Crawl, Walk, and Run on How to be AI Ready with Peter Kromhout and Mariam Halfhide
Apr 18, 2024
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Peter Kromhout and Mariam Halfhide share insights on becoming AI Ready. They discuss aligning strategy and data quality, navigating data management, and implementing AI. The conversation also covers the shift to generative AI, ethics in data initiatives, and the path to AI readiness.
AI readiness requires alignment of data and business strategies to support organizational goals.
High-quality foundational data is essential for accurate AI outputs, necessitating proper data management and quality control measures.
Collaboration among IT, data analytics, and business teams is crucial for developing a strong foundation for AI readiness, emphasizing accountability and transparency in AI deployments.
Deep dives
Importance of Data Foundation and Strategy Alignment
To become AI-ready, the importance lies in having a strong alignment between data and business strategies. Understanding the business questions and goals is key, as AI is a means to an end, supporting the organization's mission alongside productivity and efficiency.
Building the Essential Data Foundation
Having a solid data foundation is crucial for successful AI implementation. Proper data management, data quality, source verification, semantic interpretation, and feature development are vital components. Garbage in, garbage out principle applies, necessitating high-quality foundational data for accurate AI outputs.
Collaboration and Use Case-Driven Approach for AI Readiness
Collaboration among IT, data analytics, and business teams through a use case-driven approach fosters a holistic understanding. Capturing information like meanings, relationships, semantics, and quality expectations is key in developing a strong foundation for AI readiness.
Accountability and Ethics in AI Deployment
Accountability becomes paramount in AI deployments, especially with the rise of generative AI. Transparency, ethics, and responsibility are mandatory considerations integrated into data and AI strategies to address potential misuse and negative impacts.
Continuous Learning and Resource Recommendations
Embracing continuous learning and pushing boundaries through collaboration is essential in navigating AI readiness challenges. Resources like LinkedIn for curated content and Center for Humane Technology for insightful materials offer valuable insights for professionals in the field.
Everyone wants to be doing AI and we know that data is at the center. So, how do we become AI Ready? Tim and Juan chat with Peter Kromhout and Mariam Halfhide from Xebia to discuss strategies and techniques to become AI Ready.
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