Cloudera's State of Enterprise AI and Modern Data Architecture report revealed that although most enterprises (88%) are adopting AI, many still lack the necessary data infrastructure and employee skills to maximise its benefits.
Top barriers and use cases
Among the top barriers to adopting AI were security and compliance risks (74%), lack of proper training or talent (38%), and the cost of AI tools (26%).
According to the report, AI's top use cases were improving customer experiences (60%), increasing operational efficiency (57%), and expediting analytics (51%).
Managing data
The study also revealed that the majority (94%) of respondents said that they trust their data, but over half (55%) find it challenging to access all of their company's data due to contradictory datasets (49%), an inability to govern data across platforms (36%), and too much data (35%).
"For the majority of companies, the quality of their data is not great; it's distributed across various infrastructures and not documented efficiently, and we're seeing the fallout from that presented in the challenges identified by the survey," said Cloudera's chief strategy officer, Abhas Ricky.
"Managing data where it resides is the most important thing when adopting AI - being able to run models cost-efficiently where that data already lives. Instead of bringing the data to the models, enterprises are starting to realise the advantages of bringing AI models to their data."
