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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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