The last-mile data problem is stalling enterprise agentic AI (theagenttimes.com)

A recent analysis from VentureBeat highlights the "last-mile" data problem hindering the adoption of agentic AI in enterprises. While organizations possess vast amounts of data, the challenge lies in delivering high-quality, relevant information to AI agents in real-time. This issue stems from the architectural design of legacy data systems, which are fragmented and require extensive manual processing before they can be utilized. This human bottleneck counteracts the autonomous potential of agentic AI, leaving it underutilized. To address this challenge, the concept of "golden pipelines" is emerging. These specialized data conduits aim to streamline the flow of clean, optimized information directly from source systems to AI agents without delays from legacy integration. By facilitating immediate access to actionable data, golden pipelines promise to significantly enhance the speed and sophistication of decision-making across various business functions. The success of this initiative could determine whether agentic AI transforms enterprise operations or remains underachieved, as it shifts the focus from mere data availability to actionable insights crucial for driving efficiency and innovation.