How AI Search Is Recommending Online Financial Advisors

Consumer discovery of online financial advisors is shifting from search engine results to AI-generated shortlists. When a prospective investor asks ChatGPT, Gemini, or Perplexity for the best robo-advisor or a comparison of managed portfolio services, the AI platform now produces a ranked recommendation list that shapes which brands enter the buyer consideration set. Being named in that response is no longer enough. The critical question is whether the AI system recommends the brand as a top choice.

The LLM Authority Index benchmark for June 2026 reveals that AI recommendation power in the online financial advisor category is concentrated in two dominant platforms. Betterment and Wealthfront together capture a disproportionate share of the modeled monthly AI opportunity value, while several well-known brands appear frequently in AI responses but rarely earn shortlist positions. This report interprets those benchmark findings and explains what the data means for every brand competing in the category.

Methodology

1. Market studied: Online Financial Advisors, including robo-advisors, managed portfolio services, and digital financial advisory platforms.
2. Brands/entities included: Betterment, Wealthfront, SoFi, Fidelity Go, Schwab Intelligent Portfolios, Ellevest, Empower (Personal Capital), Facet Wealth, Vanguard Personal Advisor, and Zoe Financial.
3. Data collection date/window: June 2026.
4. AI platforms tested: ChatGPT, Gemini, Copilot, Perplexity, Google AI Mode, and Google AI Overviews.
5. Number of prompts tested: Prompt count was not provided in the supplied dataset. A total of 1,282 observations were analyzed across all platforms and prompt clusters.
6. Prompt categories: Discovery (awareness-stage), Comparison (consideration-stage), and Pricing and Fee Evaluation (decision-stage).
7. Definition of a mention: A mention means the company appeared in an AI-generated response, regardless of sentiment, rank, or framing context.
8. Definition of a valid recommendation: A valid recommendation is a positive, shortlist-quality or ranked recommendation that earns recommendation credit. This is the key CiteWorks distinction: visibility in an AI response is not the same as recommendation credit.
9. Ranking and scoring metrics used: Valid recommendation coverage, Top 3 rate, rank-one rate, Top 10 rate, average recommended rank, net sentiment score, and modeled monthly AI Authority Value.
10. Limitations: This is a point-in-time benchmark. AI outputs can change. Modeled values are estimates and not revenue. This report is not a full audit or a full market census. Prompt count was not disclosed in the supplied data; observation counts are used as the primary volume measure.

Key Findings

Two brands control the recommendation layer. Betterment and Wealthfront appear in roughly half of all observations and each earns a valid recommendation in approximately 30% of cases. Their combined modeled monthly AI Authority Value of $3.73 million represents 16.5% of the total $22.7 million category-wide opportunity. No other brand in the benchmark achieves a valid recommendation coverage rate above 15%.

SoFi shows a pronounced visibility-to-recommendation gap. SoFi appears in 18.3% of observations but earns a valid recommendation in only 7.6% of cases. Its modeled monthly AI Authority Value of $1.03 million is roughly half that of either category leader. The analysis found that SoFi is frequently mentioned in AI responses but is not being advanced into buyer shortlists at the same rate, a pattern suggesting the brand has presence without proportionate recommendation credit.

Empower (Personal Capital) is the most exposed brand in the category. Empower appears in 43 observations across all platforms but earns exactly one valid recommendation across all 1,282 observations, with that single recommendation ranking at position 7. Its net sentiment score of 0.02 indicates AI responses are essentially neutral. For a brand with significant market presence, the benchmark shows the starkest example of presence without recommendation power in this dataset.

Fidelity Go achieves the best average recommended rank in the category. When Fidelity Go earns a recommendation, its average recommended rank is 2.23, the strongest rank quality in the benchmark. On Copilot specifically, the analysis found a 19.1% Top 3 rate and a 17.3% rank-one rate. However, its overall valid recommendation coverage of 14.7% limits its total modeled monthly AI Authority Value to $222,000, illustrating that rank quality alone does not compensate for limited recommendation frequency.

Decision-stage prompts favor Betterment decisively. In the Pricing and Fee Evaluation cluster, which carries the highest buyer-stage multiplier in the model at 1.5x, Betterment captures $1.15 million in modeled monthly AI Authority Value compared to Wealthfront's $391,000 in the same cluster. This cluster represents the highest-intent buyers, and Betterment's concentration here indicates it is winning the final selection stage where commercial impact is largest.

What Changed in the Market

Buyers evaluating online financial advisors are no longer moving exclusively from search engine results to brand websites. They are also asking AI systems to compare robo-advisors, explain fee structures, surface alternatives, and recommend shortlists. This shifts the competitive dynamic because AI platforms present answers as ranked lists. A brand appearing first or second in an AI response has disproportionate influence on consumer consideration before the buyer ever visits a website.

For trust-sensitive financial services categories, the stakes of AI recommendation positioning are particularly high. Consumers evaluating managed portfolio services are making decisions about their personal finances. They want reassurance that the recommended provider is legitimate, well-reviewed, and competitively priced. When an AI platform delivers a shortlist with positive framing, it functions as an implicit endorsement. The brands that earn that framing benefit from a form of trust transfer that is difficult to replicate through paid advertising alone.

The benchmark data shows that AI systems in this category are building shortlists from a narrow set of trusted sources. Betterment and Wealthfront benefit from extensive coverage across comparison articles, review sites, financial media, and official content. Their citation architecture is broad and consistent. When an AI system evaluates which robo-advisor to recommend, it finds multiple high-quality sources supporting both brands across the awareness, consideration, and decision stages of the buyer journey.

Several brands with strong name recognition outside this category appear to face a different structural problem. SoFi's broader identity as a lending and banking platform, Schwab's identity as a full-service brokerage, and Fidelity's identity as a fund company may be diluting the advisor-specific recommendation signal that AI systems use to build shortlists. Recognition earned in adjacent categories does not automatically transfer to recommendation credit in a specialized prompt cluster.

What the Benchmark Found

Recommendation leaders

Betterment leads the category with a modeled monthly AI Authority Value of $1.99 million. The analysis found it appearing in 50.6% of all observations, earning a valid recommendation in 30.7% of cases, and achieving a Top 3 rate of 22.5% with a rank-one rate of 10.6%. Its average recommended rank is 2.45, meaning when Betterment is recommended, it typically appears near the top of the list. Its net sentiment score of 0.70 is the highest in the category, indicating consistently positive framing across AI platforms.

Wealthfront closely trails Betterment with a modeled monthly AI Authority Value of $1.74 million. It appears in 50.9% of observations and earns a valid recommendation in 30.4% of cases. Wealthfront holds the highest rank-one rate in the category at 13.1%, and its average recommended rank of 2.35 is marginally stronger than Betterment's. The analysis found that Wealthfront leads the comparison cluster, where it captures $682,000 in modeled monthly value versus Betterment's $157,000 in the same cluster, suggesting Wealthfront is particularly well-positioned when buyers are actively weighing alternatives.

Visible but under-recommended

SoFi appears in 18.3% of observations but earns a valid recommendation in only 7.6% of cases. Its Top 3 rate is 4.5% and its rank-one rate is 3.7%. The average recommended rank of 3.06 is competitive when SoFi is recommended, but the low recommendation coverage rate means the brand is frequently named without being advanced. Its modeled monthly AI Authority Value of $1.03 million reflects the size of the visibility gap relative to its mention presence.

Schwab Intelligent Portfolios appears in 24.1% of observations and earns a valid recommendation in 10.2% of cases. Its modeled monthly AI Authority Value is $310,000. The Top 3 rate is 4.5% and the rank-one rate is 3.0%, with an average recommended rank of 3.15. The benchmark shows Schwab performs best on Google AI Overviews, where it achieves a 9.7% Top 3 rate and a 6.9% rank-one rate, suggesting a platform-specific recognition pattern that is not fully replicated across other AI systems.

Strong niche performer

Fidelity Go appears in 27.9% of observations and earns a valid recommendation in 14.7% of cases. Its modeled monthly AI Authority Value is $222,000. The benchmark marks Fidelity Go with the best average recommended rank in the category at 2.23, a Top 3 rate of 12.0%, and a rank-one rate of 6.3%. Copilot is its strongest platform, where it achieves a 19.1% Top 3 rate and a 17.3% rank-one rate. The gap between its rank quality and its total captured value reflects the commercial cost of limited recommendation frequency.

Present but commercially weak

Empower (Personal Capital) appears in 3.4% of observations and earns exactly one valid recommendation across the full dataset. That recommendation ranks at position 7. The net sentiment score of 0.02 indicates AI responses are essentially neutral about the brand. The benchmark data suggests Empower is being mentioned in factual or comparison contexts rather than positive recommending contexts, a meaningful distinction given the brand's market presence.

Facet Wealth appears in 4.2% of observations but earns only 7 valid recommendations in total. Its net sentiment score of 0.15 indicates weak positive framing. The brand has a limited AI recommendation footprint.

Under-cited challengers

Vanguard Personal Advisor appears in only 1.8% of observations and earns a valid recommendation in 0.9% of cases. Its net sentiment score of 0.52 is relatively strong, but the low presence rate limits its total modeled monthly AI Authority Value to $1,707. The evidence suggests the brand has meaningful framing quality when mentioned, but insufficient mention frequency to generate material recommendation value.

Ellevest appears in 2.9% of observations with a net sentiment score of 0.08 and earns only 6 valid recommendations across all platforms. Zoe Financial appears in 1.9% of observations, earns 2 valid recommendations, and carries a net sentiment score of 0.08. Both brands have minimal AI recommendation presence in the current benchmark snapshot.

Platform-specific patterns

The benchmark shows meaningful platform variation. Fidelity Go is strongest on Copilot. Schwab Intelligent Portfolios performs best on Google AI Overviews. Betterment and Wealthfront maintain consistent recommendation leadership across ChatGPT, Gemini, Perplexity, and Google AI Mode. Brands that perform well on only one platform carry concentration risk if that platform's behavior shifts.

Why Visibility Is Not Enough

A brand can appear in AI answers and still fail to win the buyer shortlist. The benchmark data makes this distinction concrete across multiple companies in the category.

Raw mention presence measures how often a company appears in AI responses. Valid recommendation coverage measures how often a company is actually recommended or shortlisted. These are different signals with different commercial consequences. SoFi appears in 18.3% of observations but earns a valid recommendation in only 7.6% of cases. Schwab Intelligent Portfolios appears in 24.1% of observations but earns a recommendation in only 10.2% of cases. Empower (Personal Capital) appears in 3.4% of observations but earns a single valid recommendation across 1,282 observations. Each of these brands has visibility. None has recommendation power proportionate to that visibility.

Top 3 placement matters more than general presence. Betterment achieves a Top 3 rate of 22.5% and Wealthfront achieves 22.8%. These brands are not simply appearing in AI responses. They are appearing at the top of the list, where buyer attention concentrates and where the shortlist decision is effectively made. SoFi's 4.5% Top 3 rate and Schwab's 4.5% Top 3 rate mean both brands are present in the response but rarely at the position where it matters commercially.

Rank-one placement carries the largest individual position value. Wealthfront leads the category with a 13.1% rank-one rate. In roughly one of every eight AI responses about online financial advisors, Wealthfront is the first recommendation. No other brand exceeds 6.3% at rank one. The distance between rank one and rank three is measurable. The distance between rank one and rank seven is commercially significant.

Net sentiment and framing quality determine whether a mention helps or hurts. Empower (Personal Capital) carries a net sentiment score of 0.02. Facet Wealth carries 0.15. Ellevest and Zoe Financial both carry 0.08. These brands are being mentioned in neutral or mixed contexts rather than in the positive recommending contexts that generate recommendation credit. Betterment and Wealthfront both carry net sentiment scores above 0.69, indicating that their mentions are almost always positive and forward-recommending.

Citation frequency is not endorsement. A brand can be cited as a comparison anchor, listed as an alternative, or named in a cautionary context without being recommended. The benchmark distinguishes between factual mentions and positive recommendations. Brands that appear primarily in neutral or comparison-anchor contexts are visible but not commercially effective in AI-generated buyer shortlists.

Modeled monthly AI Authority Value is a benchmark estimate. It represents the modeled value assigned to positive valid Top 3 recommendations within the category. Betterment's $1.99 million and Wealthfront's $1.74 million are benchmark values designed to surface relative competitive weight, not booked revenue or confirmed pipeline.

The Citation Layer

AI platforms build recommendations from public source evidence. The brands earning AI recommendations consistently are not necessarily the largest or most advertised brands in the category. They are the brands with the most consistent, positive, and citable public evidence across the buyer journey.

Betterment and Wealthfront appear to benefit from extensive coverage across comparison articles, editorial reviews, financial media, and official owned content. The source pattern for both brands is broad and reinforcing across buyer stages. When an AI system evaluates which robo-advisor to recommend at the consideration or decision stage, it finds multiple convergent sources supporting both brands with specific, positive, and detailed evidence.

SoFi's lower recommendation rate despite strong brand recognition may reflect a source architecture issue. SoFi appears frequently in factual references related to lending, student loan refinancing, and banking, but the advisor-specific source footprint may be thinner than its overall brand presence suggests. AI systems appear to be finding SoFi in general financial contexts more readily than in advisor-specific recommending contexts.

Empower (Personal Capital) and Facet Wealth show the clearest evidence of citation-without-endorsement patterns. Both brands appear in AI responses, but the framing is neutral rather than positive and recommending. The source material AI systems are retrieving about these brands may be factual and informational rather than comparative and favoring.

The source types that appear to shape AI answers in this category include official brand websites with detailed product and fee information, editorial reviews from financial publications, independent comparison pages that rank providers, review platforms where user ratings are aggregated, financial media coverage, and advisor-specific directory or ecosystem pages. Brands with a stronger and more consistent footprint across these source types tend to earn higher valid recommendation rates in the benchmark.

Supporting search and source visibility data was not provided in Ahrefs format for this benchmark snapshot. If organic search footprint, keyword ranking data, referring domain counts, or page-level authority signals become available, they would be incorporated as supporting evidence for the traditional search and source layer. Such data would not override the LLM Authority Index AI recommendation metrics but would help explain which public evidence channels may be contributing to or limiting each brand's AI retrieval profile.

What Brands Need to Fix

Weak valid recommendation coverage. Several brands appear in AI responses but earn recommendations at rates well below category leaders. SoFi at 7.6%, Schwab Intelligent Portfolios at 10.2%, and Empower at effectively 0% all need to improve the quality of their AI presence, not only the frequency of their mentions.

Low Top 3 and rank-one presence. SoFi and Schwab Intelligent Portfolios both achieve Top 3 rates of 4.5%. Both brands achieve rank-one rates below 4%. These brands appear in AI responses but rarely at the position where buyer shortlists are formed. Improving rank position requires more than increasing mention volume.

Absent or weak performance in decision-stage prompt clusters. Empower (Personal Capital) and Facet Wealth appear in the discovery cluster but earn effectively zero recommendations in the comparison and pricing clusters. These are the highest-intent buyer stages, and absence from them is a material commercial risk.

Neutral or cautionary framing. Empower at 0.02, Facet Wealth at 0.15, Ellevest and Zoe Financial at 0.08 are all being mentioned in contexts that do not generate recommendation credit. Improving framing quality requires building the specific types of positive, comparative, and endorsing source material that AI systems synthesize when producing shortlists.

Thin or misaligned source footprint. Brands whose broader identity spans multiple financial service categories may have source footprints that are too generalized to drive advisor-specific recommendation coverage. The public evidence layer needs to be concentrated around the specific use cases, features, fee structures, and comparisons that advisor-category buyers ask about.

Platform concentration risk. Brands that perform well on only one AI platform face concentration risk. Fidelity Go's Copilot strength and Schwab's Google AI Overviews strength are genuine assets, but they do not translate across the full platform set. A recommendation strategy that relies on a single platform creates exposure if that platform's synthesis patterns shift.

Inconsistent or incomplete entity information. Brands that appear inconsistently across platforms or that appear under multiple name variants may have fragmented entity information in the public evidence layer. Consistent, accurate, and detailed entity signals across owned and third-party sources reduce the risk of being misidentified, underweighted, or misframed in AI responses.

How CiteWorks Studio Helps

1. Map AI recommendation visibility. Track prompts, platforms, company presence, valid recommendations, Top 3 and rank-one performance, framing, and citation sources across the full buyer journey to establish a precise baseline of where the brand stands and where it is losing ground.

2. Identify the sources shaping AI answers. Find the editorial, review, forum, directory, owned, and search-visible sources that influence brand framing in AI-generated responses so the most commercially consequential source gaps become actionable.

3. Build the citation architecture plan. Strengthen the public evidence layer so AI systems have more accurate, consistent, and persuasive source material to synthesize when producing buyer shortlists in this category.

Commercial Takeaway

AI-led discovery is changing where buyer shortlists are formed in the online financial advisor category. Two brands control the majority of AI recommendation value in the current benchmark. For every other brand in the category, the path to improved AI visibility is not simply about being mentioned more often. It requires building the specific source architecture that AI systems use to justify recommendations to high-intent buyers.

Competitor displacement is a concrete risk. When an AI system recommends Betterment and Wealthfront in the top two positions, every other brand is pushed down or out. The gap between rank 3 and rank 7 is commercially meaningful. Brands outside the top three are effectively invisible to the buyer who accepts the AI shortlist as the starting point for evaluation. The benchmark shows that SoFi, Schwab Intelligent Portfolios, and Fidelity Go all have the brand recognition to be competitive but are not converting that recognition into consistent top-three recommendation credit.

The source architecture advantage that Betterment and Wealthfront currently hold is not permanent, but it is self-reinforcing. The more consistently AI systems recommend these brands, the more buyers interact with them, generate reviews, and create additional public evidence that feeds back into the retrieval layer. Brands that delay addressing their citation architecture allow that gap to compound.

The commercial opportunity for brands outside the top two is specific: improve recommendation-stage visibility at the consideration and decision stages, where buyer intent is highest and where the benchmark currently shows the largest concentration of underperformance. That is a different problem from improving general brand awareness, and it requires a different type of evidence-building strategy.

Find Out Where Your Brand Stands in AI Recommendations

The LLM Authority Index benchmark shows the category shape. A brand-specific analysis can reveal which prompts the brand wins or loses, which AI platforms are under-recognizing it, which source layers are shaping recommendations in its favor or against it, and what changes may improve its shortlist eligibility across discovery, comparison, and decision-stage queries.

CiteWorks Studio can show where your brand appears in AI-generated responses, where competitors are being recommended instead, which prompt clusters carry the most commercial risk, which sources appear to be shaping AI answers, and what needs to change to move from mention presence to recommendation credit.

To request an AI Visibility Audit, AI Company Discovery Report, or Citation Architecture Review for your brand, contact CiteWorks Studio.

Benchmark Source

This analysis is based on the 2026 AI Market Discovery Index for Online Financial Advisors, published by LLM Authority Index. The benchmark dataset and public industry report were supplied for this category. Read the full benchmark report at the LLM Authority Index.