Upskilling & Hiring for AI

Build Unicorn Teams, Not Unicorn People

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.

3D Cover Upskilling How to Win the Battle for DataAI Talent

Get the Ebook

What Do Hiring & Upskilling Have to Do With Maturing Your AI Operating Model?

More Than You Might Think

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.


Ready to Win the Battle for Data + AI Talent?

3 Initiatives to Drive Adoption + ROI While Upskilling

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.