Mastering AI: Designing and Implementing Effective Data Strategies
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Descripción
#dataanalytics #datascience #ai Episode #793 of CXOTalk features a conversation on data management and Artificial Intelligence (AI) with esteemed guests, Dr. Inderpal Bhandari and Dr. Anthony Scriffignano. Dr. Inderpal Bhandari...
mostra másEpisode #793 of CXOTalk features a conversation on data management and Artificial Intelligence (AI) with esteemed guests, Dr. Inderpal Bhandari and Dr. Anthony Scriffignano.
Dr. Inderpal Bhandari holds the position of Global Chief Data Officer at IBM. In his role, he is instrumental in optimizing data utilization within the organization, focusing on integrating AI technologies to align data strategy with business objectives.
Dr. Anthony Scriffignano, former Chief Data Scientist at Dun & Bradstreet, is currently a Distinguished Fellow at the think tank, The Stimson Center. He has an extensive background in AI, with a particular emphasis on data quality, and its critical role in implementing viable AI solutions that are congruent with business requirements.
In this episode, the discussion explores using data in AI initiatives, the importance of data quality, and strategies to ensure that AI initiatives are constructive and aligned with business goals. The conversation also addresses the practical integration of AI in organizational operations, including technological considerations, human resources, and the cultivation of an enabling culture.
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Read the complete transcript: https://www.cxotalk.com/episode/mastering-ai-designing-and-implementing-effective-data-strategies
Specific topics include:
► About Inderpal Bhandari
► About Anthony Scriffignano
► The relationship between data and AI
► How to align data strategy with business objectives
► Focus on strategy first and technology tools later
► Comparing business and technological challenges
► Alignment challenges business and technology domains
► The role of technologists as change agents in organizational alignment
► Managing and selecting technology to solve data and AI challenges
► Challenges in AI-enabled initiatives
► Costs of not implementing governance or data quality in AI projects
► Differences between generative AI and more traditional AI projects
► Advice to business and technology leaders on data and AI
This insightful dialogue offers valuable perspectives for individuals seeking a deeper understanding of the relationship between data management and Artificial Intelligence in a large-scale corporate environment.
Información
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Organización | Michael Krigsman |
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