How Financial Brands Can Build a Winning AEO Strategy from the Ground Up 

Search engine optimization (SEO) became an established industry with growing competition to rank in online search engine result pages (SERPs) in the mid-1990s. What started as an effort for brands to surface their content by including consumer-focused keywords that targeted user search intent developed into a market valued at $92.74 billion in 2025.

While SEO tactics have evolved to include more robust data-backed methods, occasionally challenged by changes to search engine algorithms, the industry has experienced limited notable disruption. 

However, the recent introduction of widespread artificial intelligence (AI) access and implementation has dramatically shifted the SEO landscape. AI tools like ChatGPT and Perplexity AI, both launched in late 2022, changed the way search users interacted with information online. Soon after, search engines like Google and Bing began heavily integrating AI into public-facing search interfaces and backend algorithm updates. 

The result has been a significant change in how users search for content and how search engines present relevant answers. In response, SEO is quickly being overtaken by AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization) as approaches for brands to surface their content in response to consumer search behavior and tools. 

Answer Engine Optimization is the process of structuring content in order for AI-powered search engines to easily identify and deliver that content as the most authoritative answer to user questions, searches, and prompts. Generative Engine Optimization is the practice of optimizing content so AI-driven search, chat, and generative models surface it in generated responses.

The pivot to AI-powered search has also altered how content is accessed by users and how efforts are evaluated by marketers. SEO focuses on driving clicks and improving SERP rankings. AEO and GEO prioritize zero-click visibility. This means AI engines aim to surface content directly on the search results page with AI-generated answers using any number of online sources. These strategies are designed to provide instant answers that, ideally, do not require additional time, research, or link clicks for users to arrive at a solution. 

This shift in how information is sourced and presented is especially crucial in regulated, trust-sensitive industries like finance. With AEO and GEO, the authority, accuracy, and clarity of content pages and broader websites can determine whether that information is used as a source by emerging AI search systems.

This also means traditional SEO key performance indicators (KPIs) used to measure success are less relevant to AEO and GEO systems. Metrics such as click-through rate (CTR), average position, and organic traffic volume are becoming less insightful for digital marketing efforts. Instead, KPIs for AEO and GEO can be assessed through visibility, citation frequency, source attribution, and referral traffic.

Rather than disregarding SEO, marketers can take an integrated approach to incorporate SEO, AEO, and GEO practices alongside broader public relations and brand strategies. This can be achieved by aligning technical optimization with content development that underscores authority building, narrative control, and audience trust.

Understanding AEO: Why It’s the Next Frontier in Financial Marketing

Answer Engine Optimization is powered by a specific type of AI technology called a Large Language Model (LLM). LLMs are designed to receive user input (i.e. a search question or prompt), understand that text based on training data, and generate a conversational response. 

LLMs are used by answer engines, chatbots, and AI assistants to go beyond traditional search results and provide a synthesized answer for the user. They tend to select sources based on an algorithm that assesses the content’s authority and accuracy along with its relevance to the user’s search intent. 

To do this, LLMs also prioritize structured information presented in clear language that can be easily parsed and verified. Domain expertise, consistent factual reliability, and strong engagement can help increase the likelihood that a brand’s content will surface in an AI-generated response. 

Financial brands already understand the importance of providing credible, factually accurate information. Your Money or Your Life (YMYL) standards for SEO have emphasized the need for strict quality standards for content addressing topics that can impact user safety, health, or stability. This includes financial content that can have major consequences on consumer well-being. AEO and LLM standards further highlight the importance of information accuracy since they assess and source content that is credible and deemed authoritative rather than relying on keyword volume or relevance.

For the financial industry, recognition as a trusted source within AI-generated answers directly impacts visibility and reputation. Brands that are not optimized for AEO and GEO risk being excluded from critical, high-intent conversations. Prioritizing trust signals, authoritative content, and accurate data can help financial brands remain discoverable and dependable moving forward.

Measuring this discoverability is also changing with the transition from click-through rates to inclusion metrics and trustworthiness. Marketers will need to assess how often AI systems include their brand content in synthesized responses to user queries. In compliance-heavy sectors like finance, credibility and accuracy drive visibility, and being included matters more than being clicked. Early data shows that bottom-of-funnel (BOFU) traffic from LLM-generated responses converts at 10% or higher, demonstrating users who trust the answer they receive are taking action with high intent.

Building Brand Visibility in LLMs 

Financial brands need to continue adhering to SEO best practices while integrating AEO requirements for brand visibility in this new normal. To target LLMs, marketers should aim to increase how often their brand is referenced, recommended, or acknowledged by AI systems. The ultimate goal is to build a consistent presence across both human and machine platforms to ensure the brand is trusted, cited, and surfaced wherever financial decisions begin for search users.

One factor to consider is the impact of an AI system tendency known as big brand bias. Because they are trained on large amounts of online data typically dominated by larger brands with more mentions, backlinks, and total available material, LLMs tend to include content from big brands more frequently than their smaller counterparts. Big brand bias is an intrinsic predisposition for LLMs to present answers that include content and sources from well-known or established brands. This can be especially true in the U.S., where large enterprise commercial banks represent 62.51% of the market. 

This does not mean smaller financial institutions (FIs) are excluded from the AEO picture. Small and midmarket financial brands can counter big brand bias in LLMs by creating distinctive, proprietary content that offers unique insights or data not found elsewhere, giving AI systems a reason to reference their expertise. 

Structuring authoritative content properly can also help surface material in LLM-generated responses. This can include:

• Incorporating clear headings, subheadings, and semantic markup that signal key topics and hierarchy

• Using bullet points, numbered lists, and concise paragraphs to make information machine readable and easier for AI to parse

• Including precise terminology, definitions, and credible citations to reinforce authority

• Working with an integrated branding agency to optimize existing content and create a strategic content calendar

Pairing corporate-owned content with earned media on high-authority, third-party sites can also enhance credibility and signal brand trustworthiness to LLM models. Integrating PR and communications into AEO can amplify this effect. To do this, marketers can prioritize authoritative coverage and third-party quotes. 

Publishing content at regular intervals and maintaining authoritative messaging across all web properties reinforces expertise, while leveraging user-generated content, reviews, and forum discussions taps sources LLMs frequently reference. This can help smaller brands increase recognition and be surfaced alongside larger competitors in LLM-synthesized results.

Strengthening Web Citation Visibility in LLMs 

Strengthening brand visibility in LLMs starts with ensuring content is discoverable, credible, and authoritative. Financial services marketers should take a strategic approach to content, credibility signals, and technical optimization to boost chances their brand will be recognized and cited by AI-driven platforms.

SEO Fundamentals

Even as AEO and GEO evolve, technical SEO should remain the foundation for strong online visibility and digital marketing. Marketers can continue to publish content that is crawlable, well-structured, responsive, and optimized with fast load speed. Website pages should incorporate a logical internal linking framework to help users and AI understand site hierarchy. 

HTML should be clean, or free of errors and depreciated code. Clean HTML and optimized page performance can make it easier for LLMs and search engines to evaluate content accurately. Adding FinancialService schema markup can provide context for AI systems to better understand and more reliably extract content to increase the likelihood a brand is sourced in AI-generated answers.

Content Strategy for AEO

To develop an effective AEO content strategy, marketers can focus on proprietary insights and BOFU content such as pricing pages, comparison tools, and regulatory FAQs highlighting a brand’s unique value. This is especially important in helping smaller FIs stand out in the context of big brand bias. 

Marketers should avoid creating generic, top-of-funnel content that AI platforms can summarize without providing attribution since this limits brand recognition. Instead, publishing new content that offers novel insights, new facts, or proprietary data can help a brand become a referenced authority and increase the chances that AI platforms will surface that content.

Regularly updating content marketing while remaining aligned with regulatory standards can also help build credibility. This signals to LLMs that information is current and accurate, making a brand more likely to be used in AI responses over outdated or static sources.

Showcase E-E-A-T

Establishing credibility and trust with AI platforms for AEO also requires the implementation of the E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) principle. This process starts with clearly reinforcing authorship, compliance, and business purpose across About pages and leadership content. Again, signaling verified expertise and organizational transparency can help increase the probability that LLMs will reference this content as a trusted source. 

Using schema and structured data to define organizational roles and industry-specific legal identifiers that can enhance trust and AI visibility. Examples include: 

• SEC or FINRA registration numbers for broker-dealers and investment advisors
• FDIC or NCUA charter numbers for banks and credit unions
• Insurance license numbers issued by state insurance regulators
• CFTC or NFA IDs for commodities and futures professionals
• CFP or CFA certifications for financial planners and analysts

Including these identifiers in structured data helps LLMs verify regulatory compliance and professional authority, making content more likely to be cited.

Measuring Success: Building an AEO Performance Baseline

As already highlighted, the changes brought on by AEO and GEO have also altered how marketers can measure success. KPIs are evolving beyond traditional SEO metrics, and marketers now need to consider new inclusion and coverage metrics. 

Inclusion metrics evaluate how often the brand is mentioned or cited in AI responses. These can include LLM-generated answers or featured snippets. Marketers should also monitor zero-click acquisition, such as People Also Ask box dominance, which case studies show can increase brand visibility by 214%. Coverage metrics measure whether specific content fully answers high-intent questions. Examples of this include question completion rate, topic depth, and content comprehensiveness scores. 

While the AEO industry is fast evolving, marketers can leverage tools specifically designed to track inclusion and coverage KPIs to inform their strategy. Vested’s partnership Scrunch.ai is structured to make it easier to monitor these metrics at scale. In addition, tracking LLM referral traffic and conversion rates through GA4 custom reporting can help quantify BOFU impact. Citation velocity, or the frequency and quality of third-party mentions, can signal growing brand authority. 

Steps to Building a Sustainable AEO Strategy

Establishing an AEO strategy requires a holistic approach that aligns content, technical SEO, and brand authority. By following structured steps, brands can create, maintain, and optimize content to earn trust, inclusion, and long-term visibility with AI answer systems.

Step 1: Understand Your Audience

Effective AEO requires a clear understanding of target audience and user search intent. Marketers can leverage research, surveys, and real consumer questions to guide content development. The objective is to develop material that corresponds with high-intent queries. In turn, tailored content increases relevance and the chances of being surfaced by AI.

Step 2: Strengthen Your Messaging Foundation

Clarity and specificity are essential for consumers and AI platforms to understand a brand. Messaging should clearly articulate what is on offer, who it is intended for, and the value it provides. A strong messaging foundation helps LLMs accurately interpret and reference content, while consistency across pages reinforces brand authority.

Step 3: Prioritize Accessibility

Word choice is just one part of creating effective content. It should also use structured headings, bullet points, semantic organization, clean HTML, modular layouts, and JSON schema markup to make it easy for AI systems to understand. This accessible, well-structured approach improves indexing, comprehension, and the possibility of content being accurately referenced by AI engines. 

Step 4: Elevate Brand Reputation

AI platforms rely, in part, on established brand authority when choosing sources to reference. One way to improve brand reputation is to secure quotes and coverage in respected industry publications. Using platforms like Qwoted or leveraging respectable PR partnerships can help marketers cultivate high-quality, third-party references to signal trustworthiness to AI.

Step 5: Maintain High-Value Content

Consistency and originality are critical to long-term AEO success. Brands need to regularly publish unique, authoritative content to remain a reliable, respected source with LLMs. Developing comprehensive guides, research reports, and in-depth analyses offering high-value material that addresses real user needs is core to this strategy. By publishing unique, fresh content that cannot be easily summarized without attribution, brands can remain top-of-mind for users and AI platforms.

How Vested Can Help

Vested is uniquely positioned to help financial brands integrate all critical components of AEO into a results-driven strategy. Our dedicated team understands how to break down traditional silos and develop bespoke marketing approaches that encompass PR, brand visibility, technical SEO, and high-value content. With proven governance and compliance expertise in the financial sector, we ensure content is authoritative and trustworthy. 

Connect with us to assess your AEO readiness and develop a roadmap tailored to your organization.