The Search Landscape Has Fundamentally Changed
If you opened Google recently and noticed something different, you are not imagining it. AI Mode — Google’s conversational, generative search experience — is no longer a beta experiment. It is the new default for millions of queries, and it is rewriting the rules of paid search visibility faster than any update since the introduction of Quality Score.
For B2B marketers and paid search managers, the stakes are enormous. Early data from Google’s own benchmarks suggests that AI Mode responses can reduce traditional blue-link click-through rates by 20–35% for informational queries. Yet at the same time, Google is rolling out new ad formats specifically designed for this environment — formats that reward advertisers who adapt quickly and punish those who cling to legacy keyword-matching strategies.
This article breaks down exactly what AI Mode means for your ad spend, which new products you need to understand, and how to restructure your campaigns to capture intent in a world where the search results page looks nothing like it did in 2023. Whether you manage Google Ads in-house or work with an agency, the playbook you are about to read is the one that matters right now.
What Is Google AI Mode and Why Does It Change Ad Delivery?
AI Mode is Google’s fully generative search experience, powered by Gemini. Instead of returning a ranked list of ten blue links, it synthesises an answer — complete with follow-up question suggestions, cited sources, and embedded product or service recommendations — directly on the results page.
From an advertising perspective, the critical shift is this: the traditional keyword auction still runs, but the ad placement logic is now layered on top of a semantic understanding of the entire conversation thread, not just the single query the user typed. Google’s system evaluates the full context — previous questions in the session, inferred intent, user location signals, and device behaviour — before deciding which ads to surface and in what format.
This has three immediate consequences for advertisers:
- Exact match is less exact. Google’s AI interprets meaning, not just words. An ad targeting “enterprise CRM software” may now appear for a user who typed “what tool helps my sales team track deals without spreadsheets” — if the AI judges intent alignment to be high.
- Ad position is no longer purely bid-driven. Relevance signals derived from your landing page, your creative assets, and your historical engagement data carry more weight than ever.
- New ad units exist that were not available 18 months ago. Sponsored answers, Direct Offers, and AI Max placements sit inside the generative response itself — not below it.
AI Max for Search: The Campaign Setting You Cannot Ignore
In early 2025, Google began rolling out AI Max for Search campaigns, a bundle of capabilities that supercharges traditional Search campaigns with generative matching and asset expansion. By mid-2026, it is available globally and is already the default recommendation for new campaigns.
AI Max does three things simultaneously:
- Keywordless matching: The system reads your landing pages, your ad copy, and your existing keyword list to infer additional queries it should enter auctions for — without you having to add those keywords manually.
- Creative asset expansion: Google generates headline and description variants using your brand guidelines and landing page content, then tests them dynamically.
- URL expansion: Rather than always sending traffic to your specified final URL, the system may route users to a more relevant page on your site if it predicts a better outcome.
For B2B advertisers, AI Max is both an opportunity and a risk. The opportunity is reach — campaigns routinely find high-intent queries that human keyword researchers miss. The risk is control — without proper negative keyword lists and URL exclusions, traffic can drift toward irrelevant audiences.
| AI Max Feature | Benefit | Risk if Unmanaged |
|---|---|---|
| Keywordless matching | Captures long-tail AI Mode queries | Budget waste on irrelevant intent |
| Asset expansion | Faster creative testing at scale | Off-brand messaging without review |
| URL expansion | Higher landing page relevance | Traffic sent to unoptimised pages |
| Audience signals | Better bid adjustments | Over-reliance on Google’s data |
Our recommendation: enable AI Max on your highest-performing Search campaigns first, layer in robust negative keyword lists from day one, and use URL exclusions to protect pages that are not conversion-optimised. Review the search term report weekly — it will surface query patterns you have never seen before.
Performance Max in an AI Mode World
Performance Max (PMax) was already Google’s most automated campaign type. In the AI Mode era, it has become even more central — and even more opaque. Google has positioned PMax as the primary vehicle for capturing demand across Search, Display, YouTube, Gmail, Maps, and Discover simultaneously, with the AI allocating budget dynamically across channels.
The key 2026 update is that PMax campaigns now bid directly into AI Mode placements. When a user’s conversational session generates a product or service recommendation slot, PMax is often the campaign type that wins that placement — because its asset groups are rich enough for Google’s AI to construct a relevant sponsored answer.
To maximise PMax performance in this environment, focus on three levers:
Asset group depth. Upload every image format, every headline variant, every video length. The more raw material Google has, the better it can assemble a relevant unit for each context. Sparse asset groups are now a significant competitive disadvantage.
Audience signals. Feed PMax your CRM lists, your website visitor segments, and your customer match audiences. These signals help the AI understand who your best customers look like, accelerating the learning phase and improving placement quality.
Search theme additions. Google now allows you to add up to 25 search themes per asset group — essentially telling the AI which topics are most relevant to your business. Treat these like broad match keywords with strategic intent.
| PMax Optimisation Lever | Impact on AI Mode Visibility | Priority |
|---|---|---|
| Complete asset groups (15+ headlines) | High — enables dynamic ad assembly | Critical |
| CRM audience signals | High — faster learning, better targeting | Critical |
| Search themes (up to 25) | Medium — guides topic relevance | High |
| Negative keyword lists (account level) | Medium — prevents brand safety issues | High |
| Conversion value rules | Medium — optimises for best customers | Medium |
Direct Offers: The New Ad Format Inside AI Answers
Direct Offers are the most significant new ad unit Google has introduced for AI Mode. They appear as sponsored cards embedded directly within a generative AI answer — not in a separate ad block above or below the organic content, but woven into the response itself.
A user asking “what is the best project management software for a 50-person engineering team” might receive a generative answer that includes two or three Direct Offer cards for relevant SaaS products, each showing a product image, a brief value proposition, a pricing signal, and a CTA button.
For B2B advertisers, Direct Offers are currently most effective for:
- Software and SaaS products with clear pricing tiers
- Professional services with a defined deliverable
- High-consideration products where comparison intent is strong
To be eligible for Direct Offers, your campaigns must meet several requirements: you need active PMax or AI Max campaigns, your Google Merchant Center or Business Profile must be linked and verified, and your landing pages must load in under 2.5 seconds on mobile (Google’s AI quality filter is strict on page experience).
If you are running ABM campaigns targeting specific accounts or industries, Direct Offers can be layered with audience targeting to ensure your card appears when users from your target account list are conducting relevant research sessions.
Keyword Strategy in a Conversational Search Environment
The death of the keyword has been announced prematurely many times. Keywords are not dead — but their role has fundamentally shifted from primary targeting mechanism to guardrail and signal.
Here is how to restructure your keyword strategy for AI Mode:
Shift from exact match to intent clusters. Group keywords not by surface-level word similarity but by the underlying intent they represent. A cluster around “reduce customer churn” might include queries that look very different on the surface but share the same business problem.
Invest in negative keyword architecture. As Google’s matching becomes broader, your negative keyword lists become your primary control mechanism. Build tiered negative lists: account-level negatives for irrelevant industries, campaign-level negatives for intent mismatch, and ad group-level negatives for competitive separation.
Use search term data from AI Max to discover new clusters. The keywordless matching in AI Max will surface queries you never anticipated. Mine this data weekly and promote high-performing themes into dedicated campaigns with tighter control.
Align keywords with conversational phrasing. AI Mode users ask questions in natural language. Adding question-format keywords — “how do I,” “what is the best way to,” “which tool helps with” — can improve your auction eligibility for high-intent conversational queries.
For a deeper look at how organic and paid search interact in this new environment, our SEO services team works alongside paid search to ensure your brand appears in both the generative organic answer and the sponsored placements simultaneously.
Measurement and Attribution in the AI Mode Era
One of the most disruptive aspects of AI Mode for advertisers is the measurement challenge. When a user has a multi-turn conversation with Google — asking five follow-up questions before clicking an ad — traditional last-click attribution assigns all credit to the final click and misses the entire journey.
Google’s solution is Meridian, its open-source Marketing Mix Modelling framework, combined with enhanced conversions and data-driven attribution within Google Ads. But for most B2B advertisers, the practical steps are:
Enable enhanced conversions immediately. This passes hashed first-party data back to Google, improving attribution accuracy even when cookies are absent. It is the single highest-ROI technical implementation available right now.
Move to data-driven attribution (DDA) across all campaigns. Last-click and position-based models are now actively misleading in an AI Mode environment. DDA uses machine learning to assign fractional credit across the full conversion path.
Implement server-side tagging. Browser-based tracking is increasingly unreliable due to ad blockers, browser restrictions, and the multi-device nature of conversational search sessions. Our tracking and reporting team can implement server-side solutions that dramatically improve data completeness.
| Attribution Model | Accuracy in AI Mode | Recommendation |
|---|---|---|
| Last click | Low — misses conversational journey | Discontinue |
| Position-based | Low — arbitrary credit weighting | Discontinue |
| Linear | Medium — spreads credit evenly | Acceptable interim |
| Data-driven (DDA) | High — ML-based fractional credit | Recommended |
| MMM + DDA combined | Very high — cross-channel view | Best practice |
Creative Strategy: Writing Ads That Win AI Mode Placements
Google’s AI assembles ad units dynamically from your asset library. This means the quality of your individual assets — not just your overall ad — determines whether you win premium AI Mode placements.
Several principles now govern high-performing creative:
Lead with specificity. Vague headlines like “Grow Your Business” perform poorly in AI Mode auctions because they provide weak relevance signals. Specific headlines like “Cut Sales Cycle by 30% with Automated Outreach” give the AI clear context for matching.
Include numbers and proof points. Google’s AI quality scoring rewards credibility signals. Headlines and descriptions that include statistics, customer counts, or specific outcomes consistently outperform generic claims.
Write for the question, not the keyword. Since AI Mode users phrase queries as questions, your ad copy should feel like a direct answer. “Struggling with manual reporting? Our dashboard automates it in 48 hours” matches conversational intent better than “Best Reporting Software.”
Maintain brand voice across all asset variants. With AI Max generating additional creative variants, establish clear brand guidelines in your Google Ads account and review auto-generated assets before they go live. Inconsistent messaging across AI-assembled units can damage brand perception.
If you need support scaling your creative production for AI Mode requirements, our AI content service helps B2B brands generate on-brand asset libraries at the volume these new formats demand.
Budgeting and Bidding in a Generative Search World
AI Mode has changed the economics of paid search in ways that are not yet fully reflected in industry benchmarks. Here is what we are seeing across client accounts:
CPC volatility has increased. Because AI Mode auctions factor in conversational context, the same keyword can command very different CPCs depending on where it appears in a user’s session. Early in a research conversation, CPCs tend to be lower; as intent sharpens across turns, CPCs rise significantly.
Conversion rates for AI Mode placements are higher. Users who engage with a sponsored Direct Offer or AI Max placement inside a generative answer are typically further along in their decision process. Across B2B accounts, we are seeing 15–25% higher conversion rates for confirmed AI Mode placements compared to traditional SERP positions.
Target CPA and Target ROAS bidding strategies outperform manual bidding. Google’s Smart Bidding has access to AI Mode session signals that manual bidders cannot see. In this environment, fighting the algorithm is counterproductive. Set ambitious but realistic targets, give campaigns sufficient conversion volume (50+ conversions per month minimum), and let Smart Bidding operate.
For budget planning, our calculator can help you model the expected impact of shifting budget toward AI Mode-optimised campaigns based on your industry and average deal size.
Conclusion: Adapt Now or Cede Ground to Competitors
Google AI Mode is not a future trend — it is the present reality of paid search in 2026. The advertisers who are winning are those who have embraced the new campaign types, rebuilt their creative strategies around asset depth, implemented first-party data infrastructure, and accepted that control in paid search now means intelligent guardrails rather than rigid keyword lists.
The core principles have not changed: reach the right person, with the right message, at the right moment. What has changed is the mechanism. AI Mode means the “right moment” is now a multi-turn conversation, the “right message” is dynamically assembled from your asset library, and the “right person” is identified through intent signals that go far beyond a single keyword.
For B2B brands navigating this transition, the path forward requires coordination across paid search, content, first-party data, and technical tracking — exactly the kind of integrated approach we bring to every engagement. Explore our Google Ads and AI solutions services, or contact us to discuss how we can help your brand stay visible as search continues to evolve.
