Strategic Focus: Five Barriers To Industrial AI Analytics Adoption – And How To Overcome Them
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Executive Summary
This report is written for technology buyers evaluating industrial AI analytics software. It examines five common barriers to adoption: poor and fragmented data; difficulty demonstrating return on investment (ROI); skills and capability gaps; governance and trust concerns; and the challenge of scaling beyond proof-of-concept in complex legacy environments. The report sets out practical steps to address these barriers, emphasizing the importance of strengthening data foundations, establishing governance and security-by-design, linking AI outputs to measurable operational outcomes, building workforce capability, and designing for production deployment and multi-site scale.About the Authors
Jatinder Devgun
Senior Analyst
Jatinder is a Senior Analyst at Verdantix, providing insights on emerging technologies and market dynamics for technology buyers and software vendors. His expertise lies in as...
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Malavika Tohani
VP Research
Malavika is a VP Research at Verdantix, guiding research that explores how digital technologies and services are reshaping industrial operations to become safer, more efficien...
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