Internationally recognized as the pioneer of an entire field in data literacy and one of dataIQ™’s 100 Most Influential People in Data, Jordan is the owner of Bodhi Data and currently serves as the Senior Vice President of Data and AI Transformation at AgileOne. He has also served as the Chair of the Advisory Board for The Data Literacy Project and speaks at leading companies, events and universities among which are the United Nations, Fidelity Investments, Vanguard, Nike, Big Data London, Coca-Cola, the PBS annual meeting, Bacardi, and Columbia University.

Jordan helps audiences identify important signals in their data through visualizing and storytelling, stipulating that wisdom, above strategy and goals, is required to become truly data literate. He has authored five books on data and AI, and was awarded first place in the International Book Awards in 2023. His mission is to empower individuals and organizations to be more data literate and data-driven. 

By the end of Jordan's speeches, you will feel more confident to succeed with the necessary data and AI skills.

Let's get to know Jordan a bit better with 4 burning questions. 

1. Where do you draw inspiration from as an author?

My inspiration as a writer can come from many sources. I love to write in general, like journaling. I love to study and read. I find there is goodness in helping and mentoring others. So, I can find inspiration in reading about philosophy or Taoism, from meditation and reflection, from industry trends, to mindset. There are many things that can inspire me and I hope I don't miss them. I like to journal and write things down. I hope that reflects in my mind and can come out, if needed, in my writing or speaking.

2. How big of a role did your degree in Economics and an MBA play in your success as a thought leader in data literacy? 

I think the degrees I received are indicative of my personality. First off, I am a big believer in critical thinking for ourselves. This plays a part in education, whether high school, undergrad, or graduate degrees. Learning is also a key for me, so the more I learn, the better a thought leader I can be. So, my personality is one of growth, seeing limits I can push, and learning. That applies to thought leadership. I don't want to just regurgitate ideas but have my own ideas, generate new content, and maybe I can help people think a bit more.

When it comes to studying economics, I studied in a program that allowed me to study the philosophy of economics and not just one school, like the Chicago school of economics. This ability to study economics in a manner that was theory and philosophy, the ability to see maybe problems that were present and then schools of thought that came from them, could have been what helped me with my building of data literacy. There was a thought in my mind that we blew open and drove to where I am today. By studying philosophy of business and economics, we aren't just beholden to one space or thing and told that's it. Instead, we can generate questions ourselves, philosophies ourselves, and we can think for ourselves.

3. What is a universal problem that organizations across the board face when it comes to data?

There are multiple data problems that can span across organizations and regions. One in particular is that companies are investing in data and AI but aren't finding the traction and ROI they should.  Data is powerful and when used right, augments the human and helps in decision making. A problem is when 90-99% of people aren't data professionals, they may not be as comfortable with using data for decisions as a data professional. The other side is data professionals may not know the business side of an organization as well, either.  So, it is the two sides of a coin: learning and skills gaps. Data and AI literacy, plus business literacy, plays a role here. Then, when using data for business problems, we can look to use cases and driving value vs having people not understanding what to do.

4. What do you want people to know most about data and AI in the present time?

I want people to know that they have a seat at the data and AI table. There is a lot of hype and talk about AI right now, even fear. Instead of driving fear and hype, let's empower people to determine their seat at the table and develop skills to use data and AI, not fear it.