The top two blockers for scaling AI are hiring people with AI skills and identifying good business cases.
To address both issues at once, build teams made up of both data and domain experts, plus evolve the operating model for AI initiatives over time. This ebook demonstrates how to execute on this winning combination.
When an upskilling program works well, it creates a virtuous cycle where business analysts acquire AI skills and create value. This increases awareness of the value of AI and new users are identified or raise their hand to be upskilled.
Throughout this process, the organization is progressing on other topics (i.e., strategic alignment and steering, AI product development, business transformation), all of which evolve and mature their operating model to generate more AI/ML talent and ROI.
1. Teams need a common AI/ML platform that ensures workers of all skill levels — from business analysts to graduate-level data scientists — want to use it.
2. No AI value will be generated without an adoption program that encourages use across data workers and the business.
3. Finally (and most importantly), an upskilling program is critical to get 10 to 100 times more people involved with AI development.