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Healthcare can’t be technologically ready for AI until it’s emotionally ready first.

In this episode of The Signal Room, host Chris Hutchins sits down with Susie Brannigan — a trauma-informed nurse executive, Just Culture leader, and AI ethics advocate — to explore the human readiness gap in healthcare transformation.

Susie explains why trust must be rebuilt before new systems (Epic, AI, automation) can succeed, and how leaders can shift culture from blame to learning, from burnout to belonging. Drawing from real unit experience and frontline realities, she breaks down what emotionally safe leadership looks like during implementation, why “pilot” language often erodes credibility, and how Just Culture + trauma-informed leadership create the psychological safety required for change.

We also discuss where AI can genuinely help clinicians (and where it can go too far), including guardrails for empathy, presence, and patient-facing AI interactions. If you’re leading digital transformation, managing workforce fatigue, or trying to implement AI without losing your people, this conversation is a practical guide.

Key topics covered

• The human readiness gap: emotional readiness before technological readiness
• Trust erosion in healthcare leadership and why it blocks adoption
• Epic implementation lessons: skill gaps, overtime, and unit-level support
• What Just Culture is and how it reduces fear and turnover
• Trauma-informed leadership and psychological safety on high-acuity units
• Emotional intelligence alongside data literacy as a core leadership skill
• Designing AI with empathy, guardrails, and clinical accountability
• Practical advice for leaders: rounding with purpose, supporting staff, choosing sub-leaders

Chapters

00:00 Emotional readiness and the human readiness gap
01:10 Why implementations fail without trust
07:20 Epic vs AI: why this shift feels different
09:10 What Just Culture is and why it works
11:20 Trauma-informed leadership and secondary trauma
19:40 Emotional intelligence in tech-driven environments
22:10 AI, empathy, and guardrails for patient-facing tools
29:30 Coaching and simulation: preparing nurses for crisis care
34:40 Leadership advice for AI-era change
38:20 How to connect with Susie Brannigan
42:10 Closing

Connect with Susie Brannigan

• LinkedIn: Susie Brannigan
• Business page: Susie Brannigan Consulting
  (Susie shares culture assessments, Just Culture training, trauma-informed training, and leadership support across healthcare and other industries.)

If this episode resonated, share it with a leader who’s trying to implement change without losing trust. The future of healthcare transformation depends on psychological safety.

Stay curious. Stay human.

#JustCulture #HealthcareLeadership #AIinHealthcare

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In this insightful episode of The Signal Room, Chris Hutchins sits down with Amit Shivpuja, Director of Data and AI Enablement at Walmart, to delve into the critical role of ethical leadership and responsible AI in building trust for successful AI adoption. Recorded live at the Put Data First Conference in Las Vegas, they discuss why trust forms the foundation for scaling AI technologies effectively.

Amit emphasizes that AI can only reach its potential when supported by trustworthy data, explaining that 'garbage in is garbage squared out,' highlighting the risks of bias amplification. The conversation covers how early stakeholder involvement and human oversight are essential components of responsible AI strategies. Amit also addresses workforce concerns by advocating transparent communication about AI's impact and upskilling.

Listeners will gain valuable insights into how healthcare leadership, AI ethics, and AI readiness intersect to create scalable, trustworthy AI systems. This episode is a must-listen for leaders and innovators aiming to integrate ethical AI principles into their business strategy.

Connect with Amit on LinkedIn, explore his book 'The Data and AI Compass,' and follow his Substack for deeper insights into AI governance and data strategy.

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As AI adoption accelerates, cybersecurity risk is evolving faster than most organizations are prepared for.

In this episode of The Signal Room, host Chris Hutchins is joined by Anita Mareedu, a network security engineer at Cadence, to explore how artificial intelligence is reshaping cybersecurity, national security, and workforce readiness.

Recorded at the Data First Conference in Las Vegas, this conversation dives into real-world cybersecurity challenges across industries, including healthcare, finance, government, and semiconductor design. Anita shares her journey from electrical engineering and VLSI research into network and application security, offering a grounded perspective on how AI both accelerates productivity and expands the attack surface.

We discuss why AI systems must be secured as aggressively as they are deployed, how the CIA triad (confidentiality, integrity, availability) applies differently across industries, and what leaders need to understand about data exposure, access controls, and compliance as AI becomes embedded into everyday workflows.

This episode is especially relevant for leaders navigating AI adoption, cybersecurity professionals managing expanding risk, and students or early-career professionals wondering how to prepare for an AI-driven future of work.

Key topics covered

• How AI is changing cybersecurity and network security
• AI risk management and agentic AI concerns
• National security implications of AI and data exposure
• Industry-specific security priorities: healthcare, finance, government
• Application security, API security, and cloud environments
• Compliance frameworks including NIST, HIPAA, and SOC
• Workforce transformation and career pathways in cybersecurity
• How to learn, adapt, and stay relevant as technology evolves

Chapters

00:00 AI, cybersecurity, and why risk is accelerating
02:50 From VLSI to network security: a career journey
07:40 Application security, APIs, and modern attack surfaces
12:30 AI productivity vs. AI security risk
15:20 National security, data exposure, and sensitive information
18:10 Industry differences: healthcare, finance, government
21:00 Workforce fear, job security, and AI transformation
24:00 Advice for students and early-career professionals
27:00 Where to start learning cybersecurity today
30:00 Closing reflections

If this conversation resonated, share it with a colleague working in AI, cybersecurity, or technology leadership. AI is here to stay. How we secure it will shape everything that comes next.

Stay curious. Stay human.

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This episode of The Signal Room dives into AI strategy and readiness, focusing on the design principles that truly matter in healthcare AI. Chris sits down with Keshavan Shashadri, Senior Machine Learning Engineer, for a grounded conversation on authentic intelligence, AI systems designed to understand context, respect human judgment, and recognize their limits.

Together, they explore why context is crucial in healthcare AI and where it often breaks down, from patient history and clinical workflows to institutional policy, regulation, and human availability. Keshavan outlines four critical layers of context necessary for building AI systems that are trusted, safe, and effective.

The discussion covers how large language models (LLMs) are not replacements for doctors, the importance of AI supporting rather than supplanting clinical judgment, and the need for human-in-the-loop checkpoints where risk is significant. It also distinguishes between transparency and true explainability in regulated environments and highlights that AI bias often arises from what it doesn't know rather than what it does.

This episode is a practical, ethical, and strategy-driven discussion on deploying responsible AI in healthcare leadership. If you're invested in healthcare ethics, AI regulation, and designing AI systems that earn trust, this conversation is essential listening.

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Summary

In this conversation, Chris Hutchins and Carol Velandia discuss the transformative impact of AI on healthcare, emphasizing the importance of language access and communication equity. Carol shares insights from her work at Equal Access Language Services, highlighting the need for ethical considerations in AI applications and the critical role of human interaction in healthcare. They explore the implications of recent legislation on language access, the necessity of integrating language services into healthcare infrastructure, and the potential of AI to enhance, rather than replace, human communication. The discussion underscores the importance of compassion and understanding in patient care, advocating for a future where technology and humanity coexist to improve healthcare outcomes.


Takeaways

AI has limitless potential but also raises concerns.
Language access is crucial for effective healthcare delivery.
Communication equity is essential for patient trust.
Legislation alone cannot change human behavior.
Language barriers can lead to severe patient safety issues.
AI should enhance human capabilities, not replace them.
Ethics in communication cannot be outsourced to AI.
Inclusion must be built into healthcare systems from the start.
Language access is a civil right that needs protection.
Effective communication is a bridge between compliance and compassion.


Titles

Navigating the AI Transformation in Healthcare
Bridging Communication Gaps with Language Access


Sound bites

"AI can expand access and make it faster."
"AI is not moral intelligence, humans are."
"Language access is a matter of patient safety."


Chapters

00:00 The Exciting Yet Scary Transformation of AI
02:40 Equal Access Language Services: Bridging Communication Gaps
05:20 Communication Equity in Healthcare
08:12 Legislation and Language Access: A Critical Discussion
11:05 The Importance of Language Access in Patient Safety
14:01 AI in Language Services: Enhancing or Replacing?
16:58 Ethics and AI: The Human Element
19:47 AI's Role in Translation and Interpretation
22:35 Designing Language Access into Healthcare Systems
25:23 The Infrastructure of Inclusion and Language Access
28:11 Final Thoughts: Compassionate Care and Language Access

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In this conversation, Danette McGilvray and Chris Hutchins discuss the ongoing challenges organizations face regarding the emphasis on data versus technology. They highlight the significant financial investments made in technology while often neglecting the data that drives it. The discussion also touches on the organic growth of systems and the need for a better understanding of data management.

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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

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In this episode of the Signal Room podcast, Chris Hutchins speaks with Dr. Larry Kuhn about the critical role of trust in leadership, especially in the context of AI transformation. They discuss the concept of 'trust tax' and 'trust dividend', the importance of psychological safety, and the need for authentic leadership in navigating change. Dr. Kuhn shares insights on how leaders can foster trust and create a supportive environment for their teams during times of uncertainty and disruption.

Read 7 Dimensions of Credible Authenticity by Dr. Kuhn

https://thehrc.com/trust-at-work-the-7-dimensions-of-credible-authenticity/

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