Fidelity AI Market Strategy Report - IRAs

Answer Capsule

Fidelity holds the strongest rank position in the IRA category, earning a 29.3% Rank 1 rate and an average recommended rank of 1.30, meaning when AI systems recommend Fidelity, they almost always place it first. Fidelity captured $1.2M in modeled monthly AI Authority Value, placing it second overall behind Charles Schwab. The clearest win is Fidelity's net sentiment score of 0.90, the highest in the measured universe, indicating AI systems frame Fidelity positively nearly every time it appears. The clearest weakness is that Fidelity's overall recommendation coverage rate of 38.8% trails Charles Schwab's 57.9%, meaning Schwab appears in more shortlists overall. The clearest opportunity is converting Fidelity's strong rank position into broader recommendation coverage across all buyer stages and platforms.

Who This Report Is For

This report is for IRA and brokerage marketing, product, and strategy leaders at Fidelity who need to understand how AI systems are recommending the brand versus competitors in buyer-facing discovery, comparison, and pricing decisions.

Report Card

• Report type: AI Company Market Strategy Report
• Target company: Fidelity
• Category / market studied: IRAs and brokerage/investment platform discovery
• Reporting month: June 2026
• AI platforms tracked: ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity
• Public high-intent clusters: 3 (Discovery, Comparison, Pricing and Fees)
• AI observations analyzed: 1,497
• Competitors tracked: Charles Schwab, Vanguard, Robinhood, Betterment, SoFi, Wealthfront, M1 Finance, E*TRADE, Merrill Edge

Executive Summary

Fidelity holds the strongest recommendation rank position in the IRA category. Across 1,497 observations, Fidelity appeared in 46.8% of all AI responses and earned 582 valid recommendations, a 38.8% recommendation coverage rate. When AI systems recommend Fidelity, they place it first 29.3% of the time, with an average recommended rank of 1.30. No other provider in the measured universe achieves a lower average rank.

Fidelity's net sentiment score of 0.90 is the highest among all ten tracked providers. AI systems frame Fidelity positively in nearly every appearance, with only 71 neutral mentions and zero negative mentions out of 700 total appearances. This framing quality is a significant competitive advantage in a category where trust and credibility drive buyer decisions.

The strongest cluster for Fidelity is Brokerage and Investment Platform Comparisons, where it achieved a 38.9% Top 3 rate and a 30.6% Rank 1 rate. The strongest platform signal is on Copilot, where Fidelity achieved a 63.9% Top 3 rate and a 52.2% Rank 1 rate, the highest platform-level performance for any provider in the category.

The clearest gap is overall recommendation coverage. Charles Schwab appears in 73.9% of responses and earns a 57.9% recommendation coverage rate, compared to Fidelity's 46.8% presence and 38.8% coverage. Schwab's $2.1M in modeled monthly AI Authority Value is nearly double Fidelity's $1.2M. Fidelity wins on rank position when recommended, but Schwab wins on breadth of recommendation across more prompts and platforms.

The gap between Fidelity's rank strength and Schwab's coverage breadth defines the central strategic challenge for the brand in AI-led IRA discovery. Fidelity's core recommendation signal is high quality. The volume of retrieval is not yet matching that quality across all platforms.

What Fidelity Is Winning

Strongest rank position in the category. Fidelity's average recommended rank of 1.30 is the best in the measured universe. When AI systems include Fidelity in a shortlist, they place it first more often than any competitor. This is the most valuable position in AI-generated buyer shortlists.

Highest net sentiment score. Fidelity's net sentiment score of 0.90 is the highest among all ten providers. AI systems frame Fidelity positively in 89.9% of its appearances. This framing quality signals trust and credibility to buyers at the moment of decision.

Dominant performance on Copilot. On Microsoft Copilot, Fidelity achieved a 63.9% Top 3 rate and a 52.2% Rank 1 rate. Fidelity appears in 76.1% of Copilot responses and earns recommendation credit in 64.8% of them. This is the strongest platform-level performance for any provider in the category.

Strong performance on Perplexity. Fidelity achieved a 61.0% Top 3 rate and a 45.6% Rank 1 rate on Perplexity, with a 97.2% net sentiment score on that platform. Perplexity users see Fidelity as the top recommendation in nearly half of all responses.

Zero negative framing across all platforms. Fidelity received zero negative mentions across all 1,497 observations. This is a rare signal in a category where several competitors carry cautionary or negative framing in parts of the dataset.

Where Fidelity Has the Clearest AI Visibility Gaps

Overall recommendation coverage trails Charles Schwab. Fidelity's 38.8% valid recommendation coverage rate is solid but meaningfully below Schwab's 57.9%. Schwab appears in 73.9% of all responses compared to Fidelity's 46.8%. The gap is most pronounced in awareness-stage prompts, where Schwab appears in 73.7% of responses versus Fidelity's 43.6%.

Weak presence on ChatGPT. Fidelity appears in only 7.0% of ChatGPT responses, the lowest platform presence for the brand. While Fidelity achieves a strong average rank of 1.0 when recommended on ChatGPT, the total recommendation count is only 16 out of 256 observations. This is a significant gap on the most widely used AI platform.

Google AI Mode underperformance. Fidelity appears in only 18.1% of Google AI Mode responses, compared to Schwab's 97.2% and Vanguard's 71.8%. Fidelity's rank position on Google AI Mode is strong at 1.43, but the low presence rate means the brand is absent from a large volume of AI-generated responses on a platform that is growing in commercial relevance.

Comparison cluster is Schwab's strongest territory. In the Brokerage and Investment Platform Comparisons cluster, Schwab achieves a 54.1% Top 3 rate versus Fidelity's 38.9%. Schwab's modeled captured value in this cluster is nearly double Fidelity's $408K. This is the cluster where buyer decisions are formed, and Schwab holds a commanding lead in AI recommendation volume at that stage.

Pricing and Fees cluster rank position has room to improve. Fidelity leads the Pricing and Fees cluster with a 36.3% Top 3 rate and a 29.7% Rank 1 rate. However, the average recommended rank in this cluster is 1.30, slightly above the Discovery cluster's 1.24. Given Fidelity's reputation for transparent pricing, a stronger rank position in this decision-stage cluster is a reasonable and achievable target.

Biggest Opportunity

The clearest path for Fidelity is converting its strong rank position into broader recommendation coverage on ChatGPT and Google AI Mode. Fidelity wins when it is recommended, but it is not being recommended often enough on the highest-volume AI platforms. These two platforms together represent a significant share of buyer-facing AI discovery traffic, and Fidelity's presence rate on both is well below its performance on Copilot and Perplexity. The path forward is to strengthen the public evidence layer that AI systems retrieve when constructing shortlists on these platforms, ensuring Fidelity appears in more responses while maintaining the rank position and positive sentiment it achieves where it is already strong.

Prompt Evidence

Copilot / Brokerage and Investment Platform Comparisons Prompt: "Compare Fidelity vs Charles Schwab for IRA investing" Result: Fidelity was recommended first with a 1.0 average rank, cited for low fees and strong customer service.

Perplexity / Best Brokerage and Investment Platform Discovery Prompt: "What is the best brokerage for retirement accounts?" Result: Fidelity ranked first in a shortlist of three providers, with positive framing around fee structure and investment options.

ChatGPT / Brokerage and Investment Platform Pricing and Fees Prompt: "Which IRA provider has the lowest fees?" Result: Fidelity was mentioned but not ranked in the top three. Charles Schwab and Vanguard received the primary recommendation positions in this response.

Google AI Mode / Brokerage and Investment Platform Comparisons Prompt: "Compare Vanguard and Fidelity for IRA fees" Result: Fidelity appeared in the response but was listed after Vanguard in the comparison, with a second-position rank in this cluster observation.

What CiteWorks Studio Would Do Next

Phase 1: AI Market Discovery Audit Map Fidelity's current recommendation coverage across all six platforms and three buyer stages to identify the specific prompts and platforms where presence is weakest, with priority on ChatGPT and Google AI Mode gaps.

Phase 2: Recommendation Readiness Plan Build a targeted plan to improve Fidelity's retrieval frequency on ChatGPT and Google AI Mode by identifying the source and framing gaps that limit presence on these platforms despite strong rank performance elsewhere.

Phase 3: Owned Answer Layer Buildout Develop structured content on Fidelity's owned properties that AI systems can reliably retrieve for fee comparison, investment options, and customer experience prompts at the comparison and pricing stages.

Phase 4: Citation and Authority Layer Development Expand Fidelity's citation footprint in financial media, comparison articles, and review platforms to increase the volume of authoritative sources AI systems can synthesize when constructing IRA shortlists.

Phase 5: Monthly AI Visibility and Recommendation Tracking Monitor Fidelity's recommendation coverage, rank position, and sentiment across all platforms and clusters on a monthly basis to measure progress against the ChatGPT and Google AI Mode gaps and maintain performance on Copilot and Perplexity.

Why This Matters

Fidelity holds the strongest recommendation rank position in the IRA category and the highest sentiment score in the measured universe. But rank position alone does not determine how many buyers see Fidelity in a shortlist. Charles Schwab's broader recommendation coverage means Schwab appears in more AI-generated shortlists across more prompts and platforms. Buyers who ask AI systems for IRA recommendations see Schwab more often, even in prompts where Fidelity would rank first if it appeared.

The gap is not in quality of recommendation. It is in breadth of retrieval. Fidelity needs to appear in more AI responses while maintaining its high rank position and positive framing. The brands that win in AI-led discovery are the brands that AI systems can retrieve, verify, and surface across every buyer stage and platform. Fidelity has the trust signal and the rank quality. The next move is to expand the retrieval signal on the platforms where the gap is largest.

Core Metrics

• Mentions: 700
• Valid recommendations: 582
• Top 3 recommendation count: 533
• Rank 1 recommendation count: 439
• Average recommended rank: 1.30
• Positive mentions: 629
• Neutral mentions: 71
• Negative mentions: 0
• Raw mention presence rate: 46.8%
• Valid recommendation coverage: 38.8%
• Top 3 recommendation rate: 35.6%
• Rank 1 recommendation rate: 29.3%
• Strongest cluster by recommendation behavior: Brokerage and Investment Platform Comparisons (38.9% Top 3 rate)
• Strongest platform by recommendation behavior: Copilot (63.9% Top 3 rate, 52.2% Rank 1 rate)

Sentiment Score

Sentiment Score = (629 positive x 1) + (71 neutral x 0) + (0 negative x -1) / 700 total mentions = 0.90

Fidelity's net sentiment score of 0.90 is the highest in the measured universe. This means AI systems frame Fidelity positively in nearly every appearance.

Unclassified mention counts would be misleading here because they would treat Fidelity's 700 appearances as equivalent to a competitor with 700 appearances but significantly lower framing quality. Share of voice is a diagnostic metric, not a business KPI. A positive recommendation, a neutral reference, a cautionary mention, and a competitor-displaced mention are not equal signals. Counting all appearances as wins is bad measurement and leads to strategies that optimize for the wrong outcome.

Classified sentiment is required before interpreting AI visibility. Fidelity's score of 0.90 confirms that when the brand appears in AI responses, it appears in a positive, recommendation-ready context. The strategic question is not about protecting framing quality. It is about extending the reach of that framing to more prompts and more platforms.

Sentiment by Platform

Methodology

1. Market studied: IRAs and brokerage/investment platform discovery, comparison, and pricing decisions, covering retail investors at the awareness, consideration, and decision stages of the buyer journey.
2. Brands tracked: Charles Schwab, Fidelity, Vanguard, Robinhood, Betterment, SoFi, Wealthfront, M1 Finance, E*TRADE, and Merrill Edge. This is not a full market census. Additional providers operating in the IRA category were not included in this benchmark universe.
3. Data collection window: June 2026, snapshot-based measurement. AI platform outputs can change over time and this report reflects conditions at the time of data collection.
4. AI platforms tested: ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, and Perplexity.
5. Observation count: 1,497 total observations analyzed across three high-intent clusters. Unique prompt count was not available in the public version of this benchmark.
6. Prompt clusters: Awareness (Best Brokerage and Investment Platform Discovery), Consideration (Brokerage and Investment Platform Comparisons), and Decision (Brokerage and Investment Platform Pricing and Fees).
7. Definition of a mention: A mention is recorded when a company name appears anywhere 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 appearance in which the company receives explicit recommendation credit or a ranked shortlist position. Neutral references, cautionary mentions, and competitor-displaced appearances are not counted as valid recommendations.
9. Metrics used: Valid recommendation coverage, Top 3 recommendation rate, Rank 1 recommendation rate, average recommended rank, net sentiment score, and modeled monthly AI Authority Value. Modeled AI Authority Value is a benchmark estimate and is not revenue, pipeline, or booked demand.
10. Sentiment scoring: Net sentiment score is calculated as (positive mentions x 1 + neutral mentions x 0 + negative mentions x -1) divided by total mentions. This is a framing quality signal, not a measure of customer satisfaction.
11. Ahrefs and traditional search data: No Ahrefs or organic search data was supplied for this report. Traditional search metrics are not used as AI recommendation proxies in CiteWorks Studio methodology.
12. Limitations: This is a point-in-time benchmark based on a defined provider universe, a defined cluster set, and a defined platform set. Results reflect the public evidence layer available to AI systems at the time of measurement. The public version of this benchmark includes three of the ten measured clusters. AI recommendation behavior varies by prompt phrasing, platform version, and retrieval conditions.

See How AI Is Recommending Your Brand

The IRA category benchmark shows that AI-generated shortlists are already shaping buyer decisions across discovery, comparison, and pricing prompts, and that recommendation coverage, rank position, and framing quality vary significantly by brand, platform, and cluster. Fidelity's strong rank position and sentiment score are meaningful advantages, but the ChatGPT and Google AI Mode gaps represent measurable exposure at scale. An AI visibility audit can show exactly which prompts are driving the coverage gap, which sources are shaping AI answers on those platforms, and what changes to the owned and citation layers would close the distance between Fidelity's current retrieval volume and the rank quality it achieves when it does appear.