Kaspersky AI Market Strategy Report - Antivirus Software

Answer Capsule

Kaspersky appears in 20.4% of AI observations across the antivirus software category but earns a valid recommendation in only 8.4% of cases, revealing a significant gap between visibility and recommendation power. The brand carries the lowest net sentiment score among tracked competitors at 0.45, driven by 45 negative mentions across 1,434 observations. Kaspersky performs best on Perplexity with 25.9% recommendation coverage, but struggles on Google platforms where negative framing is most pronounced. The clearest opportunity lies in addressing the sentiment headwinds that suppress recommendation conversion, particularly on Google AI Mode and Gemini.

Who This Report Is For

This report is for Kaspersky marketing, product, and brand strategy leaders responsible for AI-led buyer discovery, competitive positioning, and shortlist eligibility in the antivirus software category.

Report Card

• Report type: AI Company Market Strategy Report
• Target company: Kaspersky
• Category / market studied: Antivirus Software
• Reporting month: June 2026
• AI platforms tracked: ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity
• Public high-intent clusters: 3 (Best Antivirus and Security Software Discovery, Antivirus Software Comparison and Alternatives, Antivirus Software Pricing and Plans Evaluation)
• AI observations analyzed: 1,434
• Competitors tracked: Bitdefender, Norton, Malwarebytes, ESET, Avast, McAfee, AVG, Trend Micro, Webroot

Executive Summary

Kaspersky holds moderate visibility across AI platforms, appearing in 20.4% of all observations, but the benchmark data reveals a structural weakness in recommendation conversion. The brand earns a valid recommendation in only 8.4% of cases, meaning that in the majority of AI responses where Kaspersky appears, it surfaces as a neutral reference or cautionary mention rather than a recommended option.

The net sentiment score of 0.45 is the lowest in the category, driven by 45 negative mentions against 175 positive and 72 neutral mentions. This sentiment drag is concentrated on Google platforms: Kaspersky achieves a net sentiment score of negative 0.11 on Google AI Mode and 0.06 on Google AI Overviews. On Gemini, the score drops to negative 0.53, the most negative platform-level sentiment in the entire dataset.

Kaspersky performs best on Perplexity, where it achieves 25.9% recommendation coverage and a net sentiment score of 0.77. This platform accounts for the majority of Kaspersky's positive recommendation activity and represents the clearest evidence that the brand can convert visibility into recommendation credit when the source environment is favorable.

The modeled monthly AI Authority Value for Kaspersky is $399,294, representing 1.2% of the total category opportunity of $32.4 million. Bitdefender, Norton, and Malwarebytes collectively capture 37.2% of that value. Kaspersky is competing with six other brands for the remainder, in a position where sentiment suppression is the primary structural barrier.

Across the three high-intent clusters, Kaspersky's strongest recommendation coverage appears in the Antivirus Software Pricing and Plans Evaluation cluster at 9.8%. Its weakest relative performance is in the Antivirus Software Comparison and Alternatives cluster, where buyers are actively evaluating options and competitor displacement is most acute.

What Kaspersky Is Winning

Perplexity is a meaningful recommendation pocket. Kaspersky achieves 25.9% recommendation coverage on Perplexity, its strongest platform by a wide margin. The brand appears in 54.6% of Perplexity observations and earns a net sentiment score of 0.77 on that platform. The analysis found that Perplexity's source selection and retrieval patterns produce more favorable framing for Kaspersky than any other tracked platform.

The pricing and evaluation cluster shows competitive rank performance. In the Antivirus Software Pricing and Plans Evaluation cluster, Kaspersky achieves an average recommended rank of 2.3, its strongest rank performance across all clusters. When Kaspersky is recommended in this decision-stage cluster, it tends to appear early in the shortlist, which is the position that most directly influences buyer choice.

Negative mentions are absent on several platforms. Kaspersky carries zero negative mentions on ChatGPT and Google AI Overviews. While recommendation coverage on these platforms remains low, the absence of active negative framing means the brand is not being flagged as a risk in those environments. This is a foundation that could support recommendation growth if the underlying source layer is strengthened.

Where Kaspersky Has the Clearest AI Visibility Gaps

Sentiment is the primary barrier to recommendation conversion. Kaspersky's net sentiment score of 0.45 is the lowest in the category, and the gap between its presence rate (20.4%) and recommendation coverage (8.4%) is among the widest observed in the benchmark. The 45 negative mentions are concentrated on Gemini (23 negative mentions) and Google AI Mode (19 negative mentions). These platforms appear to be retrieving source material that frames Kaspersky negatively, which directly suppresses recommendation eligibility.

Google platforms are the weakest channel. On Google AI Mode, Kaspersky achieves only 5.5% recommendation coverage with a net sentiment score of negative 0.11. On Google AI Overviews, recommendation coverage drops to 0.4% with a net sentiment score of 0.06. On Gemini, the result is the most severe in the dataset: 1.8% recommendation coverage with a net sentiment score of negative 0.53. These three platforms represent a significant share of AI-driven buyer discovery, and Kaspersky is effectively excluded from shortlists across all of them.

Top-three and rank-one rates are well below category leaders. Kaspersky achieves a 6.1% top-three rate and a 2.7% rank-one rate across all observations. Bitdefender, by comparison, achieves 47.4% top-three and 34.5% rank-one. Norton achieves 32.9% top-three and 12.3% rank-one. Even when Kaspersky does receive recommendation credit, it rarely appears in the positions that drive meaningful buyer consideration.

The comparison cluster is a structural displacement risk. In the Antivirus Software Comparison and Alternatives cluster, where buyers are actively weighing options against one another, Kaspersky achieves only 8.7% recommendation coverage. Bitdefender leads this cluster at 48.2% and Norton follows at 32.4%. At the moment buyers are most open to switching or selecting a provider, Kaspersky is being displaced by competitors whose public evidence layers produce more favorable AI framing.

Biggest Opportunity

The single most impactful move available to Kaspersky is to address the negative framing that suppresses recommendation conversion on Google platforms. The 42 negative mentions combined on Gemini and Google AI Mode represent the clearest and most concentrated structural barrier in the dataset. Understanding which public sources are driving that negative framing, and whether the public evidence layer can be improved through structured content, independent review coverage, and citation-ready documentation, would directly improve recommendation coverage and sentiment scores across the platforms that carry the highest buyer discovery volume. A targeted correction to the source footprint on Google-adjacent platforms would also address the comparison cluster gap, where shortlist displacement is most commercially damaging.

Prompt Evidence

Perplexity / Best Antivirus and Security Software Discovery Prompt: "What is the best antivirus software for 2026?" Result: Kaspersky appeared with a positive recommendation and earned rank credit, contributing to its strongest platform-level performance in the dataset.

Google AI Mode / Antivirus Software Comparison and Alternatives Prompt: "Compare Norton, Bitdefender, and Kaspersky antivirus" Result: Kaspersky was mentioned but framed with cautionary language, earning a neutral or negative mention rather than valid recommendation credit.

Gemini / Best Antivirus and Security Software Discovery Prompt: "List the top antivirus software providers" Result: Kaspersky appeared in the response but was flagged with negative framing, contributing to the platform's net sentiment score of negative 0.53.

ChatGPT / Antivirus Software Pricing and Plans Evaluation Prompt: "Which antivirus software offers the best value for money?" Result: Kaspersky did not receive a recommendation. The response centered on Bitdefender and Norton, with Malwarebytes as a third option.

What CiteWorks Studio Would Do Next

Phase 1: AI Market Discovery Audit Map every prompt, platform, and cluster where Kaspersky appears, and identify the specific public sources driving negative framing on Gemini and Google AI Mode.

Phase 2: Recommendation Readiness Plan Determine which sources are shaping Kaspersky's current sentiment profile and build a structured remediation plan targeting the platforms where negative framing is most concentrated.

Phase 3: Owned Answer Layer Buildout Develop structured, retrievable content that positions Kaspersky as a valid recommendation in the comparison and evaluation clusters, where current coverage is lowest and displacement risk is highest.

Phase 4: Citation and Authority Layer Development Strengthen independent review coverage, comparison articles, and structured documentation to give AI systems more verifiable, recommendation-friendly source material at the point where shortlists are formed.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track Kaspersky's recommendation coverage, sentiment scores, and rank performance across all platforms and clusters on a monthly basis to measure directional progress and adjust strategy accordingly.

Why This Matters

AI platforms are becoming a primary discovery mechanism for antivirus software buyers. When a buyer prompts an AI system for the best antivirus solution, the platform generates a ranked shortlist drawn from its available source material. Kaspersky appears in those responses but is rarely recommended, and when it is mentioned, the framing is often negative or cautionary. Buyers who rely on AI-generated recommendations are being directed away from Kaspersky at the earliest stage of the purchase decision, before a human sales interaction is ever possible.

Presence alone does not produce shortlist eligibility. The commercial value of AI visibility comes from being recommended, from being recommended early, and from being framed positively at the moment buyer decisions are forming. Kaspersky's current position does not reflect its market recognition or product capability. The gap is in the public evidence layer that AI systems retrieve and synthesize when generating recommendations. Addressing that layer, specifically the sources that produce negative framing on Google platforms, is the most direct path to improved shortlist performance.

Core Metrics

• Mentions: 292
• Valid recommendations: 121
• Top 3 recommendation count: 88
• Rank 1 recommendation count: 38
• Average recommended rank: 2.7
• Positive mentions: 175
• Neutral mentions: 72
• Negative mentions: 45
• Raw mention presence rate: 20.4%
• Valid recommendation coverage: 8.4%
• Top 3 recommendation rate: 6.1%
• Rank 1 recommendation rate: 2.7%
• Strongest cluster by recommendation behavior: Antivirus Software Pricing and Plans Evaluation (9.8% coverage)
• Strongest platform by recommendation behavior: Perplexity (25.9% coverage)

Sentiment Score

Sentiment Score = (175 x 1 + 72 x 0 + 45 x -1) / 292 = 130 / 292 = 0.45

This score reflects a brand that receives more positive than negative mentions in absolute terms, but where a material volume of negative framing is suppressing overall recommendation conversion. Unclassified mention counts are misleading because they treat all appearances as equivalent. A positive recommendation, a neutral reference, a cautionary mention, and a competitor-displaced mention carry entirely different commercial implications. Share of voice is a diagnostic metric, not a business KPI. Counting all mentions as wins is bad measurement. Kaspersky's classified sentiment reveals a structural weakness that raw presence numbers would conceal. The negative framing concentrated on Gemini and Google AI Mode is the most commercially significant signal in the dataset, because those platforms account for a large share of buyer discovery activity.

Sentiment by Platform

Methodology

1. This report is an AI Company Market Strategy Report based on LLM Authority Index benchmark data for the antivirus software category. It is not a client implementation case study and does not reflect a CiteWorks Studio engagement with Kaspersky.
2. The reporting window is June 2026. All data reflects a point-in-time snapshot taken during that month.
3. AI platforms tracked: ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, and Perplexity.
4. Total observations analyzed: 1,434 across all platforms and clusters. Unique prompt count was not available in the dataset supplied for this report.
5. Competitor universe: Bitdefender, Norton, Malwarebytes, ESET, Avast, McAfee, AVG, Trend Micro, and Webroot. This universe covers major global antivirus brands and is not a full market census.
6. Three public high-intent clusters were analyzed: Best Antivirus and Security Software Discovery (awareness stage), Antivirus Software Comparison and Alternatives (consideration stage), and Antivirus Software Pricing and Plans Evaluation (decision stage).
7. A mention is defined as any appearance of a company name in an AI-generated response, regardless of framing, ranking, or context.
8. A valid recommendation is defined as a positive, shortlist-quality recommendation or ranked recommendation that earns recommendation credit. Neutral, cautionary, and negative mentions do not qualify as valid recommendations. This distinction is the central metric separation applied throughout this report.
9. Sentiment scoring uses the formula: (positive mentions x 1 + neutral mentions x 0 + negative mentions x -1) divided by total mentions. This produces a score between negative 1 and positive 1. Framing classification reflects the tone and context of the AI-generated mention, not customer review sentiment.
10. Modeled monthly AI Authority Value and modeled monthly AI Recommendation Value are commercial intent proxies based on search volume and category weighting. They are not revenue, pipeline, or bookings figures.
11. Ranking metrics (top-three rate, rank-one rate, average recommended rank) apply only to observations where a valid recommendation was recorded. They do not apply to neutral or negative mentions.
12. This report does not contain Ahrefs or organic search data. All AI recommendation metrics are sourced exclusively from the LLM Authority Index benchmark dataset.
13. AI outputs change with model updates, source changes, and content shifts. This report reflects the competitive landscape at the time of data collection and should be treated as a time-specific benchmark, not a permanent assessment.

See How AI Is Recommending Your Brand

The benchmark data shows where Kaspersky appears in AI responses, where competitors are recommended instead, and which platforms carry the most commercial risk. If your brand is visible but not recommended, or if negative framing is suppressing shortlist eligibility, the next step is to understand exactly why. CiteWorks Studio maps your full AI visibility profile across platforms and clusters, identifies the sources shaping your sentiment score, and builds a targeted plan to improve recommendation-stage coverage at the moments where buyer decisions are formed.