Stu is a technologist and entrepreneur who has been innovating and commercializing large scale model intensive production systems for over two decades.
Jun Wu, Forbes – October 9, 2020
Most of this year, enterprises have been reviewing the lessons learned in the past few years from their Enterprise AI initiatives, i.e., what has worked, what hasn’t, and how to move forward to modernize their infrastructures and take full advantage of AI. According to Garner’s recent research report, from 2018 to 2020, only around 47% of projects in enterprise organizations are in production. The rest are stuck in the pre-production phases. Many enterprises are still trying to get their AI projects into operation and contributing to the business.
What’s holding these enterprises back?
Last week, I spoke to Stu Bailey, the Co-founder and Chief Enterprise AI Architect at ModelOp, a company trying to help enterprises implement ModelOps, the key component in operationalizing enterprise AI. We caught up following a roundtable that Stu moderated in September that featured many industry leaders along with Erick Brethenoux, VP Analyst with Gartner's, and the lead for their AI research. Erick Brethenouxc introduced Gartner's Enterprise AI framework, and the panelists highlighted key challenges that Enterprises are facing.
