The author provides examples of successful AI leapfrogging, such as EvenUp, an AI-driven platform that uses medical records and legal data to speed up the process of personal injury law. The author concludes by stating that while AI leapfrogging is not easy to execute and may initially involve high customer acquisition costs, the long-term value is significant due to low churn rates and the difficulty of displacing a dominant paradigm once it is established.
Key takeaways:
- African countries were among the fastest to adopt mobile payments, leapfrogging over traditional credit card systems. This concept of leapfrogging, skipping a step in the technology transformation chain, is predicted to occur with AI in industries that are still reliant on outdated systems.
- Industries such as agriculture, hospitality, education, legal, construction, and manufacturing are primed for "AI leapfrogging". The idea is to reach new demographics of users who were bypassed by previous software revolutions.
- For a leapfrog event to occur, the value of the change must greatly outweigh the burden of the change. This can be achieved by creating huge value with a change and lightening the burden of the change itself.
- Generative AI is seen as a potential solution for industries that have been slow to adopt SaaS solutions. By generating tasks from scratch and removing tedious tasks from workflows, it can reduce the burden of a shift to digitization and enhance the value of that change.