Data integrity study from Precisely and Drexel University’s LeBow College of Business exposes widespread data trust issues and its impact on data and AI initiatives
Precisely, the global leader in data integrity, today released a new study conducted in collaboration with the Center for Applied AI and Business Analytics at Drexel University’s LeBow College of Business (Drexel LeBow). Key findings from this year’s 2025 Outlook: Data Integrity Trends and Insights report shed light on the most pressing challenges businesses face in achieving AI readiness and other data initiatives, and how they’re prioritizing investments in data integrity to overcome them.
AI success impacted by lack of data readiness
The report reveals that, despite 60% of organizations stating AI is a key influence on data programs (a 46% increase from 2023), only 12% report that their data is of sufficient quality and accessibility for effective AI implementation. For years, companies have grappled with poor-quality data, leading to a deeply rooted distrust in the data used for analytics and AI. While 76% of organizations say data-driven decision-making is a top goal for their data programs, 67% still don’t completely trust the data they rely on for these decisions, a rise from 55% in 2023.
A lack of data governance is the primary data challenge inhibiting AI initiatives, cited by 62% of organizations. This is likely due to the role that data governance programs play in managing an organization’s data usage – including where it’s stored, its lineage, who has access to it, whether it has personally identifiable information (PII) attributes, and more.
Skills gap further impede AI adoption
With more companies prioritizing data-driven decision-making, the shortage of skills and resources needed for data management, analytics, and AI has also grown this year. Forty-two percent (42%) say a shortage of skills and resources continues to be one of their biggest challenges to data programs, up from 37% in 2023.
“While organizations are eager to benefit from AI’s capabilities, a talent shortfall impedes AI integration,” said Murugan Anandarajan, PhD, Professor and Academic Director at the Center for Applied AI and Business Analytics at Drexel University’s LeBow College of Business. “Our research findings highlight that gap, with 60% of respondents citing a lack of AI skills and training as a significant challenge in launching AI initiatives – a signal to business leaders that upskilling must be a strategic imperative.”
Data quality remains the top data integrity challenge and priority
Given the findings relating to AI, it’s unsurprising to see data quality reported as a primary focus for organizations worldwide. This year, 64% of respondents identified data quality as their top data integrity challenge, up from 50% in 2023. Additionally, the overall perceptions of data quality have declined, with 77% of respondents rating the quality of their data as average or worse, compared to 66% in the previous year.
The most significant barrier to achieving high-quality data is the lack of adequate tools for automating data quality processes, cited by 49% of respondents. Inconsistent data definitions and formats (45%), and data volume (43%) are also top concerns.
The research also shows that poor data quality continues to have a ripple effect across all aspects of data integrity, with 50% of respondents reporting that data quality is the number one issue impacting their organization’s data integration projects.
Data governance adoption has risen dramatically
To combat challenges with data trust, quality, and AI success, organizations are increasingly realizing the importance of robust data governance programs. This year, 51% of organizations identified data governance as a top challenge to data integrity, second only to data quality, marking a dramatic 89% increase from the previous year (up from 27% in 2023). In line with this, adoption has increased with 71% reporting that their organization has a data governance program, compared to 60% in 2023.
This increased investment is paying off. Organizations that invested in data governance programs report benefiting from improved data quality (58%), improved quality of data analytics and insights (58%), increased collaboration (57%), increased regulatory compliance (50%) and faster access to relevant data (36%).
Data enrichment and location intelligence emerge as key data initiatives
The 2023 report predicted the emergence of data enrichment and spatial analytics as business-critical technologies, and this year’s report demonstrates a significant leap forward in adoption. In 2024, 28% report data enrichment as a priority for data integrity, up from 23% in 2023. Organizations are now seeking to reveal maximum context from their data for enhanced innovation, operational efficiencies, and competitive advantage. Similarly, 21% of organizations say spatial analytics is a priority for data integrity initiatives, up from 13% the previous year.
“Our joint research with Drexel Lebow reveals a marked decline in organizations’ confidence in their data readiness despite the increase in importance of data-driven decision-making,” said Josh Rogers, CEO at Precisely. “To fully capitalize on the business benefits of analytics and AI, organizations need to invest in data integrity. Establishing a foundation of accurate, consistent, and contextual data can serve to help them make informed decisions with confidence and truly realize the value of their AI initiatives.”
Register for Trust ’24 to hear more from Precisely CEO Josh Rogers and the team at Drexel LeBow on what the research findings mean for organizations. For a deeper dive into the data, access the full 2025 Outlook: Data Integrity Trends and Insights report.
Methodology
The survey of data and analytics professionals was conducted in the first half of 2024. The online survey was jointly developed by Drexel LeBow and Precisely, with an analysis of results led by Drexel LeBow with collaboration from Precisely. More than 565 data and analytics professionals worldwide participated in the survey. Respondents represented a wide variety of titles within their organizations, including data managers, stewards, architects, and analysts (30%), IT managers (18%), C-level executives (12%), VP or line-of-business directors (11%), line-of-business managers (7%), VP or IT directors (6%), and others (16%).
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