The article also emphasizes the importance of creating a training program that is succinct, universal, and prepared. It should cover a wide variety of subjects in a condensed timeline to allow organizations to swiftly adopt AI. The training should also cater to the diverse expertise of trainees from different departments and disciplines. The author concludes by stating that as AI becomes more pervasive, it will create new roles and jobs, particularly for trainers to help assimilate AI into companies.
Key takeaways:
- For AI to be fully actualized, it should be tightly integrated into in-house operations. This can be achieved by forming interdisciplinary teams that include both data scientists and domain experts, and training domain experts in the fundamentals of AI and machine learning.
- Outsourcing AI in energy companies is not always ideal due to the specific needs of these companies, especially large national oil companies (NOCs). These organizations often deal with confidential information and safety-related issues, requiring specialized training.
- A comprehensive AI training program can provide a balance between theoretical knowledge and hands-on experience. This can be achieved by partnering with a university and a tech provider to create an exhaustive training curriculum.
- Despite debates about AI replacing humans, hybrid AI will always require human involvement, necessitating AI training. As AI becomes more pervasive, it will create new roles and jobs, particularly for trainers to conduct knowledge transfer and help assimilate AI into companies.