Organizations realize that simply implementing AI technologies does not guarantee business success. To extract true value from AI investments, it is crucial to tie them directly to Key Performance Indicators (KPIs) and ensure a robust data infrastructure is in place. The difference between successful and stalled AI projects often lies in focusing on the right opportunities and context, rather than merely adopting the latest models or tools.
Data quality and governance are critical for scaling AI initiatives and achieving a positive ROI. As businesses transition from experimentation to deploying AI for real business results, they need to prioritize their data strategies. By fostering an environment of collaboration and clear data ownership, organizations can create context-powered AI solutions that drive pragmatic value.
👉 Pročitaj original: CIO Magazine
