Why data fragmentation is becoming a business problem, not just a technical one (www.techradar.com)

A recent analysis from Gartner highlights that an alarming 60% of AI projects lacking "AI-ready" data are expected to be shelved by 2026, emphasizing that the issue is not merely technical but fundamentally business-related. Data fragmentation occurs when critical information is dispersed across various systems and formats, hampering decision-making and delaying AI initiatives. Instead of treating it as an IT concern, organizations must recognize how this fragmentation impacts strategic decisions and collaborations, ultimately stalling projects and costing time and resources. Innovative companies are shifting away from traditional approaches that rely on data consolidation and are embracing collaborative data environments powered by privacy-enhancing technologies (PETs). These methods enable organizations to extract insights from each other's data without needing to pool sensitive information. For instance, a Swiss bank and a publisher effectively targeted advertising audiences without exposing their data, resulting in significant cost reductions. This shift underscores a crucial evolution in the AI/ML landscape: organizations that prioritize collaborative strategies over exhaustive data ownership are poised to leverage existing insights more effectively, allowing them to act swiftly in a competitive market.