For all of AI’s promises, we still need people to do a lot of work behind the scenes to make it all possible. People collect, enrich, clean, and prepare data for AI systems to operate accurately and optimally. In fact, data scientists spend countless hours cleaning and combining datasets, a process commonly referred to as “data wrangling.”
![People in the AI Tech Stack [Infographic]](https://blog.cloudfactory.com/hs-fs/hubfs/02-Contents/5-Infographics/people-in-ai-tech-stack-infographic.jpg?width=1200&name=people-in-ai-tech-stack-infographic.jpg)
Our latest infographic takes a closer look at the critical role people play in preparing data for some of the most innovative tech in development today. Learn about three uses of machine learning that involve the expertise of people to gather, enrich, and moderate data for AI-powered systems. And, get tips for your workforce options when you need people in your AI tech stack.
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Outsourcing Infographics Workforce Strategy AI & Machine Learning
