PHILADELPHIA, PA — This week, Qlik® unveiled new research that shows while enterprises recognize the enormous potential of unstructured data to enhance efficiency and generate valuable insights, many are struggling to effectively utilize this resource. The survey highlights a significant gap in expertise and insufficient tools as major hurdles. Notably, only a small percentage of enterprises allocate more than a quarter of their AI budget to unstructured data initiatives.
Brendan Grady, General Manager of Qlik’s Analytics Business Unit, emphasized the importance of unstructured data. “With many sources citing that unstructured data makes up to 80% of the world’s data, it is no surprise that enterprise leaders want more real value from this untapped source,” he said. However, nearly 70% of respondents admitted their organization is not well equipped to understand how generative AI (GenAI) can be leveraged on their unstructured data.
The survey provides a detailed look at the current landscape of AI adoption in relation to unstructured data:
- Data Privacy and Compliance Concerns: A significant majority, 59%, are very concerned about data privacy, while 47% worry about regulatory compliance. Concerns about return on investment (ROI) are less prominent, with only 19% expressing high concern.
- Vendor Evaluation Priorities: When evaluating vendors, system integration (55%), cost (50%), and governance features (49%) top the list of priorities. In contrast, vendor reputation is a low priority for just 16% of respondents. Expected financial gains from unstructured data usage are modest, with 45% anticipating a 10%-20% improvement in their financial metrics.
- Interest vs. Investment in GenAI: While there is considerable interest in using GenAI for unstructured data—two out of three respondents plan to invest in such tools—only 22% report making significant investments in AI technologies.
- Operational Efficiency and Innovation: A majority (62%) view unstructured data as a key driver for operational efficiency. However, only 31% see it as a catalyst for innovation. Nearly half (45%) cite improved search and query tools for internal documents as a primary use case.
- Traditional Search Tools Falling Short: Traditional enterprise search tools are deemed inadequate for extracting value from vast document libraries. Only 16% have purchased specialized tools designed for unstructured data insights, with most efforts still in early or pilot stages.
Erik Bradley, Chief Strategist & Director of Research at Enterprise Technology Research, commented on the survey’s findings. “The gap in expertise needed to harness the full potential of generative AI for unstructured data is a critical challenge facing enterprises today,” he noted. “While the appetite for leveraging unstructured data is high, the lack of specialized skills and appropriate tools is a significant barrier. Organizations must invest in bridging this knowledge gap and integrating advanced AI capabilities seamlessly into their existing analytics frameworks to truly capitalize on the opportunities presented by GenAI.”
Unlocking the Power of Unstructured Data
The implications of these findings are significant. Unstructured data, which includes emails, social media posts, and documents, represents a vast and largely untapped resource. Efficiently leveraging this data can drive operational efficiencies and yield actionable insights, yet many organizations are not equipped to do so. Failing to address these gaps could result in missed opportunities and competitive disadvantages.
Moreover, concerns around data privacy and regulatory compliance highlight the need for robust governance frameworks. As enterprises navigate the complexities of unstructured data, ensuring compliance and protecting sensitive information are paramount.
In conclusion, the Qlik survey sheds light on the significant potential of unstructured data and the challenges enterprises face in harnessing it. Addressing these barriers through targeted investments in expertise and technology will be crucial for organizations aiming to unlock the full value of their data assets. This focus on unstructured data could redefine operational efficiency and drive meaningful business outcomes in the years to come.
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