quality of your AI teammate depends on how you guide their thinking. Give them tasks, get an assistant. Ask better questions, get a thinking partner.

7 Ways to Think Deeper

These seven thinking moves help you reframe problems before you even write a prompt. Each one helps you see the problem differently, often in ways your competitors haven’t considered.

1. Challenge Your Assumptions

Instead of: “How do we reduce churn?”

Try: “What if churn isn’t the problem? What if it’s showing us a product gap?”

Why it works: You pause before fixing and ask if you’re solving the right thing.

Potential outcome: A SaaS team discovers churned customers outgrew their product. Churn becomes upsell opportunities.

2. Borrow from Other Industries

Instead of: “How do we improve trial conversion?”

Try: “How do language learning apps keep people engaged daily?”

Why it works: You find new ideas by studying how others solve similar problems in different contexts.

Potential Outcome: A product team adds streaks and milestones to help users reach activation faster.

3. Try the Opposite

Instead of: “How do we shorten the sales cycle?”

Try: “What if making it longer helped us close bigger deals?”

Why it works: Sometimes the thing you’re trying to optimize is the thing getting in your way.

Potential Outcome: A B2B company adds business audit step, helping them close higher-ACV customers.

4. Find Hidden Connections

Instead of: “How do we improve pricing?”

Try: “What patterns show up when we compare churn reasons to our competitors’ ads?”

Why it works: Some of your best insights live in unlinked data.

Potential Outcome: A team repositions after discovering churned users match competitor’s target audience.

5. Find the Simplest Change

Instead of: “How do we drive more revenue?”

Try: “What’s one sentence in our demo that changes how people see the product?”

Why it works: Small shifts often create the biggest results.

Potential Outcome: A team moves their outcome statement to demo opening for better conversion.

6. Find the Excluded

Instead of: “How do we raise prices?”

Try: “Who are we unintentionally leaving out?”

Why it works: You expand opportunity by seeing who’s missing.

Potential Outcome: An analytics platform creates startup tier, opening new market segment.

7. Use Old + New

Instead of: “How do we improve email performance?”

Try: “What if we brought back personal touches using today’s tools?”

Why it works: Some tactics work no matter the decade.

Potential Outcome: A team adds timely check-ins and thank-yous based on user behavior.

Rhiannon Naslund, Chief Marketing Officer at Origami Risk is driving this shift in thinking and evolution in her team.

“This kind of shift in thinking doesn’t come naturally to everyone. That’s why we’re focused on giving people the space to learn and build confidence.

We’re showing what it looks like to guide AI with deeper thinking, using real examples that connect to their role. When someone sees how the way they structure a question changes what AI gives back, like refining messaging for a healthcare risk manager or pressure-testing a new idea, it clicks. They start to see how much impact they can have by pushing AI to think differently.”

The Bigger Picture

Whether you think you’ve mastered AI or you’re still struggling with it, you’re probably operating at 20% of what’s possible.

The biggest AI advantage doesn’t come from better tools or prompts. It comes from questioning what everyone else takes for granted.

This becomes critical as we move toward AI agents that work autonomously. Teams that can’t think strategically with AI now won’t be able to build agents that think strategically later.

Erin Mills, CMO of Quorum and co-host of FutureCraft GTM Podcast, sees this connection clearly as someone building both AI strategies and autonomous systems.

“Organizations with strong fundamentals in strategic AI use are better positioned for what comes next. If your team struggles to frame the right problems or identify blind spots in their current approach, those same gaps will show up when you try to build AI agents that operate independently.

In our FutureCraft GTM conversations, we’re seeing a shift toward systems that make decisions on their own. What matters most now is having the judgment to guide them well. The teams that master strategic questioning now will be the ones successfully deploying autonomous AI later.”

Your next competitive advantage may be hiding in a question you haven’t asked yet.

Your Next Steps

Pick one challenge your team is working on this week. Before jumping into solutions, ask: “What assumptions are we making that might not be true?”

Then reframe it using one of the seven thinking moves above.

Want your team to think deeper? Forward this newsletter. The shift from good prompting to strategic thinking separates the winners from the optimizers.

The Practical AI in Go-to-Market newsletter is designed to share practical learnings and insights in using AI responsibly. Subscribe today and let’s learn together on this AI journey!

For those who prefer more interactive learning, explore our applied AI workshops, designed to inspire teams with real-life use cases tailored to specific go-to-market functions.

Also check out this team transformation case study and step-by playbook of how we helped transform a lean GTM team into a human-AI powerhouse with human and AI teammates.

Or, if audio-visual content is your style, here are virtual and in-person speaking events where I’ve covered a variety of AI topics. I’ve also keynoted at many organization and corporate-wide events. Whether through the newsletter, multimedia content, or in-person events, I hope to connect with you soon.

I’m taking a break from our usual AI discussions to share something personal as we prepare for Thanksgiving. Phil Nugent recently featured my story in Colorado AI News. It made me reflect on how life’s detours often guide us to where we need to be.

This year has seen incredible AI progress. Yet what matters most isn’t the technology. It’s the amazing people who make this journey worthwhile. It’s the communities that lift us up. The partners who share our mission. The champions who make space for all voices. The family who keeps us grounded.

In this newsletter, I thank many wonderful people who’ve shaped my path. A single newsletter can’t capture everyone who deserves recognition. To those named and the countless others who’ve made a difference. Thank you.

The newsletter also includes a link to a AI podcast version for those who are auditory learners or simply prefer to listen to podcasts.

As we gather for Thanksgiving, I’d love to hear your story. Who are you grateful for? What unexpected turns brought good things to your life?

#ThankYou #StrategicMarketing #ForceForGood #DEI #AI

When I showed these retro hairstyles to ChatGPT and Claude, their responses showed how different they are. It proved what I’ve seen while working with them for quite some time.

I was inspired by a journalist who let AI make all her decisions for a week, even her haircut! (Check out the article in comments)

I wanted to test what I thought about these two AIs in a fun way. No, I’m not really thinking about these 70s styles 😄, but I knew their answers would show how they think differently.

I asked both to pick a hairstyle. ChatGPT jumped right in with specific advice and style details. But Claude politely said no and suggested I talk to a real stylist!

I then showed each AI what the other said and asked them to explain the differences. You can see their responses in the carousel below.

This matches how I use them at work:

• I turn to Claude as a thought partner, especially for strategy where we need to align and bring different people together. It’s more careful and thoughtful, great for people-focused work.

• I use ChatGPT when I need quick, clear answers. It’s fast and direct – perfect for information gathering, data analysis, and straightforward tasks.

Often, like in this test, I find it helpful to use both. This helps catch any mistakes, gives me more ideas, and leads to better answers.

It’s not about which one is better. It’s about picking the right tool for the job.

They’re simply trained differently. One prioritizes direct engagement, the other professional boundaries.

What’s your experience? Have you noticed these AI “personality differences”? How do you pick which one to use for different tasks?

#ChatGPT #Claude #AITraining #FutureOfWork #AICollaboration GrowthPath Partners