This week, our hosts Nick Woo, Rehgan Bleile, and Brendan Kelly celebrate their 20th episode with a reflection on AI advancements in 2024 and predictions for 2025.

In this episode, the team dives into the diverse maturity levels of enterprise AI adoption, from early experimentation to large-scale deployment, the role of executive buy-in, and collaboration between business and technical teams. They highlight the rise of AI agents, growing reliance on data quality, and the shift toward optimization and governance as enterprises consolidate tools and processes. Looking ahead, they predict faster deployment cycles, deeper integration of AI into workflows, and a focus on user-centered design.

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On this episode, we welcome Bhavna Mehta, Assistant Vice President of Data and Analytics at Cincinnati Children’s Hospital Medical Center. Bhavna leads initiatives in data governance, AI governance, analytics, and business intelligence, leveraging her technical expertise and strategic insight to bridge the gap between innovation and practical implementation in healthcare.

We explore the critical role of AI ethics and governance in healthcare, focusing on explainability, trustworthiness, and alignment with organizational values. Additionally, we discuss how fostering a culture of data-driven innovation empowers organizations to adopt AI responsibly and effectively. Finally, we examine the transformative potential of AI when strategically aligned with priorities like improving patient care, reducing clinician burnout, and accelerating research impact.

Bhavna Mehta

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This week, our hosts Nick Woo, Rehgan Bleile, and Brendan Kelly return for a special Q&A episode, addressing listener questions about AI adoption and governance in large enterprises. They explore how organizations balance AI innovation with practical implementation, focusing on integrating AI into existing systems while managing data privacy and security.

The hosts dive into how enterprises can approach AI use case prioritization, weighing internal applications against more complex, customer-facing solutions. They also discuss the shift from building AI in-house to purchasing specialized solutions for greater efficiency. Additionally, they highlight the critical role of governance, including AI Centers of Excellence (COEs) and committees, in overseeing and guiding AI initiatives.

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