Data quality was nominated as the main obstacle to uptake of Generative AI, according to a global survey undertaken for Informatica. The report, which canvassed 600 enterprise Chief Data Officers and other data decision makers across the US, Europe, and Asia-Pacific, found nearly all (99%) of generative AI adopters have encountered roadblocks

42% of data leaders cited data quality as the main obstacle, followed by data privacy and governance (40%) and AI ethics (38%).

The report found GenAI adoption is already well underway, with nearly half (45%) of data leaders reporting they’ve already implemented generative AI, with an additional 53% who anticipate they will, including 36% who expect to within the next two years.

“Unsurprisingly, generative AI implementation and the data strategies needed to do so successfully continue to dominate bandwidth for most data leaders, regardless of region or vertical,” said Jitesh Ghai, Chief Product Officer at Informatica.

“While there remains a myriad of technical and organizational hurdles that these leaders must navigate, it’s clear investments in holistic, highly integrated data management capabilities are the key to unlock the vast potential of GenAI and empower enterprises to take full control of their ever-expanding data estates.”

Despite challenges to generative AI implementation, 73% of data leaders use or plan to use the technology to improve time to value with faster data insights, while 66% want to drive more productivity through automation and augmentation

Data readiness is top of mind when it comes to AI and data strategy ROI. 43% reported that improving readiness of data for AI and analytics is the most common metric to measure data strategy effectiveness, a shift from the 2023 survey finding indicating the top metric was to improve how data is utilized in business decision making (45%)

Data fragmentation and complexity persists and is expected to worsen in 2024:

- 41% of data leaders struggle to balance 1,000-plus data sources, a decrease from last year (55%), but 79% expect this number to increase in the year ahead

- 58% of data leaders say they’ll need five or more data management tools to support their priorities and manage their data estates, an increase from 2023 (50%)

- 39% of data leaders reported the increasing number of data consumers is the top technical obstacle to realize their data strategy, while 38% said it was the increasing volume and variety of data. Last year, the main obstacle was a lack of a complete view and understanding of their data estates (the fourth-highest obstacle in 2024)

Internal organizational resistance also threatens to derail data strategies and priorities. 98% of those surveyed admitted organizational obstacles hold back their data strategies, including a lack of leadership support (45%), inability to justify ROI for budget (45%), and lack of cooperation/alignment across business units (44%)

The ability to deliver reliable and consistent data fit for generative AI (39%) and improving data-driven culture and data literacy (39%) are the top data strategy priorities in 2024, a shift from the 2023 report where the ability to improve governance over data and data processes was the top data strategy priority (the third-highest priority in 2024) while the ability to deliver data fit for analytics and AI was the seventh-highest.