Many organizations spend a lot of time, money and political equity trying to define an artificial intelligence (AI) strategy instead of focusing on business problems. Moving from “I want to use AI” to a tactical approach aimed at practically and sustainably solving business problems, while managing expectations, does not require superpowers. CIOs can follow these five steps to pursue an AI strategy in a pragmatic fashion.
Erick Brethenoux
VP Analyst
Erick Brethenoux is a Key Initiative leader in the AI team, responsible for managing the research agenda for AI. He specializes in machine learning, artificial intelligence and applied cognitive computing. Mr. Brethenoux guides organizations on the strategic, organizational and technology aspects of using advanced analytics as a driving force of their growth. In particular, his research focuses on the deployment of machine learning insights through integration with advanced analytics solutions, data science and next-generation, decision-making and management systems (decision intelligence).
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Wednesday, 23 June, 2021 / 02:45 PM - 03:15 PM IST
(05:15 AM - 05:45 AM EDT)
A Five-Step Formula to Pragmatically Implement AI
Thursday, 24 June, 2021 / 02:45 PM - 03:15 PM IST
(05:15 AM - 05:45 AM EDT)
AI Engineering: How to Propel AI From Prototypes to Scalable Value Generators
AI engineering brings together various disciplines from across the organization to tame the AI hype while providing a clearer path to value when operationalizing the combination of multiple AI techniques (including ModelOps). AI Engineering also includes responsible AI, dealing with risk, trust, transparency, ethics, fairness, and accountability. A sound AI Engineering practice will increase organizations’ ability to move AI projects beyond pilots and prototypes into production, overcoming fatigue and skepticism, repositioning AI as a transformative and differentiating technology.