Eunice Abora is a Senior GRC Consultant and Information System Security Officer. Her work spans government, healthcare, education, and financial services, which means the systems this book describes are ones she assesses day to day rather than reads about. She is the founder of Unlimited SkiesTech and a PhD candidate in Information Technology, specializing in AI risk management.
She has spent years teaching governance, risk, and compliance to professionals in more than 15 countries. AI is the newest thing to land on their desks, and it arrived before the training did. Organizations are adopting these systems now, which leaves the people accountable for them facing a question nobody has answered yet: how do you govern something you have never seen?
Eunice’s first degree was in Zoology, from the University of Buea in Cameroon. She later earned a Master’s in Information Technology from the University of Maryland Global Campus.
She is now a PhD candidate in Information Technology, specializing in risk management and AI governance.
A science degree, a technology degree, and doctoral work in risk. It is an unusual combination, and it is why this book treats a model’s performance claim as a result to be examined rather than a number to be recorded.
Her path ran from zoology to a classroom, from a classroom to nursing assistance, from healthcare to database administration, from database to GRC, and from GRC to AI governance. Five starting points, none of them obvious from the one before.
Each left something behind. Science taught her to ask what the evidence actually supports. The classroom taught her that an explanation either works or it doesn’t, and the room tells you immediately. Healthcare taught her what it costs when a record about a person is wrong. Databases taught her where the numbers come from. GRC taught her what happens when nobody checks.
AI governance has not finished teaching her anything yet. That is the honest position, and it is the one this book is written from.
Because she has started over this many times, she does not treat a nontechnical background as a deficit to be apologized for. Her students are auditors, nurses, teachers, and administrators who arrived in technology the same way she did. The material is explained accordingly: concepts before terminology, terminology defined on first use, everything tied to a decision someone actually has to make.
Organizations are adopting AI faster than anyone is being trained to oversee it. The accountability lands on auditors, compliance officers, risk professionals, and the people who sign off on systems they were never taught to assess.
Almost everything written about machine learning is written for engineers. It assumes a background its readers do not have and answers questions they are not being asked.
ML & AI Literacy for GRC Professionals was written for the other side of that table. It explains how these systems are built, how they fail, and where in the pipeline governance actually sits. No programming, no data science, no prior exposure to machine learning required.
The aim is not to turn a compliance officer into an engineer. It is to make sure that when a vendor presents a number, the person responsible for approving it knows which question to ask next.
The people asked to govern AI systems are rarely the people who built them. They are auditors, compliance officers, risk professionals, and administrators with no engineering background and no technical vocabulary. Eunice’s work exists for them.
Her position is that a nontechnical background is not a disqualification. It is the ordinary condition of almost everyone who will be asked to sign off on these systems, and the material should be written accordingly.
That means understanding rather than memorization. Not “the standard requires this control,” but why the requirement exists, what risk it was written to address, and what it looks like inside a real organization. A professional who understands the reasoning can handle a situation the checklist never anticipated. One who memorized the checklist cannot.
Eunice founded Unlimited SkiesTech to teach the material she had to piece together for herself. It provides practical training in cybersecurity, GRC, privacy, risk management, and AI governance to beginners, career changers, and working professionals.
The teaching is structured instruction with practical projects, real case studies, and career preparation. The goal is a place where someone with no technical background can start, and leave able to do the work.
Before buying a book about machine learning, it is fair to want a sense of how the author explains things.
Eunice teaches live to students across more than 15 countries and speaks to general audiences about staying safe online. She produces videos, podcasts, and visual explainers with the same aim as the book.
The overview below is from her AI-GRC Foundations course. No jargon, no assumed background, every concept tied to the governance work you already do.
