Artificial Intelligence
Priya Nair
Practical AI Adoption for Mid-Market Companies
AI does not have to mean a moonshot project. Here is a grounded framework for choosing use cases that pay off within a single quarter.
6 min read
Priya helps mid-market companies move AI projects from proof-of-concept to production. She has led machine learning programs across manufacturing, retail, and financial services, and focuses on the operational side of AI: data quality, governance, and measurable ROI.
3 articles published.
AI does not have to mean a moonshot project. Here is a grounded framework for choosing use cases that pay off within a single quarter.
The technology in most transformation programs is the easy part. The hard part is changing how people work, and that is where programs succeed or fail.
You do not need a PhD to make good decisions about generative AI. You need a clear mental model of what these systems can and cannot do.