Measuring AI innovation with trademark data

2026-07-21 · Source: Computation and Language · Field: Science & Research — Research Methodology & Innovation, Artificial Intelligence & Machine Learning, Economic Analysis & Policy · Depth: Intermediate, quick

Summary

This research note proposes using AI trademark data as a complementary metric to AI patents for measuring Artificial Intelligence innovation. Trademark data offers a timely and globally available source covering all economic sectors, revealing how companies exploit AI technologies to develop new goods and services. The analysis illustrates opportunities from AI trademarks, presenting insights from an empirical exploration of Italian firms. This approach can address emerging questions about AI's development and diffusion by providing a different dimension of innovation compared to patents, which often focus on technological invention. The authors reflect on how AI trademarks can be used at different levels of analysis to tackle emerging questions about the development and diffusion of AI.

Key takeaway

For policymakers and researchers mapping AI development and diffusion, integrating AI trademark data into your analysis is crucial. This data source offers a timely, globally available perspective on how companies commercialize AI into new goods and services, complementing traditional patent analysis. You should consider trademark trends to gain a more complete understanding of AI's economic impact and diffusion across diverse sectors, especially when assessing market exploitation.

Key insights

AI trademarks offer a timely, global complement to patents for measuring AI innovation in goods and services.

Principles

• AI trademarks reveal commercial exploitation of AI.
• Trademark data is timely and globally available.
• Trademarks complement patents for innovation mapping.

Method

Utilize AI trademark data to track how companies apply AI technologies in new goods and services, complementing patent analysis.

In practice

• Map AI diffusion across economic sectors.
• Identify firms exploiting AI for new offerings.

Topics

• AI Innovation Measurement
• Trademark Data
• AI Diffusion
• AI Commercialization
• Patent Analysis

Best for: Research Scientist, Policy Maker, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by Computation and Language.