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What does it take to become truly AI-ready?

In this episode, I am joined by Ritu Chakrawarty. Ritu leads GenAI/AI Solutions Strategy at AbbVie

linkedin.com/in/ritu-chakrawarty

rituchakrawarty.github.io

We break down an AI readiness framework that helps organizations move from vision to real value. We explore the essentials of data readiness, AI governance, and the AI verification practices needed to keep models safe, reliable, and trusted.
If you're leading AI strategy in healthcare, this episode offers a practical roadmap for scaling AI, reducing risk, and modernizing data foundations. We discuss how health systems can improve AI adoption, strengthen machine learning governance, and build a culture that supports responsible and measurable transformation.
Topics Covered:
AI readiness and maturity
Data strategy for AI adoption
Responsible AI and governance
Scaling AI in healthcare
AI risk management and model monitoring

Keywords
AI implementation, workflow, automation bias, healthcare, misinformation, human check
Summary
This conversation delves into the critical aspects of implementing AI in healthcare, emphasizing the necessity of establishing proper workflows to mitigate risks such as automation bias. The discussion highlights the human element in healthcare and the potential dangers of relying solely on AI recommendations without adequate human oversight.
Takeaways

• If you do not set up the workflow correctly, you risk automation bias.
• Automation bias can lead to healthcare professionals overlooking critical information.
• AI can hallucinate and provide inaccurate recommendations.
• Human oversight is essential to validate AI-generated information.
• Healthcare professionals are often busy and may rely too heavily on AI.
• Misinformation can proliferate without human checks in place.
• Proper training and workflow design are crucial for AI success.
• Understanding the limitations of AI is vital for healthcare applications.
• The integration of AI should enhance, not replace, human decision-making.
• Collaboration between AI and healthcare professionals is key to effective patient care.