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Video Conferencing: AI visibility report

Generated source analysis for Video Conferencing. Scores and market figures are illustrative, with no observed response sample attached.

Generated source analysis. Market figures and findings below are generated claims, with no measurement records attached.

Generated 10 Jan 2026 · Read the source

A comprehensive analysis of how leading video conferencing brands are perceived and recommended by Large Language Models and AI search engines.

In 2026, the video conferencing landscape has shifted from a battle of bandwidth to a battle of 'AI-native integration.' Our analysis indicates that visibility within AI recommendation engines is now the primary driver for mid-market and enterprise procurement. Microsoft Teams and Zoom maintain a dominant share of voice, but niche players like Butter and Around are capturing significant visibility in 'creative' and 'asynchronous' query clusters. The report highlights a 34% increase in user queries specifically asking for 'AI-automated meeting synthesis' capabilities, where Google Meet and Teams currently lead.

Key findings in the source

Generated claims, including numeric figures. No underlying measurements are attached.

  • Microsoft Teams holds a 94% visibility rate for 'enterprise-grade' queries due to deep integration with the Microsoft 365 ecosystem.
  • Perplexity AI shows the highest variance in brand recommendations, frequently citing GitHub discussions and Reddit for 'developer-centric' meeting tools like Jitsi.
  • Zoom's visibility has pivoted successfully from 'video quality' to 'AI Companion' utility, maintaining an 89% sentiment score across LLMs.
  • Google Meet dominates 72% of 'low-friction' and 'browser-based' recommendation slots within the Gemini platform.
  • 42% of LLM responses now prioritize 'privacy and data sovereignty' as a top-three evaluation criterion for video software.

The category scorecard.

Proposed scoring · illustrative source values. No measured ranking or trend is published here.
Microsoft Teams94 / 100Illustrative source score

Generated source profile. Scores and trends have no observed answer sample or measured history attached.

Source trend
stable (illustrative, no measured history attached)
Platform source scores
chatgpt: 96 / 100 · claude: 92 / 100 · gemini: 88 / 100 · perplexity: 95 / 100
Strength in source
Enterprise ecosystem integration
Weakness in source
Perceived complexity for small teams
Zoom89 / 100Illustrative source score

Generated source profile. Scores and trends have no observed answer sample or measured history attached.

Source trend
stable (illustrative, no measured history attached)
Platform source scores
chatgpt: 91 / 100 · claude: 89 / 100 · gemini: 85 / 100 · perplexity: 90 / 100
Strength in source
Brand ubiquity and AI features
Weakness in source
Bundling pressure from Microsoft/Google
Google Meet85 / 100Illustrative source score

Generated source profile. Scores and trends have no observed answer sample or measured history attached.

Source trend
rising (illustrative, no measured history attached)
Platform source scores
chatgpt: 82 / 100 · claude: 80 / 100 · gemini: 98 / 100 · perplexity: 84 / 100
Strength in source
Zero-install friction
Weakness in source
Feature depth compared to dedicated clients
Webex78 / 100Illustrative source score

Generated source profile. Scores and trends have no observed answer sample or measured history attached.

Source trend
declining (illustrative, no measured history attached)
Platform source scores
chatgpt: 75 / 100 · claude: 82 / 100 · gemini: 74 / 100 · perplexity: 81 / 100
Strength in source
Hardware integration and security
Weakness in source
Legacy brand perception
Butter72 / 100Illustrative source score

Generated source profile. Scores and trends have no observed answer sample or measured history attached.

Source trend
rising (illustrative, no measured history attached)
Platform source scores
chatgpt: 68 / 100 · claude: 79 / 100 · gemini: 65 / 100 · perplexity: 76 / 100
Strength in source
Facilitation and workshop tools
Weakness in source
Niche market focus
Around68 / 100Illustrative source score

Generated source profile. Scores and trends have no observed answer sample or measured history attached.

Source trend
stable (illustrative, no measured history attached)
Platform source scores
chatgpt: 70 / 100 · claude: 74 / 100 · gemini: 60 / 100 · perplexity: 68 / 100
Strength in source
UI/UX for creative teams
Weakness in source
Limited enterprise features
Whereby65 / 100Illustrative source score

Generated source profile. Scores and trends have no observed answer sample or measured history attached.

Source trend
stable (illustrative, no measured history attached)
Platform source scores
chatgpt: 62 / 100 · claude: 64 / 100 · gemini: 63 / 100 · perplexity: 71 / 100
Strength in source
Embedded video API
Weakness in source
Low general consumer awareness
GoTo Meeting58 / 100Illustrative source score

Generated source profile. Scores and trends have no observed answer sample or measured history attached.

Source trend
declining (illustrative, no measured history attached)
Platform source scores
chatgpt: 55 / 100 · claude: 59 / 100 · gemini: 54 / 100 · perplexity: 64 / 100
Strength in source
Reliability for webinars
Weakness in source
Outdated interface
Dialpad61 / 100Illustrative source score

Generated source profile. Scores and trends have no observed answer sample or measured history attached.

Source trend
rising (illustrative, no measured history attached)
Platform source scores
chatgpt: 58 / 100 · claude: 65 / 100 · gemini: 59 / 100 · perplexity: 62 / 100
Strength in source
AI-first voice intelligence
Weakness in source
Secondary player in video-first meetings
Gather55 / 100Illustrative source score

Generated source profile. Scores and trends have no observed answer sample or measured history attached.

Source trend
stable (illustrative, no measured history attached)
Platform source scores
chatgpt: 52 / 100 · claude: 60 / 100 · gemini: 50 / 100 · perplexity: 58 / 100
Strength in source
Gamified virtual office
Weakness in source
Specific use-case limitation

Platform behavior in the source.

Generated descriptions and brand lists. No provider responses are attached to establish this behavior.

ChatGPT

  • Favors established market leaders
  • Prioritizes feature-richness
  • High emphasis on integration

Strongly associates 'video conferencing' with Microsoft 365 productivity suite.

Top brands in the source: Microsoft Teams, Zoom

Claude

  • Nuanced UX evaluation
  • Focuses on 'flow' and 'collaboration style'
  • Objective analysis of pricing models

Frequently recommends 'Butter' for creative workshops and brainstorming sessions.

Top brands in the source: Butter, Around, Microsoft Teams

Gemini

  • Heavy bias toward Google ecosystem
  • Prioritizes speed and accessibility
  • Strong link to Google Workspace

Nearly 100% visibility for Google Meet in 'quick meeting' or 'calendar' related queries.

Top brands in the source: Google Meet, Zoom

Perplexity

  • Cites technical documentation
  • Aggregates real-time user reviews
  • Highly sensitive to recent product updates

Picks up on developer sentiment and open-source alternatives more than other platforms.

Top brands in the source: Microsoft Teams, Whereby, Jitsi

Enterprise Scalability

Source volume: high · Source competition: high

Top performers in the source: Microsoft Teams, Webex

AI Automation & Summarization

Source volume: high · Source competition: high

Top performers in the source: Zoom, Microsoft Teams, Google Meet

Creative & Design Workshops

Source volume: medium · Source competition: medium

Top performers in the source: Butter, Around, Miro

Privacy & Secure Communications

Source volume: medium · Source competition: high

Top performers in the source: Webex, Jitsi, Signal

Generated source analysis. Suggested strategies and trends from the source. Their effects have not been measured.

Generated 10 Jan 2026 · Read the source

Winning strategies in the source

  • Publishing detailed API documentation that LLMs can parse for integration queries.
  • Creating use-case specific landing pages (e.g., 'Video for Agile Sprints') that Claude and Perplexity index.
  • Active presence in niche community forums like Reddit and Stack Overflow to influence Perplexity sourcing.

Common weaknesses

  • Vague marketing language like 'best-in-class' which LLMs tend to ignore in favor of specific feature sets.
  • Gated content (PDFs) that prevents AI crawlers from accessing deep technical specifications.
  • Slow updates to public documentation regarding new AI features.

Emerging trends in the source

  • The rise of 'Spatial Audio' as a recommended feature for reducing 'Zoom fatigue'.
  • Increased visibility for 'Asynchronous Video' tools (Loom) as a replacement for live meetings.
  • LLMs recommending tools based on 'Carbon Footprint' and energy efficiency of data centers.

What to try next.

Suggested actions from the source. Impact labels are estimates.

For CMOs

Brand authority is being filtered through AI summaries.

Shift budget from traditional SEO to 'LLM Optimization' by creating structured data for all product features.

Suggested impact: high

Niche competitors are winning 'specific use case' recommendations.

Develop vertical-specific messaging (e.g., Video for Legal, Video for Healthcare) to capture long-tail AI queries.

Suggested impact: medium

For Product Managers

AI-driven meeting summaries are now a 'table stakes' feature.

Accelerate the roadmap for native LLM-based action item extraction.

Suggested impact: high

Integration with the 'AI Stack' (OpenAI, Anthropic, LangChain) is a visibility driver.

Build and document official plugins or connectors for major AI platforms.

Suggested impact: medium

Methodology stated in the generated source

The file does not include the prompt set, observed responses or deterministic aggregate needed to verify these methodology claims. Its reported sample and collection window should not be treated as verified measurements.

Trakkr analyzed 5,000+ queries across ChatGPT (GPT-4o), Claude 3.5 Sonnet, Gemini Pro, and Perplexity AI between January and March 2026. Data was weighted by platform market share and cross-referenced with technical documentation and third-party review aggregators.

Source title
2026 AI Visibility Report: Video Conferencing & Virtual Collaboration
Generated
10 Jan 2026
Interpretation
Use the generated hypotheses as inputs to your own category tests. Keep observed response evidence separate from this source scorecard.

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