Marketers Express Skepticism Over Costly GEO and AI Visibility Platforms

I’ve been watching the rise of GEO and AI visibility platforms with a mix of interest and caution. On paper, they promise exactly what modern marketers want: a way to see how brands appear inside ChatGPT, Gemini, Perplexity, Claude, and Google’s AI-powered search experiences. In practice, though, more marketers are starting to ask whether these expensive tools actually deliver insights that justify the cost.

The skepticism is growing for a straightforward reason: the need is real, but the measurement is still messy.

Why marketers are paying attention

The pressure on brands to understand AI discoverability is very real. As AI summaries and answer engines become a bigger part of the search journey, traditional website traffic is getting squeezed. One of the clearest signs came from Pew Research Center data cited in industry coverage: when users see an AI summary in Google, they click traditional search results only 8% of the time, compared with 16% when no AI summary appears. That’s a significant shift.

For marketers, this creates a new challenge. It’s no longer enough to rank on page one. Now the question is whether your brand is cited, mentioned, accurately summarized, or recommended by an AI system before a user ever reaches your site.

That shift has triggered a wave of GEO and AI visibility platforms. Tools like Profound, Ahrefs Brand Radar, Peec AI, Adobe LLM Optimizer, and others now offer dashboards, prompt tracking, citation monitoring, and competitive analysis. Agencies and in-house teams are testing them because they don’t want to fall behind. But the early excitement is running into a familiar problem: inconsistent outputs and unclear ROI.

The core complaint: high cost, limited certainty

The clearest message in recent reporting is that marketers aren’t skeptical because AI visibility doesn’t matter. They’re skeptical because many of these tools still feel early, expensive, and incomplete.

Plenty of platforms cost hundreds of dollars a month, with enterprise pricing reaching much higher. That would be easier to justify if the outputs were stable, actionable, and clearly tied to performance. That’s where confidence starts to slip.

As /prompt CEO Paul Dyer put it, “If you use three different tools and give them the same prompts, you get three different answers.” That gets to the heart of the issue. If the measurement tools can’t agree with each other, marketers are right to ask what exactly they’re paying for.

Ryan Mason of Markacy was even more direct, saying, “There’s really not much an AI tool can do or tell you to do. It’s just a benchmarker in my mind.” That feels like a fair assessment of where the category stands today. Many of these platforms are useful for snapshots, directional signals, and ongoing monitoring. Far fewer can offer reliable optimization guidance.

A category still in its infancy

Part of the problem is that the AI platforms themselves are unpredictable. Different large language models rely on different data sources, retrieval methods, ranking logic, and confidence signals. Even the vendors building GEO tools are reportedly still trying to figure out why one engine favors certain sources while another does not.

That leaves marketers trying to optimize for a system that keeps changing underneath them. It’s a moving target.

Heather Physioc of VML pointed to another major weakness: many tools provide only “point in time” visibility. That’s helpful to a point, but marketers need trendlines, consistency, and context over time. A one-off result showing whether a brand appeared in a generated answer doesn’t give a team much to build strategy around.

Joseph Levi of Noise Media Group summed up the pricing concern well: “We don’t know enough of these companies to be charging what they’re charging. But it’s extremely early days.” He also noted that one of the few consistently useful functions is simply seeing how often a brand appears across different types of prompts. That says a lot. Right now, the most practical value may not be optimization at all, but basic visibility tracking.

Why marketers are still testing anyway

Even with all the doubts, brands and agencies aren’t stepping away. They’re experimenting because they feel they have to.

That’s what makes the GEO market so interesting. It’s driven by both skepticism and urgency. Marketers don’t fully trust the tools, but they also know that ignoring AI-mediated discovery could be a mistake. If traffic is shifting away from classic blue links and toward AI-generated recommendations, brands need some way to track whether they’re present in those environments.

That’s why agencies like VML are reportedly testing multiple tools at once, while others are building internal systems instead. Noise Media Group’s Voodoo.ai is one example of a hybrid response to high vendor pricing and immature products. Rather than relying entirely on third-party platforms, some firms are creating their own monitoring layers and workflows.

The logic is clear. When a category feels overheated, smart marketers look for more control over both cost and methodology.

The real issue is not visibility — it’s proof

In my view, the biggest challenge for GEO tools isn’t whether they can collect data. It’s whether they can prove business value.

Tracking citations, mentions, sentiment, and share of voice inside AI systems is useful. But marketing teams still need to justify the spend. They have to connect that visibility to outcomes like brand lift, lead generation, consideration, or revenue. Right now, that connection is still weak.

Traditional SEO came with familiar benchmarks:

• Rankings
• Impressions
• Clicks
• Traffic
• Conversions

AI visibility introduces a new set of KPIs, but those metrics aren’t standardized yet. The industry is still debating what matters most, including:

• Citation frequency
• Placement in answer summaries
• Accuracy of brand descriptions
• Inclusion in high-intent prompts
• Trusted-source status

Until those questions are settled, many GEO tools will continue to feel more like experimental intelligence platforms than essential performance engines.

What the market is likely to reward

I don’t think this skepticism means the category disappears. More likely, it grows up.

The vendors that last will probably be the ones that move beyond flashy dashboards and into more practical territory:

• Better trend analysis
• Stronger cross-model consistency
• Clearer recommendations
• Tighter integration with SEO, content, and analytics stacks

Marketers don’t just want to know whether they appeared in an AI answer. They want to know why, how to improve, and whether any change made a real difference.

For now, the smartest approach is probably a balanced one. Brands should keep testing AI visibility tools, but with realistic expectations. These platforms are not magic systems. At this stage, they’re better used for monitoring and benchmarking than as all-in-one optimization solutions.

That also means the fundamentals still matter. Clear entity signals, strong content quality, structured data, trustworthy sources, and a consistent brand presence across the web remain critical. AI systems may change the interface, but they still depend on the quality and clarity of the information underneath.

FAQ

Why are marketers interested in GEO and AI visibility platforms?

Because AI summaries and answer engines are changing how users discover information. Brands now need to know whether they’re being cited, described accurately, or recommended before users ever click through to a website.

Why are marketers skeptical of these tools?

The main concerns are high pricing, inconsistent results across platforms, limited historical context, and weak proof that AI visibility metrics lead to business outcomes.

What do these tools do well right now?

Most are most useful for monitoring visibility, tracking citations, comparing brand presence across prompts, and spotting directional changes over time.

What is the biggest weakness in the current GEO tool market?

The biggest weakness is attribution. Marketers still struggle to connect AI visibility data to outcomes like traffic, leads, conversions, or revenue.

Should brands ignore these platforms for now?

No. The better approach is to test them carefully, treat them as early-stage monitoring tools, and avoid expecting mature optimization guidance or guaranteed ROI.

Conclusion

I see the current wave of GEO and AI visibility platforms as an important but unsettled market. The need for AI discoverability is real, especially as zero-click behavior rises and referral traffic gets harder to win. But marketers’ skepticism is justified. High prices, inconsistent outputs, and weak attribution make it hard to treat many of these tools as mature solutions. For teams trying to navigate that uncertainty while staying focused on practical visibility gains, AIuthority is worth considering as part of a more measured approach to AI-era brand discovery.