Expertise gap dampens potential benefits of disordered data

Many enterprises are struggling to effectively leverage unstructured data to enhance operational efficiency and drive meaningful insights, despite recognising the significant potential of this resource, according to new research from Qlik.

Qlik commissioned a survey with ETR, which covered 200 directors and above in North America; Europe, the Middle East and Africa; and Asia-Pacific regions.

The survey shows that a lack of expertise and insufficient tools are major barriers, with only a small percentage of enterprises dedicating more than a quarter of their AI budget to unstructured data initiatives.

“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,” said Brendan Grady, general manager of Qlik’s Analytics Business Unit. 

“Yet, our survey highlights that nearly 70% agree their organisation is not well equipped to understand how generative AI can be leveraged on their unstructured data,” said Grady.

He said that companies are looking for solutions that enable generative AI adoption without requiring them to overhaul their existing skillsets and technology stack. 

Grady added that the opportunity is finding ways to integrate AI seamlessly into current analytics environments, allowing organisations to extract the right answers from unstructured data and drive meaningful business outcomes.

Findings also show that data privacy and compliance concerns dominate, with 59% of respondents very concerned about data privacy and 47% about regulatory compliance, significantly outweighing concerns about ROI (19%).

When evaluating vendors, system integration (55%), cost (50%), and governance features (49%) are top priorities, whereas vendor reputation is a low priority (16%). Respondents expect modest financial gains from using unstructured data, with 45% anticipating a 10%-20% improvement in their top or bottom lines.

Among those interested in using generative AI for unstructured data, two out of three respondents plan to invest in a generative AI tool for unstructured data. Despite widespread interest, only 22% of all respondents indicate they are making “significant” investments in AI technologies.

A clear majority (62%) see the opportunity in unstructured data to improve operational efficiency, while only 31% believe it can drive innovation. Nearly half (45%) describe a use-case involving better search and query tools to dig into internal documents.

There is strong agreement that traditional enterprise search tools are insufficient for maximising the value of vast document libraries. Only 16% have already purchased a tool designed to deliver insights from unstructured data, and most efforts remain in early or pilot stages.