How Will the “Budding Effect” of AI Influence Your Career?

When Edwin Budding patented his idea for the lawnmower in 1830, he never imagined his invention would serve as a defining moment for the sports industry. The authors of What To Do When Machines Do Everything: How to Get Ahead in a World of AI, Algorithms, Bots, and Big Data have coined the term “budding effect” to describe what happens when one invention gives rise to unforeseen innovation.

The authors, three employees at Cognizant’s Center for the Future of Work, take aim at widely cited research by Oxford University that predicts that as many as 47% of U.S. jobs could be automated away by 2025. While some jobs will be lost to automation, the consultants at Cognizant predict the number is closer to 12%. Their more optimistic analysis suggests most jobs will be enhanced (75%) and many jobs will be created (13%).

But not everyone is so optimistic. Lopez de Prado, the former head of machine learning at AQR Capital Management and now a professor at Cornell University, told the U.S. House Committee on Financial Services this month that recent advances in pattern recognition, big data, supercomputing, and machine learning could “disrupt some of the highest paying jobs in finance.”

We aren’t talking about bank tellers who perform rote tasks. Prado testified that “Financial ML [machine learning] creates a number of challenges for the 6.14 million people employed in the finance and insurance industry, many of whom will lose their jobs—not necessarily because they are replaced by machines, but because they are not trained to work alongside algorithms.”

This testimony resonated with me because of my interest in educational systems, classroom instruction, and parenting. I briefly explore my thinking from each perspective below.

Education Professional: Most universities function in academic silos and lag workforce needs, so schools with even the best finance and engineering programs probably aren’t working together to develop curriculum to prepare the next generations of college graduates to work alongside algorithms. I am less confident the American public school system is preparing our children for the Fourth Industrial Revolution.

Classroom Instructor: I continue to find creative ways to teach communication, entrepreneurship, and leadership skills. All three are social and emotional skills that, according to the McKinsey Global Institute, will only increase in importance in the next ten years. With certainty that most students I teach today will not just have multiple jobs, but multiple careers, I increasingly focus my efforts on helping my students learn how to learn. A university degree is not the end of an educational journey, but a place to lay the foundation for life-long learning.

Father: If AI experiences a “Budding Effect” then we can’t predict the skills my daughters will need when they enter the workforce. However, I can help them develop a curiosity toward learning and expose them to a diversity of ideas and people. As I think about guiding my children, I appreciate the Howard Thurman quote: “Don’t ask what the world needs. Ask what makes you come alive and do that — for what the world needs is people that are alive.” When I look into the eyes of my daughters, I am not worried about what the future will bring; I am filled with hope.

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You can’t predict the future, but you can play an active role in shaping it. For those interested in exploring these ideas further, the links to some of the documents I read in the process of writing this article are included below.

Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation?. Technological forecasting and social change, 114, 254-280. Retrieved from:

Lake, Robin (2019, March 26). Preparing Students for the Uncertain Future: Why America’s Educators Are Ready to Innovate — but Their Education Systems Are Not. Retrieved from:

McKinsey Global Institute (2018, May). Skill Shift Automation and the Future of the Workforce. Retrieved from:

Prado, Marcos (2019, December 6). Testimony before the U.S. House of Representatives Committee on Financial Services Task Force on Artificial Intelligence. Retrieved from:

The Economist Intelligence Unit (2015). Driving the skills agenda: Preparing students for the future.Retrieved from: