STEVEN KAWASUMI’S BLOG
AI Leadership Is Not One Job
AI leadership is often treated as a single category. That assumption made sense in earlier stages of adoption. In many organizations, AI leadership was concentrated in a small number of people who had the most familiarity with the[...]
Blog Series Part 3: Transforming Legacy Systems Into AI-Ready Infrastructure
Many companies struggle to adopt AI because they built themselves in and for a different era. Legacy infrastructures can process transactions and enforce consistency but were not built for systems that identify patterns, influence decisions, and increasingly participate[...]
Blog Series Part 2: The Next Era of Resilient Leadership: Guiding Organizations Through AI-Native Automation
AI-native automation is changing how work moves through organizations. When used well, it helps teams respond more quickly, operate with more context, and spend less time on repetitive tasks. For leaders, that changes what resilience requires. It becomes[...]
Blog Series Part 1: Designing Human-Centered Workflows in an AI-Augmented Enterprise
AI is transforming medicine through hyper-precise diagnoses and scalable care. The open question is whether AI can support the human side of care. According to an intriguing New York Times article, it may be closer than we think.[...]
Integrating Adaptive AI Systems into Core Business Operations
Adaptive AI is moving out of experimentation and into the center of business operations. While adoption is spreading across industries, many organizations still hesitate to integrate these systems into their core infrastructure, even as adaptive AI becomes a[...]
Knowledge Continuity as a Competitive Advantage
Organizations that consistently outperform peers often do so as a result of how they establish, preserve, and carry forward institutional knowledge. Continuity, in this sense, does not simply involve storing information; it requires building mechanisms that ensure expertise[...]
AI Leadership Is Not One Job
AI leadership is often treated as a single category. That assumption made sense in earlier stages of adoption. In many organizations, AI leadership was concentrated in a small number of people who had the most familiarity with the[...]
Blog Series Part 3: Transforming Legacy Systems Into AI-Ready Infrastructure
Many companies struggle to adopt AI because they built themselves in and for a different era. Legacy infrastructures can process transactions and enforce consistency but were not built for systems that identify patterns, influence decisions, and increasingly participate[...]
Blog Series Part 2: The Next Era of Resilient Leadership: Guiding Organizations Through AI-Native Automation
AI-native automation is changing how work moves through organizations. When used well, it helps teams respond more quickly, operate with more context, and spend less time on repetitive tasks. For leaders, that changes what resilience requires. It becomes[...]
Blog Series Part 1: Designing Human-Centered Workflows in an AI-Augmented Enterprise
AI is transforming medicine through hyper-precise diagnoses and scalable care. The open question is whether AI can support the human side of care. According to an intriguing New York Times article, it may be closer than we think.[...]
Integrating Adaptive AI Systems into Core Business Operations
Adaptive AI is moving out of experimentation and into the center of business operations. While adoption is spreading across industries, many organizations still hesitate to integrate these systems into their core infrastructure, even as adaptive AI becomes a[...]
Knowledge Continuity as a Competitive Advantage
Organizations that consistently outperform peers often do so as a result of how they establish, preserve, and carry forward institutional knowledge. Continuity, in this sense, does not simply involve storing information; it requires building mechanisms that ensure expertise[...]