Recently, with the rapid development of artificial intelligence (AI) technology, the importance of data management has become increasingly prominent. Although the AI boom has not yet brought a large number of successful real-world cases, multiple studies show that good data management and high-quality data are the foundation for achieving AI goals.
The "2024 Data Complexity Report" released by NetApp shows concerning findings from a survey of 1,300 technology and data executives worldwide. The survey found that companies investing in data unification have a competitive advantage in achieving AI goals, with nearly 80% of respondents recognizing the importance of unified data in reaching ideal AI outcomes.
The report also noted that about two-thirds of companies stated that their data is "fully or mostly optimized for AI," meaning this data is accessible, accurate, and well-documented. However, 40% of executives believe that investment in AI and data management will significantly increase in the next two years.
Another report released by data management and analytics provider Qlik revealed some reasons hindering AI progress. Among the 4,200 executives surveyed, a lack of AI skills and challenges in data governance were seen as the main obstacles, each accounting for 23%. Additionally, a relatively high percentage reported issues with deployment and budgeting after AI development, as well as a lack of trustworthy data. Qlik's report emphasizes that building trust is crucial for widespread AI success, with 37% of executives expressing a lack of trust in AI, and 61% believing this trust deficit is impacting their AI investments.
Finally, Ataccama's "Data Trust Report" also highlights the importance of data management in AI practices. The company collaborated with Hanover Research to survey 300 executives from the United States, Canada, and the United Kingdom. The results showed that 51% of executives believe improving data quality and accuracy is a top priority, while 30% face challenges in managing large volumes of data.
Having a high-quality and reliable data management system is crucial for the successful implementation of AI. Additionally, issues such as skills, deployment, trust, and budgeting are challenges that cannot be overlooked. The role of data in the future of AI should not be underestimated.
Key Points:
🔑 80% of executives recognize the importance of unified data in achieving AI goals.
📊 37% of executives lack trust in AI, and this trust deficit affects AI investments.
📈 51% of executives believe improving data quality is the current top priority.