AI Answer Engines Are the New Front Door – and Marketing Leaders Need a Visibility Plan

For more than a decade, marketing leaders have treated search as the predictable gateway to demand: rank well, earn the click, convert the visitor. That model is being rewritten in real time. AI answer engines and AI-powered search experiences are increasingly the place where buyers do their research, form preferences, and build shortlists. In many cases, they never visit a website until they are deep into evaluation.

This isn’t a future trend. It’s a channel shift already influencing revenue, especially in software and B2B services where “which platform should we buy?” is a natural prompt for tools like ChatGPT, Gemini, Copilot, Perplexity and Claude.

AI answer engines are becoming the default research layer

McKinsey describes AI-powered search as the “new front door to the internet”, noting that consumer discovery behaviours have already moved materially towards AI tools and AI summaries inside search results. In their research, half of consumers intentionally seek out AI-powered search engines, and 44% say it is their primary and preferred source of insight, ahead of traditional search at 31% (McKinsey, “Winning in the age of AI search”).

That “preferred source” framing matters. It signals that AI is not just another interface. It’s becoming the decision layer buyers trust to summarise trade-offs, recommend options, and explain the “why”.

In practical terms, AI answers compress what used to be multiple steps: Googling, reading review sites, scanning forums, comparing feature pages, then digesting the information. This process now happens instantly, inside the answer.

In software buying, AI is already shaping the shortlist

Software discovery is particularly susceptible to this shift because it is research-heavy and comparison-led. G2 goes further, stating that “AI has overtaken search” and is now the #1 source for software shortlists (G2, “AI has overtaken search”). Their research of 1,000+ B2B buyers claims:

• 1 in 2 buyers now start with ChatGPT or similar tools (a 71% jump in four months).
• 55% of enterprise buyers rely on AI search more than Google.
• Sales conversions from ChatGPT recommendations are reportedly up 436%.

Even if you treat these figures as directional, the implication is clear: the earliest and most influential stage of the buying journey is moving “AI-first”. If your brand is absent, misrepresented, or simply not recommended, you may never make the shortlist.

Why this changes the economics of visibility

For the past two decades - give or take - marketing has been optimised around the click. AI answer engines break that logic in two ways:

• They answer without sending traffic. Many users get what they need without leaving the interface.
• They reshape what a “good” outcome looks like. A brand mention or citation inside an AI answer can be as influential as a top ranking, but it may not drive an immediate session you can measure.

Semrush’s 2026 AI SEO statistics roundup highlights the scale of this “zero-click” reality: roughly 60% of searches now yield no clicks, and when an AI summary appears, only 8% of users click a traditional link (Semrush, “26 AI SEO Statistics for 2026 + Insights They Reveal”).

This is a direct challenge to performance measurement. A buyer can be influenced by your positioning in AI answers repeatedly, then later visit your site via direct traffic, branded search, a sales referral, or a private link in Slack. The causal chain is real, but the attribution trail is weak.

GEO: from ranking pages to earning recommendations

McKinsey argues that as SEO has been central to digital strategy, GEO (generative engine optimisation) now needs to be a core capability: optimising not only your own pages, but also the broader ecosystem of sources AI systems draw from (McKinsey).

One of the most important points in McKinsey’s analysis is that a brand’s own sites may represent only 5–10% of the sources referenced in AI-search results. The rest can include publishers, affiliates, communities, and user-generated content. In other words: your “AI presence” is partially owned, largely earned, and constantly shifting.

What marketing leaders should do differently

GEO is not simply “write content that AI likes”. It is a multi-channel visibility discipline. Practically, that means:

• Build authority beyond your website. AI engines frequently rely on third-party sources: credible media coverage, analyst perspectives, review platforms, community discussions, and comparative guides.
• Make your positioning easy to quote. Clear language, consistent product naming, and unambiguous claims reduce the risk of AI paraphrasing you inaccurately.
• Invest in content that answers shortlist questions. Comparison pages, “best for” use cases, implementation guidance, pricing explanations, and security/compliance details map directly to the prompts buyers use.
• Strengthen trust signals. Mentions in news articles, feature stories, as well as community and review site mentions all help determine which brands get recommended in AI-led research.

The measurement problem: AI visibility is still opaque

Here’s the uncomfortable truth: for most organisations, AI answer engines are already influencing pipeline, but the visibility data is patchy.

McKinsey notes that just 16% of brands systematically track AI search performance (McKinsey). That gap exists because AI discovery does not behave like traditional web analytics:

• Prompts are private and varied. You can’t rely on a stable set of keywords. Buyers ask nuanced questions, and they iterate.
• Citations are inconsistent. Some engines cite sources, some cite sparingly, and summary formats change frequently.
• Influence happens pre-click. The user can become convinced (or unconvinced) before they ever reach your site.
• Attribution is diluted. Even when AI does drive a visit, it may appear as “referral” from a tool, or be lost in direct traffic if the journey spans devices and channels.

This creates a directional challenge. If visibility is opaque, it’s tempting to ignore the channel. But ignoring it doesn’t reduce its impact on sales. It simply leaves you blind to how your brand is being represented at the most influential moment: shortlist formation.

What to track when clicks are no longer the main signal

If you’re trying to govern AI as a channel, you need a measurement approach that combines quantitative tracking with qualitative inspection. A practical starting set of questions:

• Presence: Do we appear in AI answers for our category’s high-intent prompts (for example, “best [category] software for [industry]”)?
• Positioning: When we appear, are we described accurately and consistently with our go-to-market messaging?
• Sentiment: Are we recommended confidently, neutrally, or with caveats?
• Source mix: Which third-party sources are being used to form those recommendations?
• Competitor comparison: Who is being recommended instead of us, and what “proof” is the model using?

This is where AI-powered PR analytics and visibility tooling becomes strategically important. Marketing and comms teams need a way to monitor brand mentions, citations, and narrative accuracy across models and answer formats, not just search rankings. The goal is not to “game” the system. It is to ensure your best, most trustworthy information is what the system learns from and repeats.

The takeaway for CMOs and communications leaders

AI answer engines have become a new channel, with real influence over buying decisions and shortlists. McKinsey’s data suggests AI-powered search is already a primary source of insight for many consumers, while G2’s research indicates the shift is especially pronounced in B2B software discovery. Semrush highlights the operational reality behind this change: fewer clicks, more on-SERP and in-answer consumption, and a growing need to redefine what success looks like.

The hardest part is that AI visibility is still relatively opaque. AI-led research doesn’t always produce a trackable link, and influence often happens before analytics can detect it. That is precisely why leaders need a deliberate visibility plan: understand where you show up, how you are described, and whether your earned presence is strong enough to carry trust in a world where the “front door” is an answer, not a search results page.

In the new discovery landscape, awareness isn’t optional. Performance monitoring is the only way to make AI visibility manageable, measurable, and ultimately improvable.