To overcome AI roadblocks, three in four (78%) data chiefs predict their data investments will increase in 2024 and all (100%) plan to specifically invest in data management capabilities

Informatica, an enterprise cloud data management leader, released the findings of its annual survey of global data leaders – CDO Insights 2024: Charting a Course to AI Readiness. The report, which canvassed 600 enterprise Chief Data Officers and other data decision makers across the U.S., Europe, and Asia-Pacific, provides insights into generative AI readiness, key technical and organizational roadblocks to implementation and top data and data management priorities and strategies for 2024.

“With AI and data management, data leaders can recognize that it is not one driving the other, but rather that the two go hand in hand – and making the most of both means transformative change for these technologies, leaders’ strategies, and the future of their organizations.”

“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.”

Chris Eldredge, VP, Data Office at Paycor said, “AI is only as good as the data that trains it, which means for us to be a successful AI and generative AI organization we must first be a successful data and data management organization – and that will remain a top focus for us in the months ahead.” Eldredge added that while many of Paycor’s priorities from 2023 have remained relatively unchanged, they cannot ignore the meteoric rise of generative AI. “We are seeing adoption of process-specific solutions across a variety of use cases and business areas. This will, ultimately, lead to an even greater need for consistent, aligned and accurate data across the entire enterprise.”

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Key Findings

• Generative AI adoption is already well underway
  • Nearly half (45%) of data leaders reported they’ve already implemented generative AI, with an additional 53% who anticipate they will, including 36% who expect to within the next two years

• Data quality continues to be a major hurdle to generative AI adoption
  • Nearly all (99%) 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%)

• Despite challenges to generative AI implementation, the juice will be worth the squeeze
  • 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% of data leaders reported that improving readiness of data for AI and analytics is the most common metric to measure data strategy effectiveness, a shift from our 2023 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 data leaders 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%)

• Investment in generative AI is driving mutual investment in data management
  • Data leaders cited the ability to deliver reliable and consistent data fit for generative AI (39%) and improving data-driven culture and data literacy (39%) as 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
  • Data privacy and protection (45%), data quality and observability (41%), and data integration and engineering (37%) remain top data management capabilities to invest in to support these priorities

These findings emphasize the intrinsic connection between generative AI adoption and sound data management strategies, and the increased priority data leaders around the world have placed on both in the year ahead. While this new era of AI promises plenty of potential, it guarantees increased complexity for enterprises and data leaders, from the management of disparate and evolving data ecosystems to the countless data and organizational roadblocks to implementation. As the report states: “With AI and data management, data leaders can recognize that it is not one driving the other, but rather that the two go hand in hand – and making the most of both means transformative change for these technologies, leaders’ strategies, and the future of their organizations.”

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