Over 80% of AI projects fail and the reason isn’t the models. It’s the data.
Specifications, formulations, packaging details, supplier data, and regulatory requirements are scattered across spreadsheets, PDFs, legacy PLM systems, ERP instances, and email threads. Companies attempt to layer AI on top of this fragmentation, only to get unreliable outputs, broken trust, and stalled pilots.
In this webinar, we’ll unpack why AI initiatives collapse without a specification-first data foundation, what “AI-ready” actually means in practice, and how leading organizations are progressing from digitization to orchestrated intelligence. You’ll learn the four-layer AI progression model, what “Trusted AI” requires in regulated product environments, and next steps for delivering AI at a measurable value. What You’ll Learn:
How to identify whether your current product data can actually support AI
The hidden risks AI introduces in regulated product environments (and how to prevent them)
How leading teams embed AI directly into formulation, packaging, and supplier workflows
What measurable AI success looks like – from faster impact analysis to reduced rework and stronger compliance confidence