In KDnuggets, Oleg Royz, VP Retail and Distribution at DataArt, outlines strategies for overcoming data maturity challenges and accelerating AI adoption.
“Despite the undeniable potential of AI, many enterprises need help scaling AI-enabled use cases due to data-related hurdles. As organizations embark on ambitious AI initiatives, they often encounter significant roadblocks that hinder timely implementation and widespread adoption. Organizations must prioritize data maturity to navigate these challenges and fully realize the potential of AI.”
“Data maturity refers to an organization's ability to effectively manage, govern, and utilize its data assets. It encompasses data quality, governance, integration, and analytics capabilities. A lack of data maturity can lead to several challenges that hinder AI adoption and scalability.”
“With a deployed AI-powered system, IT can focus its resources on empowering users to independently navigate and derive insights from their company's data. Enabling this transition requires a fundamental shift in IT's role, moving from gatekeepers to partners in fostering collaboration and innovation.”
You can read the full article here.
