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AI Insights from Dun & Bradstreet Survey

In a sprawling survey involving 10,000 businesses across 32 countries, Dun & Bradstreet reveals significant insights into the current state of AI investments and their returns. A striking 65% of companies are set to enhance their AI expenditure over the next year. However, only 28% report experiencing strong or broad returns from their AI initiatives.

The findings indicate a profound impact of data readiness on the effectiveness of AI implementations. Specifically, organizations possessing fully prepared data for AI see returns at a remarkable rate of 6.5 times higher than those with only partially ready data. While only 8% of the surveyed businesses possess data that is entirely ready to harness AI at a large scale, a considerable 33% report their data as mostly ready, and 44% categorize it as partially ready. This disparity underscores a pressing need for businesses to enhance their data foundations to support their growing AI initiatives.

Among the global regions surveyed, Eastern Europe, Asia Pacific, and Western Europe emerged as frontrunners, each reporting rates of strong AI ROI at around 30-31%. In contrast, businesses in the Americas and Africa lagged, with the Americas showing a significant disconnect between AI investment and data readiness. Approximately 68% of American businesses plan to increase AI spending, yet only 23% report broad or strong returns. This hints at a critical area for improvement, suggesting that companies in the Americas have substantial potential to reap greater rewards by advancing their data readiness.

Gary Kotovets, Chief Data Analytics Officer at Dun & Bradstreet, emphasizes the vital role of data quality in determining AI success. He states, “Organizations with fully ready data experience broad returns significantly more often than their counterparts.” This observation suggests that it's not merely the presence of AI technologies that drives success, but rather the context and quality of data fed into these systems.

Furthermore, the survey reveals that while active AI initiatives have become nearly ubiquitous—98% of businesses reported some form of AI activity—there is a stagnation in ROI growth. Despite the increase in firms attempting to scale AI projects into full production (rising from 34% to 37% since Q3), the overall percentage reporting remarkable returns has remained stable at 28%.

The results also show that organizations that find themselves in the ‘partial readiness’ group generally report limited and inconsistent returns from their AI efforts, with only 16% achieving notable success compared to the 81% of those with fully ready data. This pattern urges firms to take proactive steps in building a robust data infrastructure to make the most out of their AI investments.

Despite the stagnation in reporting, the potential for ROI from AI remains clear. Companies must, therefore, prioritize data quality, focusing on verified identity and connected data to harness AI more effectively. This will not only accelerate their ability to achieve successful outcomes but also position them for future growth in an increasingly AI-driven marketplace.

In conclusion, Dun & Bradstreet's AI Momentum Survey provides a crystal-clear view of the landscape of AI investments and reveals critical gaps in data readiness that businesses need to address. As the world leans heavily into AI, organizations must ensure their foundational data is not only comprehensive but also fully prepared to support these advanced technologies. As Kotovets aptly states, “Enterprises that invest in verified identity, connected data, and decision-ready context will be better positioned to scale AI with greater speed, confidence, and control.”