Lack of data quality and governance seen as major AI obstacles

Precisely has 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 Insights1 report shed light on the most pressing challenges businesses face in achieving AI readiness and other data initiatives, and how they're prioritising investments in data integrity to overcome them.

AI success impacted by lack of data readiness

The report reveals that, despite 60 percent of organisations stating AI is a key influence on data programmes (a 46 percent increase from 2023), only 12 percent 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 percent of organisations say data-driven decision-making is a top goal for their data programmes, 67 percent still don't completely trust the data they rely on for these decisions, a rise from 55 percent in 2023.

A lack of data governance is the primary data challenge inhibiting AI initiatives, cited by 62 percent of organisations. This is likely due to the role that data governance programmes play in managing an organisation’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 prioritising 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 percent) say a shortage of skills and resources continues to be one of their biggest challenges to data programmes, up from 37 percent in 2023.

“While organisations 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 percent 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 organisations worldwide. This year, 64 percent of respondents identified data quality as their top data integrity challenge, up from 50 percent in 2023. Additionally, the overall perceptions of data quality have declined, with 77 percent of respondents rating the quality of their data as average or worse, compared to 66 percent 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 percent of respondents. Inconsistent data definitions and formats (45 percent), and data volume (43 percent) 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 percent of respondents reporting that data quality is the number one issue impacting their organisation’s data integration projects.

Data governance adoption has risen dramatically

To combat challenges with data trust, quality, and AI success, organisations are increasingly realising the importance of robust data governance programmes. This year, 51 percent of organisations identified data governance as a top challenge to data integrity, second only to data quality, marking a dramatic 89 percent increase from the previous year (up from 27 percent in 2023). In line with this, adoption has increased with 71 percent reporting that their organisation has a data governance programme, compared to 60 percent in 2023.

This increased investment is paying off. Organisations that invested in data governance programmes report benefiting from improved data quality (58 percent), improved quality of data analytics and insights (58 percent), increased collaboration (57 percent), increased regulatory compliance (50 percent) and faster access to relevant data (36 percent).

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 percent report data enrichment as a priority for data integrity, up from 23 percent in 2023. Organisations are now seeking to reveal maximum context from their data for enhanced innovation, operational efficiencies, and competitive advantage. Similarly, 21 percent of organisations say spatial analytics is a priority for data integrity initiatives, up from 13 percent the previous year.

“Our joint research with Drexel Lebow reveals a marked decline in organisations' confidence in their data readiness despite the increase in importance of data-driven decision-making,” said Josh Rogers, CEO at Precisely. “To fully capitalise on the business benefits of analytics and AI, organisations 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 realise the value of their AI initiatives.”