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PRO.FILE logo featuring a large P inside a circle, with the words PRO.FILE and from revalize next to it, including the Revalize logo.

AI-Enabled PLM Fails on Data, Not the Model

A person types on a laptop with holographic icons and the text PLM displayed, representing advanced product lifecycle management technology focused on improving data quality in PLM.
60% of AI projects are abandoned for lack of AI-ready data. This whitepaper shows why data quality, not the model, is the real bottleneck in PLM, and how to make your product data ready for AI, step by step.

What you will learn

  • Why AI amplifies what is already in your data, the good and the bad
  • The three dimensions of data quality and a five-level maturity model
  • What poor data quality really costs in engineering
  • Why AI agents and the Model Context Protocol (MCP) raise the stakes
  • A self-assessment and a pragmatic 90-day roadmap
AI runs on clean data. PRO.FILE makes yours ready.

Three independent studies, one finding

60%

of AI projects will be abandoned by 2026 for lack of AI-ready data
Gartner, February 2025 (248 respondents)

60%

of industrial companies cite data quality as their #1 AI barrier
CIMdata, AI in Industry (PLM Forum, 7 April 2026)

56%

of industrial companies use AI only in selected areas, not yet at scale
PRO.FILE Smart Manufacturing Report 2026