A new CFO Dive article highlights research from Carnegie Mellon University, conducted in collaboration with Larridin, examining whether companies making meaningful investments in AI are beginning to see measurable business results.
The research found that companies with the most concrete and specific AI disclosures in their 10-K filings showed a significant revenue-growth advantage compared with companies whose AI disclosures were more vague. While the study does not prove that AI directly caused that growth, it provides compelling evidence that companies moving beyond experimentation and into real-world AI deployment may be seeing stronger commercial outcomes.
Larridin played a central role in the research. The study drew on Larridin’s AI Transformation Tracker, which evaluates hundreds of companies using evidence-based signals including AI deployment, workforce capabilities, governance, hiring, leadership, and demonstrated business impact.
Working with Larridin, the Carnegie Mellon research team also expanded the analysis to examine AI investment intensity, the specificity of AI disclosures, AI-related risk language, and hiring patterns. Larridin data was also used to help validate the methodology for identifying AI-focused roles.
The findings reinforce an important idea behind Larridin’s work: AI transformation can be measured using observable business evidence—not just executive claims or broad statements about innovation.
As Larridin founder and CTO Ameya Kanitkar explained in CFO Dive, increasingly specific AI disclosures may indicate that companies are progressing from experimentation toward identifying and deploying higher-value use cases.
Read the full CFO Dive article to learn more about the research and what the findings could mean for companies investing in AI transformation.