Causal AI: A Year of Insights and Impacts on Business Success

It is hard to believe that it has been a year since my book, Causal Artificial Intelligence Before writing the book, I was a member of Geminos Software’s leadership team for two years; however writing this book cemented my understanding of the deep value of a Causal AI and the impact it has on early adopting businesses. What I discovered in writing this book is that unless you understand what problem you are trying to solve, the business cannot prosper and gain a competitive edge.

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I have long believed that unless a software company can solve a critical pain point, it will not succeed. Throughout the authorship process I interviewed industry luminaries and Causal AI leaders.? I gained an appreciation of the potential of Causal AI as the most effective approach to help organizational leadership improve actionable decision making.?

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Before writing this book, I had authored 10 other books, many of which were best sellers.? My approach with these books was to provide business leaders and technologists with an understanding and appreciation of the potential and risk, benefits, and “traps” of emerging technologies.? My first book, for example, was Cloud Computing for Dummies which was written in 2010.? At that time cloud computing was still a mystery to many business leaders.? I clearly remember working with a major financial services company who were considering Salesforce.com (now, of course, known as Salesforce).? The company was ready to invest in the platform but only if Salesforce would place the software inside their data center rather than on “the cloud”.? Of course, Salesforce stood its ground as a cloud-first software organization, and today I can’t think of a single company that is demanding that Salesforce migrate this application inside its data center.?

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The true power of causal AI is to determine approaches that can change outcomes.? No one has an immediate answer to solve problems.? Often when managers don’t understand how to handle a problem, they resort to blaming each other.? A better approach is to apply a causal AI approach to analyze potential interventions.? For example, did the marketing campaign fail because the market itself has changed?? Would a price reduction change the outcome?? Did the crop yield worse because of a change in the chemical composition of the fertilizer or a lack of rainfall?? What would happen if the company changed the fertilizer?? What if the company planted a different variety that was drought resistant?? However, it is too easy to look at relationships between variables and make assumptions based on correlations that are not based on reality.? There may be a correlation between crop failure and the amount of sunlight.? However, this relationship has no impact on crop failure.? The power of Causal AI is that it enables the management team to test potential interventions before taking action.

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Understanding the cause and effect of business problems.

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What are the cause and effect of events?? Most organizations are desperate to determine how to move their businesses forward by understanding what went wrong.? Business executives ask questions like: Why did a marketing campaign fail?? Why are crop yields worse this year than last year?? Traditional AI approaches may give you a warning that a failure will happen, but they can never tell you “why.”

Stu Frost Samantha Lakin Sam Greenblatt Scott Hebner David Kenny David Vellante Ibrahim Gokcen Nelson Hsu Paul Hünermund Sandy Carter Vicki Reyzelman Janice L. Brown Bill Schmarzo Buell Duncan Sandy Carter Cynthia Cohen Scott Hebner Scott Cunningham Kenneth Woanyah Fern Halper, Ph.D. Daniel Kirsch Steven Eyre Wiley