Market Insight: From Fragmented Systems To Industrial Agility – The Rise Of Industrial AI Analytics
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Executive Summary
Industrial firms depend on the ability to see what is happening across operations – and to act quickly. Data fragmentation across industrial systems and difficulty in mastering specialist analytical tools undermine this capability. Current workarounds compound the challenge. Between 35% and 55% of critical technical activities rely on proprietary software, creating ongoing maintenance challenges and limiting knowledge transfer. Industrial AI analytics creates a connected decision layer spanning operational technology (OT) and IT systems, enabling engineers to convert data into actionable insight at scale. When embedded within engineering workflows, AI accelerates investigation while preserving human judgement. Decision-makers should prioritize a connected analytics decision layer that scales engineering expertise, operationalizes proprietary knowledge and enables faster, more collaborative decision-making across the enterprise.About the Authors
Robin Sureda-Tasis
Analyst
Robin is an Analyst at Verdantix with a focus on frontier technologies, such as AI analytics, extended reality and industrial data management. He delivers actionable insi...
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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
Research Director
Malavika is a Research Director at Verdantix, guiding research that explores how digital technologies and services are reshaping industrial operations to become safer, more ef...
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