This blog is a continuation of the Building AI Leadership Brain Trust Blog Series which targets board directors and CEO's to accelerate their duty of care to develop stronger skills and competencies in AI in order to ensure their AI programs achieve sustaining results. My last two blogs introduced value of science and stressed its importance to AI, and focused on the importance of AI professionals having some foundation in computing science as a cornerstone for designing and developing AI models and production processes, as well as the richness of complexity sciences and appreciating that integrating diverse disciplines into complex AI programs is key for successful returns on investments (ROI). This blog introduces the importance of physics and explores its relationship to AI as often I see AI solutioning teams missing physics skills in the solutioning constructs - which I believe is a strategic mistake for many complex AI programs. Its important for C levels to understand that AI is not a singular discipline it requires many other skills to get the solution architecture right. So deeply understand the business problem in front of you - and the more complex the problem is the increased value physicists will have in guiding you forward.

In my last blog on board director and CEO leadership needs, I identified a series of AI leadership questions to advance AI successfully and introduced basic AI concepts such as defining basic terms like: AI, algorithm, AI model. I also described different AI model methods like: unsupervised learning versus supervised learning to provide some foundational concepts that every board director or CEO should understand. If you want a good starter on the responsibility and duty of care of C suite leadership on AI, I recommend you read an earlier blog here. Over the past six months in the AI Leadership Brain Trust Series, I have identified over 50 skills required to help evolve talent in organizations committed to advancing AI literacy. The last few blogs have been discussing the technical skills relevancy.

This blog is a continuation of the Building AI Leadership Brain Trust Blog Series which targets board directors and CEO's to accelerate their duty of care to develop stronger skills and competencies in AI in order to ensure their AI programs achieve sustaining results. My last two blogs introduced value of science and stressed its importance to AI, and focused on the importance of AI professionals having some foundation in computing science as a cornerstone for designing and developing AI models and production processes, as well as the richness of complexity sciences and appreciating that integrating diverse disciplines into complex AI programs is key for successful returns on investments (ROI). This blog introduces the importance of physics and explores its relationship to AI as often I see AI solutioning teams missing physics skills in the solutioning constructs - which I believe is a strategic mistake for many complex AI programs. Its important for C levels to understand that AI is not a singular discipline it requires many other skills to get the solution architecture right. So deeply understand the business problem in front of you - and the more complex the problem is the increased value physicists will have in guiding you forward.

What is the relevance of complexity science to AI as a discipline? You do not see enough mention of complexity science in relationship to AI competency development. This really surprises me as complexity science is all about the traversing of disciplinary boundaries and occurs both within and between multiple systems. Complexity sciences have emerged through interdependent and overlapping influences from diverse fields, including concepts from: physics, economics, biology, sociology and computer science. Complexity sciences strive to understand relevant "system" phenomenon that is characterized by changes, and unpredictability. A "system" is a set of connected or interdependent things or agents (such as a person, a molecule, a species, or an organization).

User Centered Design (UCD) - diverse and inclusive teams are key to AI solutioning success. This blog is a continuation of the Building AI Leadership Brain Trust Blog Series which targets board directors and CEO's to accelerate their duty of care to develop stronger skills and competencies in AI in order to ensure their AI programs achieve sustaining results. In this blog series, I have identified forty skill domains in an AI Leadership Brain Trust Framework to guide board directors and CEO's to ensure they can develop and accelerate their investments in successful AI initiatives. You can see the full roster of the forty leadership Brain Trust skills in my first blog. Each of the blogs in this series explores either a group of skills or does a deep dive into one of the skill areas.

This blog is a continuation of the Building AI Leadership Brain Trust Blog Series which targets board directors and CEO's to accelerate their duty of care to develop stronger skills and competencies in AI in order to ensure their AI programs achieve sustaining results. In this blog series, I have identified forty skill domains in an AI Leadership Brain Trust Framework to guide board directors and CEO's to ensure they can develop and accelerate their investments in successful AI initiatives. You can see the full roster of the forty leadership Brain Trust skills in my first blog. Each of the blogs in this series explores either a group of skills or does a deeper dive into one of the skill areas. I have come to the conclusion that to unlock the last mile of AI value realization that board directors and CEOs must accelerate building a unified brain trust (a unified set of leadership skills that are hardwired in relevant digital literacy and AI skills) to modernize their organizations more rapidly.

This blog is a continuation of the Building AI Leadership Brain Trust Blog Series which targets board directors and CEO's to accelerate their duty of care to develop stronger skills and competencies in AI in order to ensure their AI programs achieve sustaining results. In this blog series, I have identified forty skill domains in an AI Leadership Brain Trust Framework to guide board directors and CEO's to ensure they can develop and accelerate their investments in successful AI initiatives. You can see the full roster of the forty leadership Brain Trust skills in my first blog. Each of the blogs in this series explores either a group of skills or does a deeper dive into one of the skill areas. I have come to the conclusion that to unlock the last mile of AI value realization that board directors and CEOs must accelerate building a unified brain trust (a unified set of leadership skills that are hardwired in relevant digital and AI skills) to modernize their organizations more rapidly.