Stephen Harris : What's our readiness for AI, and how do we get there?

The Praxi Pod

In this episode of the Praxi Pod, host Andrew Turner speaks with Stephen Harris, a seasoned expert in data management and AI. They discuss Stephen's extensive background in the data space, the importance of data management for AI readiness, and the impact of regulatory compliance on data practices. Stephen emphasizes the need for organizations to validate their AI outputs, understand data ownership, and the evolving role of Chief Data Officers. The conversation also touches on the significance of data curation, classification, and the future of AI in organizations.

Takeaways

• Organizations must test AI internally before external deployment.
• Data management is crucial for AI readiness.
• Regulatory compliance drives better data practices in industries.
• AI should be used to validate and improve data quality.
• Education on AI and data management is still lacking.
• Data ownership issues can create internal conflicts.
• The role of Chief Data Officers is evolving and critical.
• Data curation and classification are foundational responsibilities.
• Metadata management is essential for data confidence.
• The future of AI will see a shakeout based on data quality.

Chapters

00:00 Introduction to Stephen Harris and His Journey

02:47 The Importance of Data Management and AI Readiness

05:54 Regulatory Compliance and Its Impact on Data Management

09:04 The Role of AI in Data Validation and Customer Experience

12:10 Understanding AI and Machine Learning in Business

14:54 The Need for Education in AI and Data Management

18:00 Validating AI Outputs and Managing Edge Cases

20:47 The Challenges of Data Ownership and Governance

24:05 The Role of Chief Data Officers in Organizations

27:08 The Future of AI and Data Management Roles

29:52 Data Curation and Classification in the AI Era

32:49 The Importance of Metadata and Data Quality

35:55 The Future of AI and Its Impact on Organizations