DataOps.live Field CTO Keith Belanger looks at 5 steps to get AI-Ready Data
Now that AI is a board-level topic, organizations are rushing to achieve successful outcomes, but enabling that success requires planning. According to Gartner, more than 60% of AI projects fail to deliver on business SLAs and are often abandoned because of poor data quality, weak governance, or lack of contextual relevance. While AI/ML models receive much of the attention, the truth is that they are only as good as the data that feeds them. If organizations can’t trust their data, they can’t trust their AI.