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 focused on the importance of AI professionals having some foundation in science discipline as a cornerstone for designing and developing AI models and production processes, and explored value of computing science, the richness of complexity sciences and the value of physics to appreciate the importance of integrating diverse disciplines into complex AI programs - key for successful returns on investments (ROI). This blog discusses key AI and machine learning (ML) terms that every board director and CEO must know to stay relevant and advance their duty of care. If you want a good starter on the responsibility and duty of care, I recommend you read my earlier blog here. In the Brain Trust Series, I have identified over 50 skills required to help evolve talent in organizations committed to advancing AI literacy.

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.

We are currently focused on the technical skills in the AI Brain Trust Framework advancing the key AI and machine learning literacy terms.

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 blog yesterday discussed three key basic concepts to answer: what is AI?, what is an algorithm?, and what is an AI Model? I will continue in the next two blogs to define other key AI concepts and definitions that I believe every CEO or board director must master at the basic AI proficiency levels. After all, how can you lead if you don't know your basics in one of the most significant disruptors of our lifetime. If you want a good starter on the responsibility and duty of care of C suite leadership on AI, I recommend you read my earlier blog here.

Mathematics Literacy is a key skill for Board Directors and CEO's to ensure Artificial Intelligence ... [ ] foundations of excellence and ensure Duty of Care. 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 CEOs 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. In the last two blogs, the focus has been on Mathematics Literacy, which is one of the ten technical skills to develop in building a strong foundation of AI Literacy in board directors and in CEO's to lead and govern AI effectively and efficiently.

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.

Leadership in AI requires seeing the horizon and planting poles clearly to guide those who follow. This blog is a continuation of the Building an AI Leadership Brain Trust Blog Series which targets board directors to accelerate their duty of care to develop stronger skills and competencies in AI. Either modernize or atrophy is a reality for laggard companies not preparing to compete in the increasingly intelligent world, where sensors and AI methods will be embedded in every business process. Over 80% of the companies investing in AI do not drive ongoing operational practices, rather AI is an investigative approach used to answer difficult questions, but unfortunately sustaining sponsorship to sustain the AI models, in many cases, simply dies off. I have identified over 40 overall skill domains in the AI Leadership Brain Trust Framework, and you can see the full roster, see my first blog.

Every Board Director and CEO need to accelerate their Learning in AI and Machine Learning to Manage ... [ ] Risk. Time for Something New is Now! Are you keeping informed by reading on a regular basis, here are a few guide posts to help you speed up your AI learning as a board director, CEO or senior executive striving to advance your knowledge in the Intelligence Revolution - where AI is simply everywhere! With the speed of AI content proliferating the market, and media channels growing at over 50% a years, and by 2021, over 80% of all new emerging software technologies will apply AI in some fashion in their business models, according to Gartner Group. As of August 2020, IDC reported that the AI market - including software, hardware, and services, are forecast to grow 12.3 percent to $156.5 billion in 2020. Worldwide AI revenues will surpass $300 billion in 2024 with a five-year compound annual growth rate (CAGR) of over seventeen percent.