Succeeding with AI: How to make AI work for your business
by Veljko Krunic. He holds a PhD in Computer Science from University of Colorado Boulder. Today he is CEO of Health Saver AI and holds two AI patients.
Based upon the AI books I have been reading, none certainly addresses the business side of AI. Veljko is writing this book for business leaders. At first glance one may believe technology project managers would be a target audience. This is perfect for business leaders and analysts with no AI programming.
For any business seeking to define investments for data driven decision making, this is a worth title to read. The approach is completely a business approach to AI projects, how they are different and when to fail quickly early in a project.
In addition, Veljko’s underlying message for business teams is the profit is the resulting data outcomes, as it seems almost every business seeking to gain an upper hand have already kickstarted small AI projects. Veljko certainly helps leaders understand the foundation requirements (developers, and data scientists) required to succeed.
The hard requirements for AI if overlooked, will not be enough to prove a business case and result in wasted investments. This is along the lines of The Myth of Artificial Intelligence Why Computers Can’t Think the Way We Do by Erik Larson.
Take the CLUE
Veljko brings the acronym CLUE is introduced early to address Consider available business actions – Link research question and business problem – Understand the answer, and Economize resources. CLUE will certainly appeal to business leaders.
In fact, companies of all sizes and markets are initiating AI projects, investing vast sums of money on software, developers, and data scientists. Too often however, these AI projects focus on technology at the expense of actionable or tangible business results, resulting in scattershot results and wasted investment.
Succeeding with AI delivers a blueprint for AI projects to ensure they are predictable, successful, and profitable. Furthermore, Veljko delivers practical techniques to run data science programs. Also, he ensures a cost effective and focused approach to establishing the right business goals.
Succeeding with AI certainly delivers a business framework to plan and monitor efficient and effective AI solutions. Veljko is clear to the warning signs of failed AI projects. In addition, this type of business solution requires deep experiences with AI and ML.
In conclusion, Veljko delivers solid business lessons in order for leaders to engage AI projects. This was a very insightful and engaging book. I was impressed that the book is delivered in a straightforward business approach. This is not a book for AI technologists, but rather seasoned business leaders.