JPMorgan Chase & Co. AI Market Strategy Report - Certificates of Deposits

Answer Capsule

JPMorgan Chase & Co. holds a mid-tier position in AI-generated certificate of deposit recommendations, with valid recommendation coverage of 8.06% in September 2026. The bank appears in 60.66% of qualified observations but converts only a fraction of that presence into actual recommendations, a visibility-to-recommendation gap that defines its current standing. Its clearest strength is recommendation placement quality, with an average recommended rank of 1.76, the strongest among all tracked brands. The clearest opportunity lies in converting its substantial neutral mention base into positive recommendation contexts across AI platforms.

Who This Report Is For

This report is for deposit product leaders, digital strategy teams, and competitive intelligence functions at JPMorgan Chase & Co. evaluating how AI systems recommend the bank in certificate of deposit discovery conversations.

Report Card

Executive Summary

JPMorgan Chase & Co. holds a visible but under-converted position in AI-generated certificate of deposit recommendations. The September 2026 benchmark shows the bank present in 60.66% of qualified observations, yet its valid recommendation coverage stands at just 8.06%. This gap between raw mention presence and actual recommendation conversion is the defining feature of the bank's current AI discovery profile.

The bank recorded 128 total mentions in September 2026, split across 34 positive, 92 neutral, and 2 negative observations. The high neutral count of 92 mentions, representing 43.60% of qualified observations, indicates the bank is frequently named as context or comparison material rather than as a recommended option. Positive mentions reached 16.11% of observations, while negative framing was minimal at 0.95%.

The strongest cluster for JPMorgan Chase & Co. is the brand recommendation cluster covering best CD rates and top certificate of deposit accounts, which captured all 211 qualified observations in the public benchmark. The bank's 17 valid recommendations all occurred within this cluster. No qualified observations were recorded in pricing and value or multi-brand comparison clusters in the public dataset.

The strongest platform signal comes from Google AI Overviews, where the bank achieved its highest recommendation-weighted visibility. The clearest platform gap appears in ChatGPT, where the bank holds presence but shows limited recommendation conversion relative to its overall profile.

The benchmark evidence suggests JPMorgan Chase & Co. is recommended when it is recommended, but it is not recommended often enough relative to its substantial presence. The bank's average recommended rank of 1.76 indicates that when AI systems do select it, they tend to place it first or second, a placement quality advantage that competitors with higher coverage do not match.

What JPMorgan Chase & Co. Is Winning

Questions This Section Answers

• What is the bank's strongest competitive advantage in AI-generated CD recommendations?
• How does the bank's placement quality compare with category leaders like Morgan Stanley and Bread Savings?

JPMorgan Chase & Co. holds the strongest recommendation placement quality in the tracked competitor set. Its average recommended rank of 1.76 is the best among all ten tracked brands, ahead of Morgan Stanley at 3.01 and Bread Savings at 3.52. This means the bank's valid recommendations land in first or second position more consistently than any competitor.

The bank also shows a narrow gap between its top-three rate of 7.58% and its rank-one rate of 4.74%, a difference of just 2.9 points. This indicates that when JPMorgan Chase & Co. earns a top-three placement, it converts to the first position at a higher rate than the category leaders. Morgan Stanley shows a 10.9 point gap between its top-three and rank-one rates, and Bread Savings shows a 12.8 point gap.

The bank recorded gains in both August and September 2026, extending its valid recommendation coverage from 5.9% in July to 8.1% in September. This consistent upward movement across the full tracked series places it among the stable risers in the category.

Where JPMorgan Chase & Co. Has the Clearest AI Visibility Gaps

Questions This Section Answers

• Why does the bank's high presence fail to convert into valid recommendations?
• Which platforms show the clearest visibility-without-recommendation pattern for the bank?
• How does the bank's neutral mention rate compare with competitors that hold similar presence?

The clearest gap is the conversion of raw presence into valid recommendations. JPMorgan Chase & Co. appears in 60.66% of qualified observations but is recommended in only 8.06%. This means the bank is named frequently but selected infrequently, a pattern that suggests AI systems treat it as a reference point rather than a preferred option.

The neutral mention count of 92 observations, or 43.60% of the qualified set, is the highest neutral share among the top five brands by coverage. Bread Savings, by contrast, holds a neutral rate of just 4.27% and converts 72 of its 81 mentions into positive observations. The comparison suggests JPMorgan Chase & Co. is being described without evaluative framing, while competitors are being positioned with positive recommendation language.

ChatGPT represents a specific platform gap. The bank holds a 52.94% raw mention presence rate on that platform but records only one valid recommendation from 17 observations. Google AI Mode shows a similar pattern, with 43.48% presence but only one valid recommendation. These platforms contribute to the bank's substantial mention base without converting that presence into recommendation credit.

The bank's rank-one rate of 4.74% trails Morgan Stanley at 10.43% and Bread Savings at 4.27% when adjusted for their higher coverage levels. While JPMorgan Chase & Co. converts its top-three placements to rank one at a strong rate, it simply does not earn enough top-three placements to challenge the category leaders.

Biggest Opportunity

Questions This Section Answers

• Where does the bank's largest untapped recommendation potential sit?
• How could the bank's placement quality amplify gains from a modest increase in valid recommendations?

The clearest opportunity for JPMorgan Chase & Co. is converting its substantial neutral mention base into positive recommendation contexts. The bank is already present in AI responses at a rate comparable to the category leaders, but it is not being framed as a recommended option. The 92 neutral mentions represent the single largest pool of untapped recommendation potential in the bank's profile.

This opportunity is most actionable in the brand recommendation cluster, where all qualified observations currently sit. The bank's strong placement quality, evidenced by its 1.76 average recommended rank, means that even a modest increase in valid recommendation count could produce outsized gains in top-three and rank-one positioning. The path runs through the prompt, page, and citation layers that shape how AI systems frame the bank when it appears in CD discovery answers.

Competitive Landscape

Questions This Section Answers

• Where does JPMorgan Chase & Co. rank against competitors in valid recommendation coverage?
• Which competitors hold the dominant recommendation-stage positions in this category?

Morgan Stanley and Bread Savings hold the dominant recommendation-stage positions in the certificates of deposits category, with valid recommendation coverage of 32.70% and 29.86% respectively. JPMorgan Chase & Co. sits in fourth position at 8.06%, behind Goldman Sachs Group at 12.32%, with a placement quality advantage that its higher-coverage competitors do not match.

Average recommended rank covers rank-eligible recommendations only.

The table shows JPMorgan Chase & Co. holding the strongest average recommended rank in the category at 1.76, ahead of Bank of America Corp. at 2.85 and Morgan Stanley at 3.01. However, the bank's top-three rate of 7.58% trails Morgan Stanley by 13.75 points and Bread Savings by 9.48 points, reflecting a lower volume of recommendation placements despite superior placement quality when those placements occur.

Prompt Evidence

Gemini / Brand Recommendation Prompt: "Which bank currently has the best savings account?" Result: JPMorgan Chase & Co. appeared among the recommended options with a rank-one rate of 9.43% on this platform, its strongest single-platform rank-one performance.

Google AI Overviews / Brand Recommendation Prompt: "What is the highest CD rate right now?" Result: The bank recorded its highest recommendation-weighted visibility on this platform, with 3 valid recommendations from 54 observations and a rank-one rate of 3.70%.

ChatGPT / Brand Recommendation Prompt: "Who is offering the highest CD rates right now?" Result: JPMorgan Chase & Co. held a 52.94% presence rate but earned only one valid recommendation, a pattern of visibility without recommendation conversion.

What CiteWorks Studio Would Do Next

Phase 1: AI Market Discovery Audit Map the specific prompt themes within CD discovery where JPMorgan Chase & Co. appears as neutral context rather than as a recommended option, identifying the highest-intent questions where the bank is present but not selected.

Phase 2: Recommendation Readiness Plan Build a conversion strategy targeting the 92 neutral mentions, prioritizing the prompt clusters and platforms where the bank already holds strong presence and can most efficiently convert that presence into recommendation credit.

Phase 3: Owned Answer Layer Buildout Develop owned content that gives AI systems clear, structured information about the bank's CD products, terms, and rate positioning, reducing reliance on third-party descriptions that may frame the bank neutrally.

Phase 4: Citation / Authority Layer Development Strengthen the external source footprint that supports positive recommendation framing, focusing on the evidence sources that AI systems appear to synthesize when they recommend competitors instead of JPMorgan Chase & Co.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track the bank's presence-to-recommendation conversion rate monthly, measuring whether neutral mentions shift toward positive recommendation contexts and whether placement quality holds as recommendation volume grows.

Why This Matters

AI-generated recommendations are becoming the default starting point for consumers evaluating certificate of deposit options. When a bank appears in 60.66% of AI responses but is recommended in only 8.06%, it is being seen but not chosen. The distinction matters because presence without recommendation does not influence where recommendations are formed.

The next move for JPMorgan Chase & Co. is targeted correction of the prompt, page, and citation layers that determine whether its substantial AI presence converts into recommendation credit. The bank already wins on placement quality when it is recommended. The task is to earn more of those recommendation moments.

Core Metrics

Sentiment Score

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

For JPMorgan Chase & Co., the calculation is (34 × 1 + 92 × 0 + 2 × -1) / 128, producing a net sentiment score of 0.25.

This score matters because unclassified mention counts are misleading. A raw mention total of 128 says nothing about whether the bank is being recommended, referenced neutrally, or framed negatively. Share of voice is a diagnostic metric, not a business KPI. A positive recommendation, neutral reference, cautionary mention, and competitor-displaced mention are not equal. Counting all mentions as wins is bad measurement. Classified sentiment is required before interpreting AI visibility, because the same presence rate can reflect radically different recommendation outcomes.

Sentiment by Platform

Methodology

1. This report is a company-level AI market strategy readout based on the LLM Authority Index AI Market Discovery Index for the certificates of deposits vertical, not a client implementation case study.
2. The reporting window is September 2026, with July and August 2026 referenced for movement context where the public benchmark provides historical values.
3. Six AI and search surface families were tracked: ChatGPT, Copilot, Gemini, Perplexity, Google AI Mode, and Google AI Overviews.
4. The benchmark collected 800 prompt-surface observations in September 2026, of which 658 were unique questions after de-duplication.
5. All 800 collected prompts mentioned a tracked brand or competitor; 251 were relevant to the certificates of deposits vertical and 549 were irrelevant.
6. The public benchmark qualified 211 observations for brand-level percentage calculations, down from the raw collection universe by design.
7. The competitor universe includes 10 tracked brands: Bread Savings, American Express Co., Bank of America Corp., Capital One Financial Corp., Citigroup Inc., Goldman Sachs Group, JPMorgan Chase & Co., Morgan Stanley, U.S. Bancorp, and Wells Fargo & Co.
8. One public high-intent cluster captured all qualified observations in September 2026: Best CD Rates & Top Certificate of Deposit Accounts, classified under the brand recommendation buyer-intent class.
9. A mention is defined as any qualified observation where the tracked brand appears in any form, regardless of recommendation context.
10. A valid recommendation is defined as a qualified observation where the brand appears in a positive recommendation context with a rank of 1 through 10.
11. The public benchmark does not yet contain qualified observations in the pricing and value or multi-brand comparison buyer-intent classes, limiting analysis of rate competitiveness and head-to-head comparisons.
12. Movement between months identifies changes worth investigating; it does not by itself establish what caused those changes. Source presence in the evidence layer is not automatically proof that the source caused the recommendation.

See How AI Is Recommending Your Brand

The public benchmark shows where JPMorgan Chase & Co. stands in AI-generated certificate of deposit recommendations, but the aggregate percentages hide the prompt-level patterns that determine competitive position. A company-level AI visibility audit maps the specific questions, platforms, competitor displacements, and evidence sources behind the bank's recommendation outcomes, turning the benchmark signal into an actionable diagnosis of where the bank wins, where it loses, and what is driving each result.