Majority of Companies Embrace AI Yet Fear Data Reliability Issues

Organizations Confront Data Quality Challenges in AI Adoption

In today’s fast-paced digital world, the implementation of artificial intelligence (AI) has become essential. A recent survey conducted by Dun & Bradstreet indicates that a striking 88% of organizations are actively adopting AI technologies. However, amid this rapid growth, over half of these companies, approximately 54%, are grappling with significant concerns about the trustworthiness and accuracy of the data being utilized for these advanced technologies.

Importance of Data Quality for AI Effectiveness

Gary Kotovets, Chief Data & Analytics Officer at Dun & Bradstreet, emphasizes the critical role of data in the successful deployment of AI initiatives. He states, “AI’s effectiveness – including explainability, transparency and relevancy – depends on the quality of the data it leverages.” It's alarming to note that only 50% of organizations believe their data foundations are robust enough for the proper implementation of AI solutions.

AI Implementation Concerns

Survey participants highlighted several significant challenges regarding AI implementation. Data security concerns top the list, cited by 46% of respondents, followed closely by fears of data privacy violations (43%) and the potential for sensitive information to be disclosed (42%). Additionally, 26% expressed worries about the amplification of bias through the data processed by AI systems. Thus, it is no surprise that only 52% of organizations feel they possess a strong data foundation conducive to the success of generative AI.

Stages of AI Integration

The survey identified that companies find themselves at different stages regarding AI integration. Some are still in the exploration phase (29%), while others are deploying AI solutions (25%) or actively developing AI products (24%). A smaller segment is piloting AI initiatives (10%). Two common obstacles faced during this integration include obtaining trusted business data and navigating complex ethical and regulatory landscapes, each cited by 33% of respondents.

Challenges Across AI Implementation

Regardless of their current stage in AI implementation, businesses often encounter similar challenges. These include aligning business priorities and securing internal expertise (31%), interpreting the technology due to its lack of explainability (28%), conducting AI risk assessments (27%), demonstrating a return on investment (25%), and ensuring transparency in AI processes (25%).

Achievement Through AI Deployment

Companies currently deploying AI report achieving significant progress in several areas. The most notable improvements include streamlining processes (42%), co-piloting tasks (39%), supplementing current responsibilities (38%), establishing measurement and key performance indicators (21%), and scenario modeling (18%). Meanwhile, a notable 13% are focused on eliminating personnel bias.

Future AI Trends for 2025

Looking ahead to the trends expected to shape AI in 2025, respondents pointed to intelligent automation (51%) as a key trend, followed by conversational AI (46%), multimodal and visual AI (33%), and hyper-personalization in marketing strategies (23%). Additionally, one in four respondents is preparing for the effects that new regulatory frameworks and compliance measures might have on their business operations.

Agentic AI Use Cases

Regarding the optimal applications for agentic AI—AI systems capable of working independently—an impressive 64% of respondents noted that automating routine tasks ranks as the foremost use case, followed by enhancing human capabilities (42%), improving data management (36%), and analyzing market trends (32%).

Commitment to Responsible AI

The commitment of Dun & Bradstreet to responsible AI is evident, as reflected by the recent achievement of TrustArc’s TRUSTe Responsible AI Certification. This recognition underscores the company's dedication to ethical AI practices that prioritize transparency and accountability.

About Dun & Bradstreet

Dun & Bradstreet stands as a leading global provider of business decision-making data and analytics, empowering organizations worldwide to enhance their performance. The Dun & Bradstreet Data Cloud drives solutions and provides insights that enable clients to accelerate growth, lower costs, manage risks, and transform operations. Established in 1841, companies of all sizes have relied on Dun & Bradstreet to uncover opportunities and navigate risks effectively.

Frequently Asked Questions

What percentage of organizations are adopting AI according to the survey?

According to the survey conducted by Dun & Bradstreet, 88% of organizations are implementing AI technologies.

What is the primary concern regarding data that organizations have?

The primary concern for organizations is the trustworthiness and quality of the data used for AI, with 54% reporting issues.

Which areas are companies seeing the most progress in AI deployment?

Companies report the highest progress in streamlining processes, with 42% recognizing advancements in this area.

What obstacles do companies face in AI integration?

Trust in data and navigating ethical and regulatory challenges are identified as the main obstacles, cited by 33% of respondents.

What type of AI trends are expected to emerge by 2025?

Emerging AI trends for 2025 include intelligent automation, conversational AI, multimodal AI, and hyper-personalized marketing efforts.

About The Author

Dedicated Author and financial expert Logan Wright here, 29 years old. After earning an economics degree, I spent a number of years working in different financial industries. My great passion is enabling everyone, from any background or experience level, to understand and be literate in financial matters.

My books and writings are centered on simplifying difficult financial ideas into doable, understandable guidance. Whether it's retirement planning, investing, or budgeting, I want to arm readers with the information they need to make wise financial choices and realize their financial objectives.

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