More Than Half of Companies Adopting AI are Worried About the Reliability and Quality of Their Data, According to New Dun & Bradstreet Survey
Dun & Bradstreet (NYSE: DNB) has released findings from an AI survey revealing that while 88% of organizations are implementing artificial intelligence, more than half (54%) express concerns about data quality and trustworthiness for AI applications.
Key findings show that organizations face multiple challenges in AI implementation, including data security (46%), privacy violations (43%), and information disclosure risks (42%). Only 52% of companies believe they have a solid data foundation for generative AI success.
Companies are at various implementation stages, with 29% in exploration, 25% deploying solutions, and 24% developing AI products. The survey identifies intelligent automation (51%) and conversational AI (46%) as top emerging trends for 2025. For agentic AI, 64% of respondents cite task automation as the primary use case, followed by augmenting human capabilities (42%) and strengthening data management (36%).
Dun & Bradstreet (NYSE: DNB) ha rilasciato i risultati di un sondaggio sull'IA che rivelano come l'88% delle organizzazioni stia implementando l'intelligenza artificiale, ma più della metà (54%) esprima preoccupazioni sulla qualità e sull'affidabilità dei dati per le applicazioni di IA.
I risultati chiave mostrano che le organizzazioni affrontano molteplici sfide nell'implementazione dell'IA, tra cui la sicurezza dei dati (46%), le violazioni della privacy (43%) e i rischi di divulgazione delle informazioni (42%). Solo il 52% delle aziende crede di avere una solida base dati per il successo dell'IA generativa.
Le aziende si trovano in diverse fasi di implementazione, con il 29% in fase di esplorazione, il 25% che sta implementando soluzioni e il 24% che sta sviluppando prodotti di IA. Il sondaggio identifica l'automazione intelligente (51%) e l'IA conversazionale (46%) come le principali tendenze emergenti per il 2025. Per quanto riguarda l'IA agentica, il 64% dei rispondenti cita l'automazione dei compiti come il caso d'uso principale, seguita dall'integrazione delle capacità umane (42%) e dal potenziamento della gestione dei dati (36%).
Dun & Bradstreet (NYSE: DNB) ha publicado los resultados de una encuesta sobre IA que revelan que el 88% de las organizaciones están implementando inteligencia artificial, pero más de la mitad (54%) expresa preocupaciones sobre la calidad y la confiabilidad de los datos para las aplicaciones de IA.
Los hallazgos clave muestran que las organizaciones enfrentan múltiples desafíos en la implementación de IA, incluidos la seguridad de los datos (46%), las violaciones de la privacidad (43%) y los riesgos de divulgación de información (42%). Solo el 52% de las empresas cree tener una base de datos sólida para el éxito de la IA generativa.
Las empresas están en diversas etapas de implementación, con un 29% en fase de exploración, un 25% implementando soluciones y un 24% desarrollando productos de IA. La encuesta identifica la automatización inteligente (51%) y la IA conversacional (46%) como las principales tendencias emergentes para 2025. Para la IA agentiva, el 64% de los encuestados cita la automatización de tareas como el caso de uso principal, seguida por el aumento de las capacidades humanas (42%) y el fortalecimiento de la gestión de datos (36%).
Dun & Bradstreet (NYSE: DNB)는 인공지능 조사 결과를 발표했습니다. 조사 결과에 따르면 88%의 조직이 인공지능을 도입하고 있지만, 절반 이상(54%)이 인공지능 애플리케이션에 대한 데이터 품질과 신뢰성에 대한 우려를 표명하고 있습니다.
주요 결과에 따르면 조직들은 인공지능 구현 시 데이터 보안(46%), 개인 정보 침해(43%), 정보 공개 위험(42%) 등 여러 가지 문제에 직면해 있습니다. 인공지능 생성 성공을 위한 견고한 데이터 기반이 있다고 믿는 기업은 52%에 불과합니다.
기업들은 다양한 구현 단계에 있으며, 29%는 탐색 중, 25%는 솔루션을 배포하고, 24%는 인공지능 제품을 개발하고 있습니다. 조사에서는 지능형 자동화(51%)와 대화형 인공지능(46%)이 2025년을 위한 주요 신흥 트렌드로 확인되었습니다. 자율적인 인공지능에 대해 64%의 응답자가 작업 자동화를 주요 사용 사례로 인용했으며, 다음으로 인간 능력을 증대(42%)시키고 데이터 관리를 강화(36%)하는 순이었습니다.
Dun & Bradstreet (NYSE: DNB) a publié les résultats d'une enquête sur l'IA, révélant que 88 % des organisations mettent en œuvre l'intelligence artificielle, mais plus de la moitié (54 %) expriment des inquiétudes concernant la qualité et la fiabilité des données pour les applications IA.
Les résultats clés montrent que les organisations font face à plusieurs défis dans l'implémentation de l'IA, notamment la sécurité des données (46 %), les violations de la vie privée (43 %) et les risques de divulgation d'informations (42 %). Seules 52 % des entreprises estiment avoir une base de données solide pour le succès de l'IA générative.
Les entreprises se trouvent à différents stades d'implémentation, avec 29 % en phase d'exploration, 25 % déployant des solutions et 24 % développant des produits IA. L'enquête identifie l'automatisation intelligente (51 %) et l'IA conversationnelle (46 %) comme les principales tendances émergentes pour 2025. Pour l'IA agentique, 64 % des répondants citent l'automatisation des tâches comme le cas d'utilisation principal, suivie par le renforcement des capacités humaines (42 %) et l'amélioration de la gestion des données (36 %).
Dun & Bradstreet (NYSE: DNB) hat die Ergebnisse einer Umfrage zur KI veröffentlicht, die zeigen, dass 88% der Organisationen künstliche Intelligenz implementieren, aber mehr als die Hälfte (54%) Bedenken hinsichtlich der Datenqualität und -zuverlässigkeit für KI-Anwendungen äußert.
Die wichtigsten Ergebnisse zeigen, dass Organisationen mit mehreren Herausforderungen bei der Implementierung von KI konfrontiert sind, darunter Datensicherheit (46%), Verletzungen der Privatsphäre (43%) und Risiken der Informationsweitergabe (42%). Nur 52% der Unternehmen glauben, dass sie eine solide Datenbasis für den Erfolg von generativer KI haben.
Unternehmen befinden sich in verschiedenen Implementierungsphasen, wobei 29% in der Erkundungsphase, 25% Lösungen implementieren und 24% KI-Produkte entwickeln. Die Umfrage identifiziert intelligente Automatisierung (51%) und konversationelle KI (46%) als führende aufkommende Trends für 2025. Bei agentischer KI geben 64% der Befragten an, dass Automatisierung von Aufgaben der primäre Anwendungsfall sei, gefolgt von der Verstärkung menschlicher Fähigkeiten (42%) und der Verbesserung des Datenmanagements (36%).
- None.
- None.
Businesses expect automation of tasks through agentic AI to be top use case, with one in three executives noting the opportunity to use agentic AI for strengthening data management
“AI’s effectiveness – including explainability, transparency and relevancy – depends on the quality of the data it’s leveraging, yet our survey uncovered that only five in ten organizations believe their data foundation is where it should be for proper AI implementation,” said Gary Kotovets, Chief Data & Analytics Officer at Dun & Bradstreet. “For AI planning, it is vital organizations ensure that their data is sourced from a clean, single source of truth that we call mastered data. At Dun & Bradstreet, we believe mastered data and AI are paramount to building effective solutions - our data is continually cleaned, updated, and validated to ensure it is as accurate, timely, and relevant as possible once it’s in the hands of our customers.”
Other top concerns cited by survey respondents related to AI implementation include data security (
AI Implementation & Use Cases Vary
The survey also revealed that companies are at various stages of implementation, including exploration and research (
Other challenges faced by businesses irrespective of where they are in their AI implementation journey include:
-
Aligning on business prioritization and having internal subject matter expertise (tied at
31% ) -
Lack of explainability and interpretability of the technology (
28% ) -
AI risk assessments (
27% ) -
Showcasing ROI (
25% ) -
AI transparency (
25% )
Further, companies currently deploying AI share that the highest level of progress has come from:
-
Streamlining processes (
42% ) -
Co-piloting (
39% ) -
Supplementing current tasks (
38% ) -
Measurement and KPIs (
21% ) -
Scenario modeling (
18% ) -
Personnel bias elimination (
13% )
AI Outlook for 2025
When asked about the emerging trends in AI that will impact businesses over 2025, half of survey respondents (
On the best use cases for agentic AI — AI agents working autonomously without constant human guidance — in the year ahead, two-thirds (
“We expect use cases for agentic AI in data management to abound this year. We’re already seeing how it can improve efficiency in processes such as data cleaning, integration, and analysis,” said Ginny Gomez, President,
Dun & Bradstreet recently received TrustArc’s TRUSTe Responsible AI Certification for the company’s strong commitment and adherence to responsible AI governance. Read about how the company is developing and deploying ethical AI solutions that prioritize transparency, fairness, and accountability here.
The above research and findings are based on an on-site survey conducted at The AI Summit New York (held December 11-12, 2024) of business executives across various organizational levels working in AI.
About Dun & Bradstreet
Dun & Bradstreet, a leading global provider of business decisioning data and analytics, enables companies around the world to improve their business performance. Dun & Bradstreet’s Data Cloud fuels solutions and delivers insights that empower customers to accelerate revenue, lower cost, mitigate risk, and transform their businesses. Since 1841, companies of every size have relied on Dun & Bradstreet to help them manage risk and reveal opportunity. For more information on Dun & Bradstreet, please visit www.dnb.com.
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Source: Dun & Bradstreet
FAQ
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