Here are two broad ways to allow non-IT/engineering employees to gain relevant AI literacy in order to close an unneeded gap…

The precise steps to do this remain a work in progress for most firms, but here is how we did it at Gogolook:

  • We embarked on a company-wide deep learning training program to equip our workforce — engineers and non-engineers alike, from business development, design, marketing, and administration teams — to equip them with the foundational knowledge and skills behind deep learning algorithms and useful automation tools.
  • The coursework was customized for engineers and for non-engineers: one was based on understanding and using programming tools; the other was based on using platforms that support automation and prompt control of LLMs. Both teams were then invited to collaborate to build fully functional prototypes during an internal company-wide technology event.
  • The idea was that the non-engineers would prove usability while the engineers would prove efficiency and scalability.
  • For the technical content, we covered the essential math, and topics from simple to multi-layer neural networks, training strategies, to various advanced architectures such as transformers and object detection. Trainees were required to submit two assignments, one with Kaggle and another at the company wide tech event. The whole duration was 12 weeks, 2 hours per session. The most satisfying feedback was that the engineers felt confident they could apply what was learned in their individual product teams and will continue the learning journey.
  • For the non-engineers, staff such as UI/UX designers and marketing specialists learned AI-powered semantic analysis and used their new skills to save valuable time and resources, and improve content creation efficiency and quality.
  • Overall, the approach fostered departmental ownership of AI. Employees of diverse functions can now explore new possibilities with AI, leading to a more tangible and rapid enhancement of businesses’ overall AI capabilities.

Democratizing AI in the office