AI Overviews. ChatGPT. Google AI Mode. Perplexity. Claude. Over the past two to three years, these names have changed how people think about optimising brands for organic search. Search behaviour and SEO have always evolved, but in recent months we have reached the edge of a seismic shift in how we optimise and measure success through the organic search channel.
There has been plenty of discussion about what this means for marketing teams and their SEO strategies moving forward. While many of the proven foundations still hold firm, optimising for AI search is, in many ways, a brave new world.
Beyond tactics and strategies, brands need to consider how to adapt their tech stacks to measure and report effectively in this new field. Are we on the verge of traditional SEO reporting becoming obsolete? How should brands invest in tools that support AI search? Let’s explore.
Why AI search is different and what this means for brand tech stacks
We have moved far beyond measuring the traditional ten blue links. Top rankings on Google are still important, but LLMs and AI search platforms have reshaped the landscape entirely.
Alongside traditional search rankings, which many third-party tools now struggle to report accurately due to Google no longer supporting the “results per page” parameter, we now have brand mentions and citations in LLM-generated answers. Keywords are becoming long, complex, and personalised prompts. Brands need to research and track these effectively to ensure visibility and citations across relevant answers.
Brands also need a clear, high-level view of their visibility across prompts and prompt categories compared to competitors. Sentiment and reputation tracking are becoming crucial, especially since many LLM prompts are informational or recommendation-based. Ensuring that your brand is presented positively in such answers and having accurate reporting around this is now essential.
These shifts in search behaviour require thoughtful investment in the right tech stack to futureproof your SEO and stay ahead in AI search.
What questions should brands ask potential AI search tool suppliers?
Like any investment in third-party tech, you need strong acceptance criteria. This is even more important now, since the SEO industry is still in the early stages of understanding what “good” looks like for AI search optimisation and measurement. There is also widespread information overload. Everything is moving at high speed, from LLM development to new tooling solutions, and it can be overwhelming.
The truth is that no one has all the answers yet. But there are key questions brands should ask when assessing AI search tooling suppliers and their long-term value.
Consider asking:
- Does the tool provide strong coverage across multiple LLMs and regions?
- Can I measure visibility against competitors and see where my brand is missing from prompts in which competitors are cited?
- Does the tool offer in-depth prompt research and tracking of my brand’s visibility across those prompts?
- Does it provide brand sentiment analysis?
- Does it offer feedback on how to optimise content for LLM performance?
Should I choose an all-in-one platform or a best-of-breed approach?
Given today’s landscape, finding a single perfect supplier may not be feasible. A best-of-breed approach may be the most practical option, depending on your budget.
There are several emerging AI search specialist tools leading the way, including Profound, Peec, Waikay and AirOps. If you want a clean, AI-first solution for visibility, prompt discovery, tracking and content optimisation, these platforms can be a strong fit.
However, many of these tools struggle with economy of scale. For enterprise brands with thousands of URLs across many regions, replicating large-scale tracking of prompts can become extremely expensive.
If your goal is to gain a general overview of brand performance across curated prompts and high-level visibility gaps, these tools can be valuable. But you will still need your traditional SEO platforms, since core functions such as technical SEO and link building remain important and are not typically covered by AI search tools.
You should also keep an eye on established SEO platforms like Semrush and Ahrefs. Their technical SEO, keyword research, reporting and backlink analysis features remain essential, and both platforms are building their own AI search capabilities. These are still in early stages, and at this point the newer specialist tools generally have more mature AI search features.
Analytics platforms such as Google Analytics and Adobe Analytics will also continue to play a major role, especially since traffic reporting from LLMs will become increasingly important.
Your choice will depend on your business size and goals, but for now a hybrid approach that combines existing SEO tools with AI-focused solutions is likely the strongest path.
Looking ahead
Although the industry is still early in understanding AI search and the pace of development is rapid, it is crucial to assess how your brand is currently represented across LLMs. While Google search remains dominant, the rise of LLMs as the primary user search tool is undeniable. Some studies predict that LLMs will account for the majority of traffic revenue within a few years.
Brands across marketing channels are already adapting strategies to improve visibility on these platforms. Taking action now from an organic search standpoint will position you strongly for the future. Alongside your existing SEO efforts, investing in the right supplier to support AI search measurement and optimisation should be high on your priority list for 2026.
