Key Takeaways:
- Branch’s Adam Landis AI details how AI-search delivers fewer but higher-intent users, requiring marketers to shift focus from quantity to quality in funnel management.
- Coexistence of AI search and traditional SEO is expected, with both channels growing and requiring innovative measurement methodologies.
Artificial intelligence (AI) has rapidly redefining how B2B marketers connect with their target audiences, making the shift from traditional search to AI-driven discovery a top priority.
Branch’s AI Search and Discovery Enterprise Benchmark Report dives into how organizations are managing this complex transition. Surveying 300 enterprise leaders, the report reveals data on the pursuit of reliable performance measurement and how AI search is generating fewer but significantly higher-intent users for B2B platforms.
To help us interpret these market-shifting findings, we sat down with Adam Landis, Head of Strategic Growth at Branch. Landis in our discussion detailed the significant challenges marketers face when adapting to AI-driven discovery models, the anticipated coexistence of traditional SEO and AI search, and forward-looking guidance on how to balance budget allocations.
Demand Gen Report (DGR): Adam, thanks for taking time to answer our question about the recent report from Branch. In the report, what are the most significant challenges B2B marketers face when adapting to AI-driven discovery?
Adam Landis: In Branch’s recent survey of 300 enterprise leaders, only 3% of respondents reported negative results from AI search. But when asked to share an opportunity or concern, over 60% opted to share concerns.
Like most emerging technologies, early concerns center on transparency and accuracy. That’s not surprising. LLMs are notoriously unreliable, which their proponents are quick to point out is a feature of the system, not a bug. They’re also opaque. Model providers don’t readily share the weights that make up the highly proprietary models.
Unfortunately, for marketers, that means we’re dealing with a black box that returns unreliable answers. That’s a significant challenge, and an understandable one.
DGR: What are the top strategies B2B marketers can adopt to optimize for AI-powered search platforms?
Landis: It’s well understood at this point that marketers need clean, structured data that LLMs can consume. But that’s about as far as we’ve gotten.
These are black boxes, and we’re stuck literally asking the model where we rank against competitors. It’s very reminiscent of early days in SEO. And like SEO, I don’t expect this to ever be fully figured out. Models will constantly change. But over time, we’ll develop methods to measure, test, and iterate on optimization techniques. With practice, we’ll get better and faster at understanding what works.
How SEO, AI Search Can Coexist
DGR: How do you see traditional SEO and AI search coexisting in the future for B2B marketers?
Landis: I’ve been thinking about this since seeing the data. Respondents expect both SEO and AI search traffic to increase in 2026. I don’t think AI will ever fully replace SEO, at least not as recognized by the consumer. It’s a new, additive channel.
When we look back, we’ll see a gradual convergence of AI and SEO until users stop differentiating between them. It’ll less be like the automobile replacing the horse and more like mobile smartphone usage outpacing the personal computer. Today, we use automobiles to get to the store. We use computers to get to the internet. Whether that computer is in our pocket or on our desk is beside the point.
DGR: What are the implications of AI search delivering fewer overall visits but higher-intent traffic for B2B marketing strategies?
Landis: For marketers, this is classic funnel management: If you’re not focused on getting more users into the funnel, you’re focused on increasing funnel throughput. With AI delivering fewer, but higher-intent users, many marketers are seeing similar or better conversion rates.
This shift from quantity to quality requires a change of technique. Lower-quality traffic requires investment in targeting and performance optimization to fill the funnel efficiently. For higher intent users, marketers invest in lower-funnel mechanisms like personalization, retention, and reengagement. As traffic moves down the funnel, so must marketer focus.
The New Priorities of B2B Marketing Budgets
DGR: The report mentions that 65% of leaders are dedicating at least a quarter of their 2026 marketing budget to AI search. What advice would you give to those just starting this journey?
Landis: Most things in marketing come down to ROI. And right now, you can’t measure the return without solving measurement, which is exactly where most marketers are stuck. Almost 70% of respondents are struggling with the very basics of measuring AI. As with any new technology, the standards and tools are still developing.
Measuring AI isn’t easy, but those who develop strong measurement methodologies early will quickly learn how to outpace their competition. Getting measurement right early is how you maximize return on what’s becoming one of the most important growing channels.
DGR: How should B2B marketers approach budget allocation between traditional SEO and AI search optimization?
Landis: Spend allocation should always rely on measurement. And measurement should indicate return on your investment. AI search is emerging as a powerful, fast-growing, but additive channel. Marketers will first need to learn how to measure the combined output of AI and SEO before they decide how to allocate spend across them.
DGR: How can B2B marketers measure the effectiveness of AI-driven discovery when traditional analytics tools fall short?
Landis: Mobile app analytics struggled to measure advertising impact until Facebook developed the concept of a mobile measurement partner (MMP). AI-driven discovery faces a similar early-stage challenge.
But this is an opportunity. Firms are already combing server-logs to measure AI-bot traffic and finding the language that LLMs prefer. Companies who develop their own methods for measuring optimization outcomes, when existing tools fall short, will come out ahead in the rapidly growing LLM economy.
Changing for the AEO World
DGR: How can B2B marketers ensure their brand is included in AI-generated synthesized answers?
Landis: LLMs operate differently than humans, and marketers need to adjust accordingly.
For instance, LLMs aggregate multiple sources of information, which means they reward message consistency. This is a meaningful shift from SEO. With search, you can target individuals with antithetic intent: I can market an automobile as both “luxurious” and “affordable,” complete with supporting documentation across two separate landing pages. A user looking for either will come across their respective page. An LLM consumes both pages and produces an aggregated result that may be unclear or dropped from the response entirely.
DGR: What are the most common misconceptions B2B marketers have about AI search and discovery?
Landis: This report disabused me of one: AI search is replacing SEO. The data shows budgets and traffic for both channels are growing and remain an important part of the discovery process.
DGR: How do you see AI search impacting the customer journey for B2B buyers in the next few years?
Landis: The most interesting data point in this report is that 87% of respondents expect their business to execute closed-loop AI transactions this year. This is incredible given that, as of this response, there isn’t a widespread technology that even allows AI transactions (though OpenAI may change their mind yet again next week), but here we have executives at large organizations expecting they’ll participate within months.
This, more than anything else, truly underlines how dramatically the customer journey is expected to change.
What B2B Marketers Should Do to be Prepared
DGR: What do you see as the next big innovation in AI search and discovery, and how should B2B marketers prepare for it?
Landis: Advertising, without a doubt. Like traditional search, social media, streaming, or any newly adopted consumer technology, the biggest impact to marketers will be the emergence of a new, scaled, and evolving advertising mechanism.
The entire direct-to-consumer model was enabled by targeted, programmatic advertising. The concept of “freemium” was enabled by the App Store’s distribution and monetization channels. AI search advertising will enable new business models and new routes to consumers. And like every new technology, the companies that can most quickly learn how to test, experiment, and measure outcomes will be the ones who benefit most.
AI search has arrived. The companies that will build successful businesses around it are already on their way.
