The AI Shift: How Leaders Can Avoid Falling Behind? | Dr. Steven Miller

What makes some research organizations produce meaningful, high-impact work while others struggle, even with talent and resources?In this episode of Why Research Matters, Varunika Goyal speaks with Professor Steven Miller, Professor Emeritus of Information Systems at Singapore Management University and founding dean of SMU’s School of Computing and Information Systems. Drawing on his experience across academia, industry, government, Carnegie Mellon University, Fujitsu, and SMU, Professor Miller explains how research cultures are built, why feedback systems matter, and what leaders can do to help researchers do their best work.The conversation explores research leadership, innovation, grant strategy, interdisciplinary collaboration, post-COVID work culture, AI as a collaborator, automation vs augmentation, quality control, and why skeptical voices are essential when adopting powerful new tools.Subscribe to Why Research Matters for conversations with researchers, educators, and leaders about the work behind discovery.#ResearchLeadership #ArtificialIntelligence #WhyResearchMatters00:00 Introduction to Professor Steven Miller01:27 What creates impactful research?02:07 Why research environments matter04:41 Leadership, feedback, and innovation culture05:28 Lessons from SRI International07:59 Why polished work is not enough11:43 AI tools and the need for better critique12:27 Early feedback vs polished research16:24 Research funding and creative partnerships19:16 Building SMU’s computing school25:17 Choosing new research areas strategically29:19 The dean as “chief enabler”31:38 Bureaucracy, grants, and research infrastructure35:30 COVID and institutional resilience39:27 Work from home, hybrid work, and collaboration41:45 Serendipity and hallway conversations43:31 Yin-yang tensions in research and AI45:35 AI errors, validation, and feedback systems46:04 AI as a collaborator47:18 Are organizations adopting AI fast enough?51:41 Augmentation vs automation53:36 Why automation needs control58:28 Should everyone use AI tools?1:04:32 Why skeptics matter in AI adoption1:08:30 Responsible innovation and risk1:10:21 AI dashboards, usage, and quality1:12:19 Quality control in the age of AI