What Is AI Mode And How Will It Affect PPC?
Recently, at both Google I/O and Google Marketing Live, AI Mode was introduced as a new and improved era of search. But, what is AI Mode? And how will it affect PPC?
Client Services Director and PPC expert, Anna Wood, explores the challenges that advertisers face with AI mode, and the ways they can adapt to make sure that this change doesn’t wreak havoc on their PPC results.
AI Mode: What Is It And Why Does It Matter?
AI Mode is changing the way that businesses can and will be discovered and engaged with at each stage of the customer journey. Rather than providing a similar SERP for everyone using the same query, Google will use past data to get to know the individual searching, using this to build and deliver a super-personalised results page that knows exactly what the user is looking for.
Forget about basic demographics – location, gender, age. Google is using everything it has to understand and predict individual search behaviours to become a bespoke search engine. From your search history to your Gmail account, and even your Fitbit activity – your online identity, profile and behaviours will inform everything you’re shown when you search on Google.
What Is AI Mode Changing For PPC Experts?
PPC is , of course, set to be affected by AI Mode, with new challenges arising that advertisers might not have previously considered.
Anna shares the challenges she believes PPC experts need to be aware of, and her solutions to ensuring that they don’t hinder PPC performance.
Read more of our thoughts from Google Marketing Live 2025.
User Behaviour Shift
Challenge: Users might rely more on AI summaries instead of clicking on ads, leading to a lower CTR and fewer clicks to your website.
Solution: Adopt a multi-pronged approach across Google’s networks. Lean on Performance Max, Display and Demand Gen to ensure ads are placed on other networks to capture demand and drive users to the website from multiple places through more visual formats such as images and videos. These types of ads allow for more creativity and can be more eye-catching, which is great for more visual products.
Solution: Shift ad copy to be more intent-driven by thinking of solutions to commonly searched customer problems that can help tailor ads that compete with AI summaries.
Limited Ad Real Estate
Challenge: AI overviews could reduce the number of ad slots, pushing ads down and decreasing visibility, all whilst increasing CPCs as a result of heightened competition.
Solution: Focus on optimising ads to improve quality score. Higher QS = higher ad positions and lower CPCs.
Solution: Diversify beyond the search network. Display, Performance Max, YouTube and Demand Gen campaigns can reach users at all stages of the research funnel, and often see lower CPCs.
Murky Attribution
Challenge: AI responses blend information from multiple sources, making it harder to track the entire user journey.
Solution: Leverage first-part data to rebuild visibility into the customer journey. By using CRM data, Enhanced Conversions, Customer Match Lists and offline imports, we can more effectively match conversions back to campaign performance.
Emphasis on Brand Trust
Challenge: Users engaging with AI content might become more selective about the sources or brands they trust, making it harder for unknown brands to convert clicks into sales.
Solution: Ensure trust signals are pushed and prioritised across multiple content formats – on your website, in your ad copy, and with reviews, case studies, and customer success stories.
Solution: Use multiple ad formats to display a strong brand image and messaging. Using a mix of ad types and campaign objectives (e.g. awareness) will help connect with users further up the funnel, establishing the brand name.
