AI Visibility Study: Design & Prototyping Tools

Content

Why we ran this study

At GEO Advisor, we run cross-category benchmarks to understand how software products appear in AI generated answers. As designers, founders, and product teams increasingly ask AI which tools to use, visibility inside models is becoming a meaningful distribution channel.

This study focuses on UI and UX design and prototyping tools. We wanted to understand which products AI recommends, how they are positioned, and what tradeoffs consistently shape sentiment.

Methodology

We tested 300 design-related prompts covering:

• Tool recommendations by team type

• Prototyping and collaboration workflows

• Comparisons between leading platforms

For each brand, we measured:

• Mention rate

• Sentiment

• Share of voice

We combined these signals into a single AI Visibility Score and analyzed how models describe strengths and limitations.

Top results

Figma — 98.7

Mentioned in 79.5 percent of queries
Share of voice: 53.8 percent

Figma overwhelmingly dominates AI visibility in design tooling. Models consistently treat it as the default collaborative design platform for modern teams.

Strengths surfaced by AI:

• Real time collaboration across teams

• Mature design systems with components and tokens

• Strong alignment with how product teams scale design

Tradeoffs surfaced by AI:

• Pricing and plan limitations as teams grow

• Lack of offline access becoming a constraint in some environments

Figma wins because AI sees it as infrastructure, not just a tool.

Framer — 74.4

Mentioned in 36.4 percent of queries
Share of voice: 24.6 percent

Framer appears when the context shifts toward interactive, high fidelity prototypes and production-ready design. AI often frames it as powerful, but specialized.

Strengths surfaced by AI:

• Code powered, React-like components

• High fidelity interactions and animations

• Strong bridge between design and implementation

Tradeoffs surfaced by AI:

• Steeper learning curve compared with visual-first tools

• Debugging complexity and pricing friction for non-technical teams

Framer is recommended when teams value realism and execution over accessibility.

Canva — 60.8

Mentioned in 31.8 percent of queries
Share of voice: 21.5 percent

Canva shows up as the fast, beginner-friendly option. AI recommends it for lightweight design needs and non-designer workflows.

Strengths surfaced by AI:

• Template driven design and drag and drop workflows

• Brand kits that simplify consistency

• Very fast time to value

Tradeoffs surfaced by AI:

• Limited depth for advanced design systems

• Pricing and perceived value cap its role beyond lightweight use cases

Canva wins on speed and accessibility, but AI rarely frames it as a scalable design platform.

Big takeaway

In design tooling, AI strongly favors collaboration, shared systems, and scalability. Platforms win visibility when they align with how teams actually work together across design, product, and engineering.

At the same time, pricing friction, learning curves, and offline constraints meaningfully shape where AI draws the line between default recommendation and niche use case.

For design tool vendors, AI visibility is not just about features. It is about whether the product maps cleanly to real team workflows and scales with them.