Purpose
AI Scoreboard ranks major AI companies by their current competitive position across models, products, money, mindshare, enterprise traction, developer adoption, infrastructure, and risk.
The score is directional and explainable, not mathematically definitive. Every score should be paired with rationale and confidence.
Weights
| Dimension | Weight | Description |
|---|---|---|
| Model Quality | 20% | Frontier model strength, reasoning, coding, multimodal ability, and perceived real-world quality. |
| Product Adoption | 15% | Consumer usage, paid traction, recognizable products, retention signals, and breadth of use cases. |
| Infrastructure | 15% | Compute, chips, cloud capacity, data centers, supply chain, and ability to serve at scale. |
| Enterprise Traction | 12.5% | B2B adoption, partnerships, compliance, sales motion, and large-organization credibility. |
| Developer Ecosystem | 12.5% | APIs, SDKs, docs, integrations, tooling, community activity, and developer mindshare. |
| Money / Valuation | 10% | Funding, revenue estimates, market strength, investor confidence, and financial capacity. |
| Mindshare | 10% | Media attention, search interest, brand recognition, social relevance, and category perception. |
| Risk | -5% | Legal, regulatory, safety, governance, margin, dependency, platform, reputation, and execution risk. |
Formula
total =
model_quality * 0.20 +
product_adoption * 0.15 +
infrastructure * 0.15 +
enterprise_traction * 0.125 +
developer_ecosystem * 0.125 +
money_valuation * 0.10 +
mindshare * 0.10 -
risk * 0.05Data Policy
V1 uses sample editorial data until real source notes are added. Published rankings should include source notes, timestamps, and confidence ratings. Estimated numbers should be labeled as estimates.