Fidelity AI Visibility Market Strategy Report - Roth IRAs

Answer Capsule

Fidelity holds dominant recommendation power in the Roth IRAs category, leading AI-generated recommendations in October 2026 with a 90.35% valid recommendation coverage rate across 518 qualified observations. The benchmark shows Fidelity is recommended first in 57.92% of qualified answers, a rank-one rate no competitor approaches. Its clearest weakness is a narrow 0.9-point coverage lead over Charles Schwab, which converts far less of its presence into first-choice placement. The clearest opportunity sits in correcting a high-severity factual inconsistency about total client assets that appears across Copilot and AI Overviews.

Who This Report Is For

This report is for Fidelity's marketing, digital strategy, and competitive intelligence teams, and for category analysts tracking how AI systems recommend retirement account providers at the buyer shortlist stage.

Report Card

Executive Summary

Fidelity holds dominant recommendation power in the Roth IRAs category. The benchmark shows 90.35% valid recommendation coverage in October 2026, up 3.8 points from 86.5% in July 2026, and a raw mention presence rate of 99.61%. Fidelity has held the coverage lead in every month of the series.

The company's strongest signal is placement quality, not just presence. Fidelity's top-three rate rose 22.8 points to 86.10%, and its rank-one rate rose 8.4 points to 57.92%. That rank-one figure means Fidelity is the primary recommendation in more than half of all qualified answers, a level no other tracked brand approaches. Charles Schwab, the nearest competitor by coverage at 89.4%, holds a rank-one rate of 23.36%.

The clearest gap is competitive proximity at the top. Fidelity and Charles Schwab are separated by 0.9 points in coverage but 34.56 points in rank-one rate, so near-identical coverage hides very different first-choice strength. Charles Schwab also posted the larger coverage gain this period, up 5.9 points against Fidelity's 3.8 points.

Platform performance is broadly strong but uneven. Fidelity's highest rank-one rates appear on Copilot (69.41%), ChatGPT (64.00%), and AI Mode (59.7%). Its lowest rank-one rate among tracked platforms is Gemini at 39.0%, where coverage sits at 65.9%, well below the company's category average.

Sentiment is strongly positive. Fidelity recorded 472 positive mentions, 39 neutral mentions, and 5 negative mentions across 516 present observations, producing a net sentiment score of 0.9050. The five negative mentions are the only cautionary framing in the dataset.

One high-severity factual inconsistency was detected. AI platforms provided conflicting information about Fidelity's total client assets, with Google AI Overviews stating over $7 trillion and Copilot stating $18.0 trillion, both in response to the same question about top stock brokerage firms.

The clearest opportunity is correcting that factual conflict and strengthening the source layer that AI systems retrieve when describing Fidelity's scale. Fidelity's own domain, fidelity.com, is the only tracked brand domain in the top 10 cited domains, appearing at rank 10 with 196 citations and a 3.2% share.

What Fidelity Is Winning

Questions This Section Answers

• Where does Fidelity hold the strongest recommendation position in the Roth IRAs category?
• Which AI platforms convert Fidelity's presence into first-choice recommendations most often?
• How does Fidelity's rank-one rate compare with its nearest competitors?

Fidelity's wins are broad and evidence-backed.

The strongest cluster is Brand Recommendation, the only cluster with sufficient coverage in the October 2026 benchmark. Fidelity leads it with 90.35% valid recommendation coverage, 86.10% top-three rate, and 57.92% rank-one rate.

The strongest platform by recommendation behavior is Copilot, where Fidelity holds a 69.41% rank-one rate and a 90.6% valid recommendation coverage rate across 85 observations. ChatGPT follows closely with a 64.00% rank-one rate and 98.0% coverage across 50 observations.

Fidelity also shows the strongest first-position conversion in the category. Its 57.92% rank-one rate is more than double Charles Schwab's 23.36% and more than twenty times Vanguard's 2.32%.

Negative framing is minimal. Only 5 of 516 present observations carried negative sentiment, a negative visibility rate of 0.97%.

Fidelity's own domain appears in the citation layer. fidelity.com ranks 10th among cited domains with 196 citations and a 3.2% share, cited across ChatGPT, Copilot, Gemini, AI Mode, AI Overviews, and Perplexity.

Where Fidelity Has the Clearest AI Visibility Gaps

Questions This Section Answers

• How close is Charles Schwab to Fidelity's coverage lead, and is the gap widening?
• Why is Gemini Fidelity's weakest platform for Roth IRA recommendations?
• Why is Fidelity's recommendation strength not matched by its citation share?

Fidelity's gaps are narrow but consequential.

The clearest gap is competitive proximity. Charles Schwab closed the coverage gap to 0.9 points in October 2026, up from 3.0 points in July 2026. Charles Schwab also posted the larger coverage gain this period, up 5.9 points against Fidelity's 3.8 points, and its top-three rate rose 27.4 points against Fidelity's 22.8 points. Fidelity still leads on rank-one rate by a wide margin, but the coverage lead is narrowing.

The second gap is platform-level. Gemini is Fidelity's weakest tracked platform by rank-one rate at 39.0%, with valid recommendation coverage of 65.9% across 41 observations. That coverage rate sits well below Fidelity's category average of 90.35% and below its performance on every other tracked platform.

The third gap is the citation layer. Only one tracked brand domain, fidelity.com, appears in the top 10 cited domains, and it ranks last at 3.2% share. The top 10 domains account for 47.9% of all citations, and the leading domains are third-party review and comparison sites: nerdwallet.com at 9.2%, investopedia.com at 6.5%, and youtube.com at 5.6%. Fidelity's recommendation strength is not matched by citation share.

The fourth gap is factual consistency. A high-severity conflict about Fidelity's total client assets appears across Copilot and AI Overviews, with the two platforms citing different figures from different sources.

Biggest Opportunity

Questions This Section Answers

• What factual conflict about Fidelity's total client assets appears across Copilot and AI Overviews?
• Where does the total client assets conflict originate, and why does scale matter for Roth IRA buyers?

The single biggest opportunity is correcting the total client assets inconsistency and strengthening the source layer that AI systems retrieve when describing Fidelity's scale.

The conflict is specific and traceable. When asked "What are the top stock brokerage firms?", Google AI Overviews stated Fidelity manages over $7 trillion in assets, citing Investopedia, while Copilot stated total client assets of $18.0 trillion, citing The Motley Fool. Both platforms cited the same Motley Fool page among their sources, which suggests the discrepancy originates in how each platform synthesized or retrieved the figure rather than in a single conflicting source.

This matters because scale is a primary trust signal in retirement account selection. A buyer comparing Roth IRA providers at the recommendation stage may see two different asset figures from two different AI platforms in the same research session. Correcting the underlying source layer, and ensuring Fidelity's own authoritative pages state the figure clearly and consistently, is the clearest path from reference to confident recommendation.

Competitive Landscape

Questions This Section Answers

• Where do Fidelity and Charles Schwab separate on top-three and rank-one rates?
• How far ahead is Fidelity's rank-one rate compared with every other tracked Roth IRA provider?

Fidelity holds the strongest recommendation-stage position in the Roth IRAs category, leading on both top-three rate and rank-one rate. Charles Schwab is the strongest challenger, with coverage nearly matching Fidelity's but first-choice strength far behind.

Average recommended rank covers rank-eligible recommendations only.

Fidelity's position at the top of the table is earned on both placement metrics. Its 86.10% top-three rate leads the category by 5.6 points over Charles Schwab, and its 57.92% rank-one rate leads by 34.56 points. The gap between Fidelity and Charles Schwab on coverage is narrow, but the gap on first-choice placement is wide.

AI Response Inconsistency Alerts

Questions This Section Answers

• What conflicting figures do Copilot and Google AI Overviews state for Fidelity's total client assets?
• Which sources does each platform cite for the conflicting total client assets figures?
• Why does the discrepancy appear to reflect synthesis rather than a single conflicting source?

One critical factual inconsistency was detected for Fidelity across two AI platforms, Copilot and Google AI Overviews.

The conflict concerns Fidelity's total client assets and carries high severity with 0.9 confidence. When asked "What are the top stock brokerage firms?", Google AI Overviews stated that Fidelity "manages over $7 trillion in assets," citing Investopedia, the New York Institute of Finance, and The Motley Fool. Copilot, answering the same question, stated that Fidelity has "total client assets of $18.0 trillion," citing The Motley Fool, The College Investor, and BrokerChooser. The two figures cannot both be correct.

The flagged sources show where each side of the conflict originates. The Investopedia page cited by Google AI Overviews states that "Fidelity Investments had $7.1 trillion under management and 57 million active accounts." The Motley Fool page cited by Copilot states that "Fidelity administers $18.0 trillion, making it the largest by total client assets." Both flagged excerpts carry 0.95 confidence.

The notable detail is that The Motley Fool page appears in both platforms' source lists. Google AI Overviews cited it alongside Investopedia and the New York Institute of Finance, while Copilot cited it alongside The College Investor and BrokerChooser. The discrepancy appears to reflect how each platform selected and synthesized the figure rather than a single source conflict, since the same Motley Fool page is present on both sides.

Prompt Evidence

Google AI Overviews / Brand Recommendation Prompt: "What are the top stock brokerage firms?" Result: Fidelity was recommended in the top three with a stated figure of over $7 trillion in assets, citing Investopedia.

Copilot / Brand Recommendation Prompt: "What are the top stock brokerage firms?" Result: Fidelity was recommended with a stated figure of $18.0 trillion in total client assets, citing The Motley Fool, creating a factual conflict with the AI Overviews response.

Gemini / Brand Recommendation Prompt: "What is the best Roth IRA to open?" Result: Fidelity appeared with a 65.9% valid recommendation coverage rate on Gemini, its lowest among tracked platforms, and a 39.0% rank-one rate.

ChatGPT / Brand Recommendation Prompt: "What is the best app to start investing on?" Result: Fidelity was recommended first in 64.00% of ChatGPT observations, its second-strongest platform by rank-one rate.

What CiteWorks Studio Would Do Next

Phase 1: AI Visibility Market Discovery Audit Map every prompt where Fidelity is recommended, the placement it receives, and the sources AI systems cite for each answer, with priority on the total client assets conflict.

Phase 2: Recommendation Readiness Plan Prioritize the Gemini coverage gap and the narrowing Charles Schwab coverage lead, and define which prompt clusters need correction first.

Phase 3: Owned Answer Layer Buildout Strengthen Fidelity's own pages so the authoritative asset figure, account details, and Roth IRA positioning are stated clearly and consistently for retrieval.

Phase 4: Citation / Authority Layer Development Address the citation gap where only fidelity.com appears in the top 10 cited domains, and reduce reliance on third-party pages that carry conflicting figures.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track coverage, top-three rate, rank-one rate, and factual consistency month over month across all six platforms.

Why This Matters

AI presence alone is not enough. Fidelity already appears in 99.61% of qualified answers, yet the benchmark shows that presence and recommendation strength are separate signals. A brand can be mentioned in nearly every answer and still lose the first-choice position, and a brand can hold the coverage lead while a competitor closes the gap month over month.

The next move is targeted correction of the prompt, page, and citation layers. Fidelity's rank-one strength is real and well supported, but the narrowing coverage lead, the Gemini gap, and the total client assets conflict all point to specific, fixable weaknesses in how AI systems retrieve and synthesize Fidelity's information. Correcting those layers protects the recommendation position that the benchmark shows Fidelity currently holds.

Core Metrics

Sentiment Score

Questions This Section Answers

• How is Fidelity's sentiment score calculated from positive, neutral, and negative mentions?
• Why is classified sentiment more useful than a raw AI mention total for the Roth IRAs category?

Sentiment Score = (positive mentions × 1 + neutral mentions × 0 + negative mentions × -1) / total mentions

For Fidelity in October 2026: (472 × 1 + 39 × 0 + 5 × -1) / 516 = 467 / 516 = 0.9050.

This matters because unclassified mention counts are misleading. A raw mention total treats a strong recommendation, a neutral reference, a cautionary note, and a competitor-displaced mention as equal, when they are not. Share of voice is a diagnostic metric, not a business KPI. Counting every mention as a win is bad measurement.

Fidelity's 0.9050 score reflects a framing profile that is overwhelmingly positive, with only 5 negative mentions across 516 present observations. Classified sentiment is required before interpreting AI visibility, because it separates genuine recommendation strength from simple presence.

Sentiment by Platform

Methodology

1. This report is a benchmark-based analysis of Fidelity's AI recommendation position in the Roth IRAs category, not a client result.
2. The reporting month is October 2026, with comparison points from July 2026, August 2026, and September 2026.
3. Six AI and search platforms were tracked: ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode.
4. The October 2026 benchmark produced 518 qualified observations from 800 source prompt-surface observations and 619 unique questions.
5. Ten companies were tracked in the category universe: Fidelity, Charles Schwab, Robinhood, Vanguard, E*TRADE, SoFi, Betterment LLC, Merrill Edge, Wealthfront Corporation, and M1 Finance.
6. One public high-intent cluster had sufficient coverage in October 2026: Brand Recommendation. Pricing and Value and Multi-Brand Comparison clusters had no qualified observations.
7. Stage 0 extraction retained the query, platform, answer, brand outcome, recommendation placement, sentiment, and citations where exposed.
8. A mention is any qualified observation where Fidelity appears, regardless of recommendation status.
9. A valid recommendation is a qualified observation where Fidelity appears in a valid recommendation shortlist, as marked by the dataset.
10. Brand-level percentages use the 518 qualified observations as the public denominator, not the 800 raw prompts collected.
11. Average recommended rank covers rank-eligible recommendations only, and Fidelity's 1.39 average reflects 468 valid recommendations.
12. Entity labels changed within the series: Betterment, Betterment LLC, Wealthfront, and Wealthfront Corporation appear as distinct series, and the zero readings on the original labels coincide with the first appearances of the new labels in October 2026.

See How AI Is Recommending Your Brand

The public benchmark shows where Fidelity stands in AI recommendations across the Roth IRAs category. A company-level AI visibility audit maps the specific prompts, competitors, platforms, and sources behind that position, including the factual conflicts and citation gaps that category-level percentages cannot expose.