Employers are increasingly adopting artificial intelligence (AI) technologies and generative AI platforms, but there are concerns about breaking down data silos that hold sensitive employee information. HR stakeholders question whether these technologies will effectively integrate data that is often stored in separate legacy systems. While siloed data holds valuable insights about employee experience and behavior, analysts caution that not all siloed data is useful or necessary to leverage AI effectively. HR leaders should focus on identifying the purpose of AI implementation and select the relevant data accordingly. The complexity of siloed data structures is further exacerbated when different departments purchase tools without considering their compatibility with other systems in the IT enterprise. This lack of coordination and organization within companies leads to fragmented data and prevents data consolidation.

Regulatory and compliance rules, as well as insufficient attention to tech stacks, have also contributed to the proliferation of data silos. Establishing a collaborative company culture can facilitate finding solutions to the siloed data problem, but executives often exhibit distrust and reluctance to share data due to concerns about control. According to a Zendesk report, only 22% of business leaders said their teams effectively share data. However, some companies, like Ask-AI, are working to aggregate employee data from various systems to provide insights for executives. Ask-AI's generative AI software solution connects to multiple enterprise work systems, but it does not access sensitive data like payroll applications. The company aims to gradually break down more siloed repositories of employee data, starting with customer-facing teams and expanding to other departments and HR applications.