Empowering People to Thrive with AI
AI Transformation Leader • Author • Doctoral Researcher
Sharing practical research and real-world lessons on responsible AI adoption, trust, and ethics.
How You AI
AI Transformation Leader • Author • Doctoral Researcher
Sharing practical research and real-world lessons on responsible AI adoption, trust, and ethics.
How You AI
Scholar-practitioner bridging AI research, enterprise transformation, and ethical implementation
Dr. Elizabeth Volini is a leader in enterprise AI transformation, combining deep technical expertise with hands-on experience driving responsible adoption at scale in large organizations.
Her doctoral research at DePaul University examined AI bias in hiring decisions, developing practical frameworks for building calibrated trust in AI systems through psychological inoculation and explainable AI techniques.
Prior to her AI leadership roles, Elizabeth built expertise spanning data center operations, global IT infrastructure program management, and cybersecurity. She has also been involved in initiatives supporting women in technology and is author of THE AI PLAYBOOK FOR EVERYONE.
DePaul University, 2026 • Research on AI Bias & Trust in High-Stakes Decisions
Director of AI Product Engagement • Former Infrastructure & IT Program Management Leader • Data Center Operations & Cybersecurity Expertise
THE AI PLAYBOOK FOR EVERYONE • Grace Hopper Conference • Industry Keynotes & Workshops
Contributing original scholarship to the intersection of AI ethics, human decision-making, and organizational trust
DePaul University Driehaus College of Business, 2026
AI systems in high-stakes decisions (like hiring) can perpetuate bias, yet users often over-trust algorithmic recommendations without questioning them—a phenomenon called automation bias.
A controlled experiment with 226 participants testing whether explainable AI (XAI) counterfactuals combined with psychological inoculation training enables users to detect and challenge AI bias across 8 protected categories.
Inoculation training—teaching users to recognize weak algorithmic reasoning before they encounter it—enables calibrated trust: appropriately trusting accurate AI while questioning biased recommendations.
Organizations can strengthen responsible human–AI collaboration with clear audit signals, brief user training, and well-defined escalation protocols.
Experience inoculation training for yourself by taking a look at the videos used in this experiment:
Keynotes, panels, and talks on responsible AI, trust, and the human side of adoption
How leaders turn responsible AI principles into everyday decision-making—governance, accountability, and risk-aware workflows.
Research-backed approaches for detecting bias and avoiding automation bias in high-stakes decisions like hiring and performance reviews.
What helps people embrace (or resist) AI at work—psychology, change management, and building confidence without hype.
A practical, audience-friendly talk on how modern AI works, where it fails, and how to use it responsibly in everyday work.
A practical guide to thriving in the age of AI—no technical background required
Coming 2026 • The AI revolution is here, and you don't need to be a data scientist to harness its power. This practical playbook demystifies AI and shows you exactly how to use it to boost your productivity, creativity, and impact.
Whether you're a business leader, individual contributor, or someone curious about AI's potential, this book gives you the frameworks, examples, and confidence to start using AI effectively today.
Weekly insights on AI adoption, leadership, and transformation from the frontlines
I write about responsible AI adoption, trust, and lessons learned from leading change in large organizations.
Read on Substack →Proven frameworks for rolling out AI at scale and driving real engagement
Moving from principles to practical implementation of responsible AI
Real stories and lessons learned from leading AI adoption efforts
Interested in a speaking engagement, media inquiry, or academic collaboration?