New research from Precisely and Drexel University’s LeBow College of Business Center for Applied AI and Business Analytics reveals gaps in operational maturity, data reliability, and skills as organizations seek to scale AI across the enterprise
Burlington, Massachusetts, January 21, 2026 /PRNewswire/ — exactlythe world leader in data integrity, today announced the findings of its fourth annual report. Data integrity and AI readiness study. This was carried out in collaboration with Center for Applied AI and Business Analytics at Drexel University’s LeBow College of Business The study, based on a survey of more than 500 senior data and analytics leaders at large enterprises in the US and EMEA, highlights a growing disconnect in how organizations perceive their AI readiness. While the overwhelming majority of leaders believe they are ready for AI, their responses point to fundamental gaps that can significantly undermine AI success.
“Our findings show that trust in AI does not automatically translate into ROI. Organizations are moving quickly, but many are doing so without the trusted, governed data foundation needed to scale AI responsibly. This disconnect represents what we call the agenttic AI data integrity gap, and it poses significant risks,” said Dave Shuman, Chief Data Officer at Precisely. “As AI systems become more autonomous, data integrity is no longer a nice-to-have, but a business imperative. Organizations that invest today in agentic-ready data that is integrated, improved, managed, and contextualized will be in the best position to turn their AI ambitions into measurable business outcomes.”
Access the full report here. Data integrity and AI readiness in 2026.
Disconnect between agent-enabled data perception and reality
AI continues to be a top priority, with 52% of survey respondents citing AI as a key impact on their data programs and 85% of respondents reporting their organizations adopting Agentic AI. Agentic-ready data is essential for return on investment (ROI). However, a study conducted in late 2025 identified key areas of concern around infrastructure, skills, and data readiness as organizations look to move from AI pilots to full-scale implementations.
Key findings include:
- While many leaders confidently report that they have the necessary infrastructure (87%), skills (86%), and data readiness (88%) for AI, many also acknowledge that infrastructure (42%), skills (41%), and data readiness (43%) are the biggest hurdles.
- Although most organizations claim to have successfully linked AI to business objectives, only 31% have actual metrics tied to key performance indicators (KPIs).
- 43% of leaders cite data preparation as the top barrier to aligning AI with business goals, and more than half cite data quality as the most common data integrity priority.
Data governance becomes a key differentiator
Over the past 18-24 months, the market has reached an inflection point, with AI moving towards action-driven agent systems. This research highlights a clear divide between organizations that have a clearly defined data strategy and those that don’t. Leaders who prioritize accurate, consistent, and contextual data, backed by strong data governance, report having far greater confidence in their ability to execute and scale AI initiatives.
- 71% of organizations with a data strategy and data governance program report having high confidence in their data. In contrast, 50% of organizations have not adopted it.
- While 63% have established some form of AI governance, companies that integrate AI governance into their existing data governance programs are even more successful.
- 96% of organizations report investing in location intelligence and third-party data enhancements to add context to data for AI initiatives.
- 32% of leaders who have already implemented a data strategy and governance expect to see positive ROI from AI in just 6-11 months.
Skills shortage continues
In addition to data readiness challenges, more than half (51%) of organizations cite skills as their top need for AI initiatives, but only 38% feel well prepared when it comes to staff skills and AI training. The main areas where AI skills are lacking are:
- Ability to deploy AI at scale (30%)
- Responsible AI and compliance expertise (29%)
- Transform business needs into AI solutions (28%)
- AI model development and basic AI literacy (27%)
Dr. Murugan Anandarajan, professor and academic director of Drexel LeBow’s Center for Applied AI and Business Analytics, said, “The skills gap is not due to a lack of talent in one area, but rather to the need for experts who can work on data, business strategy, and AI governance simultaneously.” “That reality has profound implications for how organizations and universities prepare their workforces for the era of agentic AI.”
Moving to Agentic AI increases data integrity risks
Agentic AI transforms the way we work by enabling systems that not only generate insights and content, but also take actions, interpret signals, make decisions, and execute workflows across the enterprise. This research highlights how unprepared many people are at the data infrastructure level. This lack of readiness has created an Agentic AI data integrity gap, a gap between the current state of enterprise data and what is needed to securely and effectively power Agentic AI at scale.
Organizations that successfully close the gap focus on Agentic-Ready Data strategies built on integrated, easily discoverable data. Enrichment by trusted third parties. Continuous updates. and strong governance, transparency, and automation. Drive trust, control, and efficiency at scale.
For a comprehensive look at the 2026 Data Integrity and AI Readiness study, join us on February 25, 2026 for the 2026 Data Integrity and AI Readiness webinar to hear directly from experts from Precisely and Drexel LeBow’s Center for Applied AI and Business Analytics, or access the full report. Data integrity and AI readiness in 2026.
About Drexel University LeBow College of Business
Drexel University’s LeBow College of Business is an AACSB-accredited, top-ranked business school offering market-focused undergraduate, graduate, and certificate programs that prepare students to make an impact at the intersection of business and technology.
LeBow’s Center for Applied AI and Business Analytics forms partnerships to benefit current and future practitioners who seek to discover, advance, and create value from the transformative impact of data and AI on business and society. The center connects leading companies with faculty, researchers, and students, providing access to university expertise, the ability to shape curriculum, and a talent pipeline for co-ops, internships, and employment. From applied research, course projects, and thought leadership to STEM youth programs and a passionate community of industry experts, collaboration benefits both organizations and students.
About accuracy
As the world leader in data integrity, Precisely ensures your data is accurate, consistent, and in context. Our portfolio, including Precisely Data Integrity Suite, helps you integrate data, improve data quality, manage data usage, geocode and analyze location data, and enrich your data with complementary datasets to make business decisions with confidence. More than 12,000 organizations in more than 100 countries, including 95 of the Fortune 100, trust Precisely’s software, data, and data strategy consulting to power their AI, automation, and analytics efforts. Learn more here www.exactly.com.
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