Visibility Is Just the Floor: Here’s What Actually Builds Trust in AI Search

In this week’s episode of Voices of Search, we spoke with Liza Adams, AI advisor and go-to-market strategist at Growth Path Partners. Liza spent decades as a senior marketing executive at companies including Juniper Networks, Pure Storage, SmartSheet, and WorldCom, and her last corporate role was CMO. She now helps marketing and go-to-market teams navigate AI transformation, not from a tools-first perspective but from a people-first one.

Her framing is refreshingly grounded. AI isn’t her passion—elevating the strategic value of marketing is. AI just happens to be the current amplifier. That lens shapes everything she shared in this conversation about how brands should think about trust, buyer behavior, and what it actually takes to be recommended (not just visible) in an AI-driven search environment.

Key Takeaways From This Episode:

• Showing up in AI search is the floor, not the goal. Being visible matters, but being believable, positively positioned, and recommended for the right customers is what drives real business impact.
• AI amplifies what already exists. If the sentiment around your brand is wrong, AI will amplify the wrong signal. If it’s right, AI will amplify that too.
• Gated content has a hidden cost in AI search. If your best thinking is behind a paywall, AI can’t see it, and someone else who gives that information away freely will capture the citations instead.
• The AI response is becoming a reality. Users won’t verify citations any more than they read Google’s second page. What AI says about your brand is what people will believe.
• Organizational silos are an AI visibility problem. When marketing, sales, and CS say different things, AI picks up inconsistent patterns, and inconsistency becomes noise, not signal.
• People-first, AI-forward is the leadership stance that matters. Upskilling and reskilling teams is not optional if you want sustainable transformation rather than short-term efficiency gains.

Start With the Customer, Not the Algorithm

Liza’s opening argument sets the tone for everything that follows: the reason most AI strategies fail isn’t technical. It’s because teams start with AI instead of starting with the customer.

“If we start with AI, then it feels like AI for the sake of AI,” she said. “But when we start with customers and how their buying behaviors and buyer journeys are changing, and we deeply understand what’s happening to them, then we can better figure out how we can use AI to better serve them.”

The buying journey has fundamentally shifted. AI search doesn’t look at a single source. It looks everywhere. Customer reviews, social channels, publications, analyst reports, and even Glassdoor. What it’s looking for is patterns. When a consistent pattern emerges across multiple sources, that becomes a signal. 

When signals are inconsistent or contradictory, they become noise. The brands that win in AI search aren’t necessarily the ones with the best on-page SEO. They’re the ones whose message is consistent, credible, and widely corroborated.

The Three Layers of AI Visibility

Liza’s framework for how brands should think about AI visibility goes well beyond simply showing up. She breaks it into three distinct levels, each building on the last:

• Visibility: Are you being cited at all? This is the baseline. Showing up in AI responses is necessary but not sufficient on its own.
• Sentiment: When you show up, is it positive? Is AI describing your brand in the way you want to be described? A brand can appear frequently and still be damaged by how it’s being characterized.
• Recommendation: Are you being recommended for the right customers and the right problems? Liza pushed back on the instinct to just want more recommendations regardless of fit. “What if we’re recommended for the wrong customer that we can’t serve really well, and ultimately they’re dissatisfied and they churn and then they say bad things about us online? Now AI sees all those bad things, and we have a very different problem.”

The implication is that AI amplifies whatever is there, good or bad. Getting the right customers through AI-driven recommendations is more valuable than getting more customers through misaligned ones.

The AI Response Is Becoming Reality

One of Liza’s sharpest observations is worth sitting with: the AI response is becoming the de facto truth, regardless of whether it’s accurate.

Users don’t verify citations. “How many times have we ever gone to the second page of Google search results? Never. Now, how many times do you think the user is going to go to those 39 different sources and check AI’s work? Never. Even worse.”

The practical implication for brands is significant. Errors, outdated positioning, or mischaracterizations that exist in the sources AI pulls from will be presented as truth, and most users will accept them as such. Fixing what AI says about you isn’t just a visibility exercise. It’s a brand integrity exercise. And it requires:

• Ensuring your website addresses the problems your customers are searching for, not just the features you offer
• Auditing whether your content uses the language your customers use, not the language your internal teams use
• Identifying whether valuable content is sitting behind paywalls that AI can’t access
• Monitoring AI responses consistently, since the same prompt won’t always produce the same answer

The Hidden Cost of Gated Content

The gated content conversation was one of the more practically urgent moments in our discussion. The conventional wisdom in B2B marketing has been to gate high-value content to capture lead data—but Liza maintains that this calculus has changed.

“If you’ve got awesome content behind a gate or a paywall, AI is not going to see that,” she said. “Somebody else who’s giving data and information for free might dominate the citations as a result.”

That doesn’t mean gated content is dead. Highly personalized content for specific accounts, or analyst reports with proprietary research, still warrant gates. But the default assumption that gating drives more qualified leads needs to be weighed against the cost of being invisible to the AI systems that are increasingly shaping buyer decisions before any human interaction takes place.

Liza’s alternative is what she calls a “race to generosity,” a phrase she credits to content strategist Andy Crestodina. The brands that give away their best thinking openly, help buyers through their journey without immediately asking for something in return, and show up consistently in the places where buyers are already having conversations are the ones that build the trust AI will amplify.

Where to Actually Show Up

On the question of which channels matter most in an AI-influenced world, Liza pointed to two categories that are growing in strategic importance:

• Human communities: Slack groups, CMO forums, industry communities. These are spaces where authentic peer conversations happen and where word-of-mouth recommendations carry real weight. “If somebody says, ‘I’m looking at these three platforms,’ people listen. That automatically becomes a short list.” AI also pulls from these communities, making organic participation more valuable than ever.
• Events: Whether online or in-person, events create the kind of authentic human conversation that can’t be easily manufactured. “We’re getting tired of the constant AI, AI. But when we can actually hear from human beings and their experiences, those rise.”

The common thread is trust built through genuine helpfulness rather than lead capture mechanics.

Silos Are an AI Visibility Problem

One of the less-discussed angles in the conversation was Liza’s argument that organizational silos don’t just hurt customer experience. They actively damage AI visibility.

When marketing, sales, and customer success are all saying slightly different things, AI picks up inconsistent patterns. “We can’t be saying one thing, and everybody else is saying another. Because ultimately, what AI does is look for patterns. If we’re saying we’re the best in the world at customer service and everybody else is saying it’s crap, we’re an outlier. We’re noise.”

The solution isn’t a new messaging document. It’s organizational alignment around customer-centric metrics that replace the siloed KPIs each function currently optimizes for independently. Liza sees AI as the force that will eventually compel this convergence. “Marketing says something different than sales, which says something different than CS. Customers don’t care about our silos. They want to experience one company.”

People First, AI Second

The conversation ended where it arguably should have started: with the people question. Liza’s stance on AI-driven workforce reduction is direct.

Making existing work faster is the floor, not the ceiling. “If we actually think about AI way beyond that, we’re using AI to improve the quality of the work and then ultimately using AI to reimagine the work. Meaning we are now doing things that weren’t possible before, and it grows the business.”

The distinction matters because automation replaces roles while reimagination creates them. “When we simply train AI to do our existing work, we automate the human out. If we reimagine what’s possible, we innovate, and then we grow the business.”

Her advice to enterprise leaders for the next 12 months was precise: give your teams the gift of upskilling and reskilling. Not just for the company’s benefit, but for the individual. “Upskilling and reskilling aren’t just something we do for our companies. It is something we do for our teams and for the individual, allowing them to thrive and better compete in the era of AI.”

That is, ultimately, what a people-first AI strategy actually looks like in practice.

Voices of Search is a daily SEO and content marketing podcast hosted by Jordan Keone and Tyson Stockton. The show delivers actionable strategies and data-driven insights to help marketers navigate the ever-evolving world of search engine optimization and content marketing. New episodes air weekly, covering everything from technical SEO to AI discovery, featuring industry leaders and practitioners sharing real-world frameworks and proven tactics.

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