Dive Brief:

• Companies with concrete artificial intelligence strategies are delivering stronger stock performance than peers that rely on vague or merely aspirational narratives, according to a new analysis from AI startup Blue Bridge Group AI.
• The firm’s 2026 AI Barometer analyzed 275 annual reports from companies across major U.S. and European stock indices, covering fiscal years 2020 to 2025. Organizations providing detailed AI strategies — including clear, quantified objectives and specific actions taken or planned — delivered stronger relative stock performance than peers that remained silent or relied on vague AI language, according to findings shared with CFO Dive.
• “There is a clear correlation between talking a lot about AI and having a positive share price — and that relationship strengthens further when disclosures are concrete rather than aspirational,” Blue Bridge CEO Sylvie Ouziel said in an interview.

Dive Insight:

The study found that AI mentions in annual reports have increased five to seven times since 2020. The communication/technology and financial sectors were the most vocal about technology choices, followed by business services, industrial/energy, luxury/consumer, healthcare/testing and aerospace/defense.

Companies discussing AI posted an average 1.3% share price gain in 2024, while companies that did not mention the technology saw an average 16.7% decline — an 18-percentage-point gap.

Those providing a comprehensive view of their AI initiatives across five dimensions — market impact, strategy, operations, organization and technology — generated an 8.8% average excess return between 2022 and 2024, compared with a 4.7% decline among companies that did not disclose AI activity.

Meanwhile, early hype around AI has given way to companies wrestling with implementation risks and challenges, with American businesses taking a particularly cautious stance compared with their European counterparts, according to the analysis.

Within the U.S., 63% of references to AI’s business impact carry a negative tone, compared with 37% in the U.K. and France and just 26% in Germany. 

AI-related concerns in the U.S. span across a number of key areas, including fragmented regulatory requirements, cybersecurity threats, intellectual property risks, model accuracy issues, and return-on-investment uncertainty, the study found.

The divergence may reflect differences in where companies sit on the AI adoption curve, according to Ouziel.

“I think the U.S. companies are probably further ahead and grappling with the difficulties of deploying AI at scale,” she said.