How AI search has reshaped the consumer journey
Half of consumers are already using AI-powered search and by 2028, it could influence up to $750bn in US spending.
This is the key finding from McKinsey’s latest research on AI search, which underlines how quickly AI has reshaped how consumers discover, evaluate and buy from brands.
The report outlines the need for brands, marketers and publishers to take the time to understand this new consumer discovery process, as traffic from traditional search could fall by 20-30% in the next few years.
AI search in the spotlight
McKinsey’s survey found 50% of consumers now intentionally use AI-powered search tools to guide purchase decisions.
Notably, this behaviour spans across all generations, including baby boomers.
AI summaries in Google have accelerated this behaviour, with around half of all Google searches today surfacing an AI overview. The report predicts this will surpass 75% by 2028.
Many consumers are using AI throughout the purchasing journey, with 73% using it to learn about a category, 53% using it for planning a trip or special occasions, 61% using it to compare products, 60% using it for understanding technical specifications, 57% for personalised recommendations, and 60% for summarising reviews of products.
McKinsey describes this evolution in how consumers search for products as a “tectonic shift.”
Consumers are no longer clicking through multiple sites, brand pages and online forums during the purchasing journey, but instead will search through a single AI interface.
The consequences for brands
The report warns that unprepared brands risk losing visibility and relevance as consumers bypass traditional search results.
AI-powered platforms are more involved during the early research and consideration stages, according to the research. This means clicks that do reach traditional websites will likely come from consumers further down the funnel.
This means traditional metrics, such as impressions, visits, and keywords, will carry the same weight in discoverability.
From SEO to GEO
These changes mean that Search Engine Optimisation (SEO) comes further down the priority line, with Gen AI Engine Optimisation (GEO) taking top spot.
McKinsey notes that 44% of AI-powered search users now say it’s their primary and preferred source of insights, overtaking traditional search (31%), retailer websites (9%) and review sites (6%).
However, only 16% of brands currently track how their content performs in AI-powered search results.
This is because generative AI draws on a broader range of sources, whereas Google’s algorithm relies on familiarity and personalisation.
In AI search, a brand’s own site typically accounts for 5-10% of the sources referenced in the answer.
For instance, the report found that the sources Google AI used for answers on consumer packaged goods drew 50% of their information from affiliate blogs and websites.
But for e-commerce, less than 5% came from this, but 80% came from brand and retailer websites.
These shifts make it harder for brands to predict where and how they’ll appear in AI-powered results, underlining the need for a broader content strategy.
The future of branding: Influence LLMs to protect your share of market
An even start line
Notably, the report highlights how traditional brand equity won’t necessarily promise AI relevance.
McKinsey’s report showcases how even some of the top brands across different sectors from hotels to electronics, weren’t featured in AI-generated answers, highlighting how some brands may have a lower share on AI-powered search vs expected market share and performance on traditional search.
Brands can no longer rely on domain authority alone; they must ensure the information ecosystem around their products, whether through affiliate reviews or websites, is accurate, up-to-date, and compelling.
How to get ahead
McKinsey recommends focusing on the following four steps in navigating the AI revolution:
Diagnose GEO performance: The report encourages brands to undertake diagnostics on where they appear across major AI search engines, how sentiment trends and which sources influence the large language models (LLMs) the most.
Broaden content investments: Due to AI-powered search being built on a wide array of content, from owned media to communities. The report highlights the importance of identifying authority gaps and addressing them.
Optimise for LLMs: Information needs to be clear, structured and precise, to appeal to LLMs, which seek credibility. This needs to be consistent across owned and third-party content.
Make GEO core to the strategy: AI-powered search needs to be a strategic priority. Teams across marketing, SEO, content and customer experience need to intersect, and KPI’s should be defined with AI platforms in mind.