News + Thought
ChatGPT, Claude or Gemini: Which is best to get your business discovered?
Whenever I’ve been speaking to clients recently, I’ve been noticing a distinct shift in the types of questions they’re asking us about their discovery strategy.
That is to say, it’s now being expanded from more than simply organic search, to now include SEO for LLMs as well. The question is no longer “how well do I rank on search engines?”, but “am I being included in the answers on AI platforms?”.
It’s a very valid one. Large language models are rapidly becoming the new interface for discovery, and for brands, this represents the emergence of an entirely new demand capture channel - one that is quickly approaching the strategic importance search engines held in the early 2000s.
But this shift goes further than a change in interface. I talk more about this in detail on an upcoming podcast series Skywire have made on the topic (stay tuned!), but the crux of the matter is that platforms like ChatGPT, Gemini and Claude are not simply helping users find information.
They are interpreting it, filtering it, and increasingly deciding what gets recommended.
In other words, discovery is moving from search engines to decision engines. This has significant implications for how brands are found, evaluated and ultimately chosen. Unlike traditional search, where users scan a page of results and make their own judgement, AI platforms deliver a single, synthesised answer.
It’s easy to see why the average internet user likes this as a model - they get a strong recommendation, backed up by justification, without the burden of decision fatigue, instantly. Sometimes that answer goes beyond a recommendation, and actually becomes a direct suggestion of what to do next. As a result, visibility is no longer just about ranking highly - it is about being included in, and ideally shaping, the answer itself.
However, not all AI platforms are evolving in the same way. Each is developing its own approach to monetisation, brand visibility and user trust, creating a fragmented landscape that brands must now navigate. So, I thought it might be helpful if I shared some insights from my chats with Skywire’s clients to help you figure out which platform might be the most helpful out of the “big three” - ChatGPT, Claude, and Gemini.
Getting discovered on ChatGPT
ChatGPT is currently the most commercially progressive of the three. With over 800 million weekly users, it has moved first in testing advertising within its platform, signalling a clear intent to become a new kind of media channel.
Ads are being introduced in a controlled format - appearing separately from responses as sponsored placements - while OpenAI maintains that they do not influence the underlying answers. This positions ChatGPT as the closest equivalent to a traditional advertising ecosystem, but within a conversational environment.
Gemini + Search Discovery
Gemini, by contrast, reflects Google’s more cautious and strategic approach. Rather than introducing ads directly into the chatbot experience, Google is focusing on integrating AI into its core search product through AI Overviews and AI Mode.
It doesn’t take a rocket scientist to see why Google adopts this approach, of course. Their conservative take on integrating AI with search is necessary in order for Google to be able to evolve its existing advertising model rather than disrupt it.
While there are currently no ads within the Gemini app itself, industry speculation suggests this may change over time, and I wouldn’t be surprised to see it by the end of the year.
That being said, for now, Google’s priority is clear: protect and extend its dominance in search by embedding AI into it, rather than treating it as a separate entity.
The third way: Understanding discovery on Claude
Claude represents a third, distinctly different philosophy. Anthropic has publicly rejected advertising within the conversational experience, with leadership stating that conversations are not an appropriate place for ads.
While this may hold in the short term, it is widely expected that monetisation will emerge through alternative routes. These are likely to include integrations, APIs and structured data partnerships, where external organisations provide trusted datasets that the model can reference directly in its responses.
In this model, visibility is not bought through ads or earned through rankings, but achieved through inclusion in the underlying data ecosystem.
Taken together, these approaches point to three emerging models for AI-driven discovery: advertising-led, search-led and integration-led.
For brands, this means there is no single strategy that will guarantee visibility across all platforms. Instead, success will depend on understanding how each ecosystem operates and aligning accordingly.
This is where the concept of “SEO for LLMs” begins to take shape. Traditional SEO has focused on keywords, backlinks and rankings. In an AI-driven environment, those factors do still matter, but they are no longer sufficient.
What matters increasingly is whether a brand is understood, trusted and consistently represented across the sources that AI models draw upon.
This includes having clear and structured information about products and services, maintaining a strong presence across authoritative platforms, and ensuring that brand messaging is consistent and unambiguous. It may also involve participating in data partnerships or providing structured datasets that can be directly consumed by AI systems.
In effect, you could frame this as “brands must move from optimising for search engines to optimising for interpretation”.
Again, I am slightly pre-empting an upcoming podcast release on a session I held with my two colleagues Simon and Gareth here (stay tuned for more on this), but ultimately, we are not moving towards a single, unified AI platform. We are moving towards a landscape of distinct discovery ecosystems, each with its own rules, incentives and mechanisms for visibility.
Those that can navigate that transition early on will be the ones that are best placed to capture demand in the next generation of digital discovery.
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