Strategic Focus: Low-Code Industrial Analytics Enabled By Generative AI
Joe Lamming
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Executive Summary
The industrial analytics landscape is evolving rapidly, especially since OpenAI and Google DeepMind popularized the concept of code-generating large language models (LLMs) in 2021 and 2022. Software vendors are beginning to integrate generative AI (GenAI) into low-code/no-code (LCNC) platforms – part of their projected market growth from $1.7 billion in 2023 to $5.0 billion by 2028. This report targets IT and operations leaders in asset-heavy industries, detailing how GenAI-enhanced LCNC solutions are already improving data discoverability and operational agility – and will continue to do so – as well as democratizing access to powerful ML (machine learning)-driven analytics. The report also explores the latest, most robust GenAI-powered techniques available to industrial analytics software vendors and indicates where buyers are most likely to see immediate value.
Demand for low-code is increasingly driven by the unavoidable complexity of high-performance industrial analytics solutions
Low-code analytics boost workforce buy-in of data-driven decision-making and inform vendor GUI strategies
GenAI represents the dawn of an exciting era in industrial automation and human-machine interfaces
GenAI translates natural, codeless language into code, converting new users into power users
Industrial LCNC software vendors should use GenAI to write code, enrich existing data and automate back-end processes
About the Authors
Joe Lamming
Senior Analyst
Joe is a Senior Analyst and Technical Lead at Verdantix, specializing in AI-first platforms and applications and data management. Combining hands-on development of software an...
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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