Exploit the Economics of Artificial Intelligence with Design Thinking and Data Science

In my most recent blog "Design Thinking Humanizes Data Science", I discussed how Design Thinking and Data Science complement each other. They are not just two sides of the same coin, but the same side of the same coin in their objectives to "diverge before converging" in driving business stakeholder collaboration with respect to identifying, brainstorming and envisioning the variables and metrics that might be better predictors of performance (see Figure 1). Maybe the most important cultural similarity between Data Science and Design Thinking is the mentality that if you don't have enough "might" ideas, you'll never have any "breakthrough" ideas. In this blog, I want to combine the value creation focus of Economics with Data Science and Design Thinking. I want to use Economics as the Digital Business Model Transformation guide in leveraging Data Science and Design Thinking to drive cultural change and business model disruption. A recent article from the University of Chicago Booth School of Business titled "Why Artificial Intelligence Isn't Boosting the Economy--Yet" highlights a common problem with new disruptive technologies – there are substantial upfront investments in these disruptive technologies, resulting in a negative short-term Return on Investment (ROI).