In a recent video from Help Net Security, Lee Waskevich, VP of Security at ePlus, delves into the pressing need for enhanced governance and stricter controls when it comes to the deployment of artificial intelligence (AI), especially in the realm of data management.
The latest ePlus AI Readiness survey shed light on the top concerns regarding data among participants, with data quality ranking at 61%, data security at 54.5%, and data governance at 52%. These findings underline the critical importance of implementing a robust data management strategy to address these issues effectively.
For organizations looking to successfully launch AI initiatives, the first step is to identify the pertinent data for each AI objective, pinpoint its location, dismantle data silos, and ensure proper tagging and governance protocols are in place. This alignment is pivotal in guaranteeing secure AI deployment and fostering positive business outcomes.
As the field of AI continues to evolve and expand, the need for a more stringent approach to governance becomes increasingly evident. With data playing a pivotal role in AI operations, organizations must prioritize data quality, security, and governance to navigate the complexities of AI deployment successfully.
Looking ahead, the onus lies on organizations to invest in robust data management practices, prioritize data security, and establish clear governance frameworks to harness the full potential of AI while mitigating associated risks. By adopting a proactive stance towards data management and governance, organizations can unlock new opportunities for innovation and growth in the AI space.