Practical AI in Go-to-Market Get practical insights in using AI for go-to-market strategy, initiatives, workflows, and roles.
Hello go-to-market leaders, strategists, and innovators! đź‘‹ 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
While most companies chase AI citations and search rankings, they’re missing something bigger. AI systems are already analyzing your brand, judging who you serve best, and recommending you (or not) — whether you guide them or not.
And they can only be as clear as you are. If you’re fuzzy on who you serve and what problems you solve best, AI will be too. This is about clarity, positioning, and knowing your customer deeply, so much more than just prompts or keywords.
Key takeaways:
AI references websites more than any other source when forming brand opinions
Vague positioning forces AI to piece together your value from scattered signals
Result: AI creates its own version of who you serve which may not match your intent
SEO tricks won’t cut it. Say clearly what you do and who you help.
Be explicit about your ideal fit instead of expecting AI to figure it out
Curious how your brand shows up to AI?
Take this quick 30-second quiz: Can AI Understand Your Website?
It scores how clearly your website communicates to AI and gives you practical tips to improve.
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 13-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 Happens When AI Evaluates Your Competitors
For example, I asked Google to profile project management platforms for a mid-sized company. Within seconds, Google’s AI-powered search results delivered a detailed analysis: which platform was “best for” specific scenarios, pros and cons for each, and clear recommendations with reasoning.
The AI didn’t just find these companies. It judged them. See Perplexity and Google’s AI Overviews responses below.
• Asana – best for growing teams needing automation
• Trello – simplest for visual planners
• Monday – powerful for custom workflows, but complex
It was exactly the kind of guidance buyers want: clear use cases, honest trade-offs, and specific recommendations. But it had to piece this together from scattered information across websites, reviews, and comparisons.
Most companies never explicitly said “we’re ideal for X situation” or “competitor Y is better for Z use case.” The AI made those calls anyway, using whatever crumbs it could find.
When AI Gets It Wrong, You Still Pay the Price
AI forms impressions based on the signals it sees. If those signals are inconsistent or unclear, it will fill in the blanks. That’s not a malfunction. It’s how these systems work. They pattern-match and summarize. But when the patterns are vague or conflicting, AI produces flawed narratives. It might categorize your brand incorrectly, recommend you for the wrong use case, or overlook you entirely. Buyers won’t know it was an AI error. They’ll just assume your brand isn’t for them.
If you’re curious how to guide those signals and increase your odds of being cited directly, I wrote a deeper piece on how to make your brand sourced and a top result in AI search. It walks through how to identify buyer questions, track what AI says, and tune your content accordingly. Read it here.
Here’s why simply chasing citations backfires.
What Most Teams are Missing
A recent Semrush study found that AI systems reference websites more than any other source when forming brand opinions. But most companies still approach this backward.
We’ve been focused on getting AI to find our content. The real challenge is helping it understand and accurately represent our value.
We got away with vague positioning because humans could fill in the blanks.
“Industry-leading solution.” “Best-in-class features.” “Perfect for teams of any size.”
Humans can interpret those claims. They know when “scalable” means 25 users vs. 2,500. AI doesn’t. So it either makes wrong assumptions — or plays it safe with vague, generic recommendations.
Why This Matters More Than You Think
AI isn’t just finding information. It’s interpreting and compiling it. It’s turning scattered signals into structured buying guidance.
In the project management example, AI created decision frameworks that most of those companies didn’t offer themselves.
And the buyers coming from those frameworks are more ready to act. A SEMrush study found that AI search visitors convert at 4.4x the rate of traditional organic traffic. Why?
They’ve already compared options
They’ve learned your value
They arrive with real intent
That makes clarity even more critical. If you’re not clearly positioned, AI won’t know when to recommend you and high-intent buyers won’t know why to choose you.
That also means it’s getting harder to stand out with surface-level content. In Beyond AI-Generated Content, I share how to rise above the noise by telling stories AI can’t replicate and creating content that buyers (and AI) actually remember. Skim it here.
This creates a fundamental problem: if you don’t clearly communicate your ideal customer profile and use cases, AI will invent its own version.
And it won’t invent that version in a vacuum. It will pull from whatever signals it can find such as customer reviews, community posts, influencer roundups, and outdated buyer guides. If you’re vague, those voices will fill in the gaps for you. And their version of your story might not match your intent.
Your website is the one place you control. You can’t dictate what people say in forums or reviews, but you can shape the narrative on your own site.
The sharpest teams know this and they’ve stopped trying to be “best for everyone.” Instead, they’re clear about who they serve best and even point customers to a competitor that might be a better fit. That’s truly being helpful.
Five Changes That Help AI Understand You
Here are five areas where companies can stop making AI guess and start being direct:
1. Say Who You’re Not For
Be bold enough to draw the line. Instead of trying to appeal to everyone, make it clear who you serve best and who you don’t. AI picks up on patterns. If your case studies all feature 250+ employee companies, but your homepage says “great for small teams,” that’s a mismatch. AI will flag it. So will buyers.
The fastest way to build trust is to help people self-select out.
2. Describe the Outcome, Not the Feature
Buyers don’t care that your product is “AI-powered.” They care that it helps them do something specific like predict customer churn or personalize pricing in real time.
Instead of “AI-powered analytics provides better insights,” try: “Need to predict customer behavior with 90% accuracy? Use our Predictive AI module.”
The more clearly you describe the job your product helps someone do, the more accurately AI can match you to the buyer’s intent.
3. Organize by Buyer Goals, Not Product Tiers
Most websites are structured around how you think about your product. AI and buyers don’t care about your internal categories. They care about achieving a specific outcome.
Instead of “Products > Premium > For Experts,” try: “What are you trying to do? → Analyze Data → In Real Time → Live Dashboard.”
This kind of goal-based structure helps both AI and humans navigate directly from intent to solution — without needing a map.
4. Be Honest About Where You Win (and Don’t)
Buyers don’t just want to know who you serve. They want to know when your product is the right tool for the job.
Say: “Best for mid-sized teams with flexible workflows. Not ideal for large enterprises requiring strict compliance.”
This kind of clarity helps AI route the right buyers your way and helps humans trust you faster. You’re not trying to win every deal. You’re trying to win the right ones.
5. Use Structured Content, Not Just Storytelling
Narrative copy is great for humans but AI needs structure to understand and cite you accurately.
Use tables, FAQs, labeled specifications, comparison grids, and feature lists. These formats make it easy for AI to extract meaning and build summaries.
Bonus: humans love them too. Especially when they’re scanning for answers.
The Business Case for Transparency
This approach might challenge old-school marketing instincts, but it aligns with sound business fundamentals: not all customers are created equal.
Customers you can’t serve well drain resources, churn faster, and rarely become advocates.
In a world shifting toward sustained profitability, your goal isn’t more leads, it’s better-fit ones. The ones you can serve exceptionally well. The ones who stay longer, buy more, and refer others.
Transparency helps AI recommend you to those right-fit prospects and steer others toward better alternatives. You win the customers you can delight. Your competitors win the ones they serve best. Everyone benefits.
What This Looks Like in Practice
This shift is already playing out on forward-thinking websites.
Andy Crestodina, Co-Founder and CMO of Orbit Media Studios, sees it first-hand.
“There is a true story in the life of your visitor. This is the reason they are on your page. The better you know that reason and provide the answers their looking for, the more likely you are to answer their questions and earn their trust.
Train AI on your audience and ask it for a gap analysis. Then fill those gaps and win the lead.”
This alignment matters just as much inside the org as it does on your website.
Megan Cabrera, VP of Marketing Operations at Sophos who is leading and driving human-AI org transformation, puts it this way:
“The same challenge we face inside — teaching AI to make smart decisions — applies externally too. When AI research tools evaluate us, they need the same kind of structure and clarity we give our internal models.
If we don’t provide it, they’ll guess. And those guesses influence what buyers see.”
Your Next Steps
Start by seeing your brand the way AI does.
Prompt to try: “I’m looking for [your category] solutions for [your target market]. Please profile the top competitors and give me recommendations with pros, cons, and best-fit scenarios.”
Then assess the results:
How does AI describe your value?
Which scenarios does it say you’re best for?
When does it recommend a competitor?
Now audit what AI is learning from.
Pick one piece of content your team uses often in sales or marketing.
Ask: “If an AI had to recommend us based on this, would it have enough clarity to get it right?”
If not, fix it. Make the connections obvious. Don’t make AI or buyers figure it out.
None of this works without clarity. If you don’t understand your customer or your value, you can’t guide AI or anyone else. The teams that get this right are clear on who they serve, what they solve, and why it matters. Their content works because their strategy is solid.
A confused buyer buys nothing.
And in today’s crowded markets, confusion is everywhere. When buyers feel overwhelmed, they don’t turn to you. They turn to community threads, peer reviews, buyer guides, and increasingly, AI to make sense of the madness. That’s why clarity is a competitive advantage.
The good news is that you don’t need to win the click to win the mind. If your site is clear, consistent, and grounded in truth, AI will carry your message forward in search results, summaries, and beyond. Your website becomes your most powerful amplifier, not just for buyers, but for the AI that increasingly guides them.
You can’t control the algorithms. But you can control the signals you send. So be the clearest signal in the noise.
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.