Digital discoverability is undergoing its most significant transformation in decades, with large language models (LLMs) and artificial intelligence (AI)-driven answer engines reshape how B2B buyers find information, the traditional goal of ranking first on a search results page is no longer enough.
As a result, the battleground has shifted to winning influence from winning clicks, requiring B2B marketers to rethink how their content is structured, crawled, and cited by AI systems. The rise of Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) isn’t just a trend—it’s the new strategic foundation for modern visibility.
To help navigate this shift, we sat down with Patrick Reinhart, VP of Services and Thought Leadership at Conductor who offered his view of how top-performing B2B teams are adapting their budgets and workflows that were found in their recently released The State of AEO/GEO in 2026: CMO Investment Report. Reinhart explains why traditional SEO remains a critical technical bedrock, breaks down the practical steps organizations need to take to secure their place in AI-generated answers and allocate the right percentage of marketing budget to measuring success through “share of answer” rather than just session traffic.
Demand Gen Report (DGR): Patrick, thanks for your time. The report states AEO/GEO is now the top strategic priority for 2026. How should B2B enterprises balance investments in traditional SEO and AEO/GEO for maximum impact?
Patrick Reinhart: Thanks for having me. Our report found that the most effective B2B teams are not treating AEO/GEO as a replacement for SEO, but as an evolution of it. Traditional SEO still provides the technical and structural foundation, crawlability, site health, internal linking, and content quality all remain critical. Without that foundation, AEO/GEO efforts simply do not scale.
What’s changing is how investment is weighted. The balance shifts from optimizing for rankings and clicks alone to optimizing for visibility and influence across both search engines and answer engines.
At the same time, teams are rethinking both content production and measurement. The priority is no longer publishing more content to chase incremental traffic, but creating high-quality, authoritative content at scale that AI systems can confidently reference. Success is increasingly measured by citations, brand mentions, and share of AI-generated answers, not just sessions, reflecting a broader shift from traffic as the primary KPI to visibility and trust as leading indicators of performance.
DGR: How does a B2B marketer leverage AEO/GEO to improve digital discoverability in 2026?
Reinhart: Digital discoverability is increasingly being absorbed by LLMs. In 2026, more of the customer journey, from early research through evaluation and even conversion, is happening inside AI-driven experiences rather than on traditional search results pages. As a result, AEO/GEO has become a core component of any modern discoverability strategy.
In this environment, discoverability is less about being the top-ranked result and more about being the trusted source behind the answer. B2B marketers leverage AEO/GEO by designing content specifically to support how AI systems interpret, synthesize, and cite information. That means prioritizing clear topic ownership, deep explanatory content, and consistent signals of expertise across the site.
High-performing teams treat their content ecosystem as a reference layer rather than a click destination. They actively monitor where and how their brand appears in AI-generated answers, so optimization decisions are based on actual visibility, citations, and mentions within LLM outputs, not assumptions driven by declining traffic metrics.
Budget Priorities
DGR: In this new landscape, what percentage of digital marketing budgets should B2B organizations allocate to AEO/GEO for competitive advantage?
Reinhart: Based on current enterprise benchmarks, most organizations allocated around 12% of their digital marketing budgets to AEO/GEO in 2025. In 2026, competitive organizations are pushing that closer to 15% or above, particularly those with higher AEO/GEO maturity.
But the more important factor is consistency— organizations that treat AEO/GEO as an ongoing capability, rather than a short-term experiment, are able to compound gains in AI visibility. Under-investing early creates a gap that becomes increasingly difficult and expensive to close as AI-driven discovery matures.
DGR: What are the best ways for B2B marketers to measure the ROI of AEO/GEO investments in 2026?
Reinhart: ROI measurement needs to reflect how AI actually influences discovery and decision-making. Clicks and sessions still matter, but they no longer tell the full story.
The most effective teams track AI-specific visibility metrics such as brand mentions, domain citations, share of answers, and exposure within AI Overviews and answer engines. Those signals are then connected to downstream outcomes like conversion rates, pipeline influence, and revenue efficiency. The goal is to understand whether AI visibility is improving the quality and speed of demand, not just driving incremental traffic.
DGR: How does AEO/GEO maturity impact the effectiveness of AI-driven marketing strategies in B2B? What are the top challenges marketers face?
Reinhart: AEO/GEO maturity directly impacts how well AI-driven strategies perform. Organizations with higher maturity have integrated AEO/GEO into content planning, technical workflows, and reporting, allowing them to scale with confidence as AI surfaces change.
The top challenge remains execution. Generating AI-optimized content at scale is difficult without strong processes, clear editorial standards, and reliable technology and data. Teams also struggle with visibility into whether their content is being crawled and interpreted correctly by AI bots. Without that feedback loop, optimization becomes reactive rather than systematic.
Tailoring Content for AEO
DGR: How can B2B organizations ensure their content is being crawled and cited by AI bots effectively?
Reinhart: It starts with technical reliability. AI systems will not cite content they cannot consistently access or understand. Continuous site monitoring, fast remediation of technical issues, and clean information architecture are non-negotiable.
Website content needs to be structured for machine understanding. Clear headings, schema markup, structured data, and explicit authorship help AI systems assess credibility and relevance. When content is easy to parse and clearly authoritative, it is far more likely to be cited in AI-generated responses.
DGR: Being a voice of authority is key. How can B2B organizations use exclusive data and original research to establish authority in AI search?
Reinhart: AI systems strongly favor sources that contribute original information. Exclusive data, benchmarks, and proprietary research provide signals that a brand is not simply restating existing knowledge.
For B2B organizations, this means investing in first-party research, industry benchmarks, and original insights tied directly to their expertise as these assets function as citation anchors for AI systems and perform well across PR, analyst relations, and sales enablement. Authority built this way is difficult for competitors to replicate.
DGR: What strategies can B2B marketers adopt to increase AI search visibility through brand mentions and domain citations?
Reinhart: Brand mentions and citations increasingly come from building deep authority through first- and third-party content. B2B marketers should align content, digital PR, and thought leadership to ensure their brand consistently appears in authoritative contexts. This includes publishing research, contributing expert commentary, and earning coverage where AI systems already look for trusted information. The goal is to create a broad, consistent presence that reinforces brand authority across multiple trusted sources, which AI systems then recognize and reflect in answers.
The Metrics that Matter
DGR: With the growing importance of AEO, how does AI referral traffic compare to traditional SEO metrics for success? What KPIs should B2B marketers prioritize in 2026?
Reinhart: AI referral traffic is still a small percentage of total traffic, but it plays a disproportionate role in early-stage decision-making. Traditional SEO metrics like rankings and organic traffic remain useful, but they no longer capture the full scope of digital visibility.
In 2026, priority KPIs include AI citation frequency, mentions frequency, AI market share and revenue influenced by AI-driven discovery. These metrics better reflect how brands are being evaluated before a user ever reaches a website.
DGR: What do you see as the top AEO/GEO-related content strategies for B2B organizations in 2026?
Reinhart: The strongest AEO/GEO content strategies focus on depth, structure, and authority. That includes scaling long-form content, implementing structured data, building cohesive topic clusters, and publishing original research.
High-performing teams invest in content at scale that clearly demonstrates expertise and can be reliably understood by both humans and AI systems. That type of content earns sustained visibility across search engines, answer engines, and emerging AI-driven experiences.
