Verdantix Green Quadrant Names Leading Industrial AI Analytics Software Vendors, As AI Boosts Efficiencies And Fills Critical Skills Gaps In Response To Aging Workforces

London, UK. A new report by independent research firm Verdantix shines a spotlight on the trends that are changing the marketplace for industrial AI analytics software, revealing how mounting economic pressures, supply chain uncertainty and rising energy costs are pushing manufacturing firms to rethink operations. As experienced workers retire and critical knowledge is lost, industrial firms face widening skills gaps and a growing need to boost quality, safety and sustainability – with fewer resources. However, fragmented data architectures, scalability challenges and a shortage of AI expertise continue to slow operational workflows and performance.

Under increasing pressure, buyers are turning to AI analytics to unlock greater value from operational data. Verdantix calculates that spend on industrial AI analytics software will reach $5 billion by 2028, as software providers roll out advanced solutions that optimize production and energy usage in real time and support predictive maintenance strategies, to reduce costly downtime.

To capture a share of this growing demand, AI analytics providers are differentiating by innovating, demonstrating return on investment (ROI) and entering into strategic partnerships that enhance asset connectivity and software integrations.  Vendors are harnessing agentic automation, multimodal models, predictive machine learning (ML) and retrieval-augmented generation (RAG), to deliver significant productivity gains and operational intelligence. This highly innovative competitive environment is composed of a mix of specialist providers offering targeted solutions in niche segments, and services firms that leverage their AI-ready data, with a focus on enterprise-wide performance.

The Verdantix Green Quadrant: Industrial AI Analytics Software (2025) report provides heads of operations, maintenance, engineering and IT with essential insights to identify the best-fit AI analytics solution for their requirements. The report highlights 19 of the most prominent industrial AI analytics software solutions in the market, with nine firms – ABB, Augury, AVEVA, C3 AI, Cognite, GE Vernova, IBM, Seeq and SymphonyAI – demonstrating market-leading capabilities. Key report findings:

• Industrial firms are leveraging AI to transform siloed data into a unified actionable view of their entire enterprise. Vendors such as ABB and Seeq offer knowledge graphs, automated labelling and semantic models to deliver faster, more reliable insights.
  
• AI is cutting costly downtime by monitoring asset health, optimizing production and improving resource allocation. Vendors such as Augury can predict asset failures early by leveraging AI and ML, whilst Nanoprecise applies an energy-focused approach to flag abnormal consumption, enabling targeted interventions and minimizing downtime.
• Industrial leaders face pressure to boost quality and sustainability with fewer resources. Vendors are responding with industry-specific AI solutions. For example, TrendMiner offer production and quality management expertise for batch and continuous manufacturers.
• With experienced workers retiring, firms are facing a loss of critical knowledge, leading to skills gaps. To counter this, they are turning to AI analytics to preserve and scale expertise by embedding domain insights into algorithms, automating diagnostics and providing clear operator guidance. Firms such as Optimistik and TwinThread support this transition through intuitive interfaces, robust process optimization and predictive maintenance, guiding users seamlessly from question to outcome.
• Many industrial firms struggle to scale AI beyond pilots. Building trust requires explainable, reliable insights. Leading vendors are addressing this by combining governed ML with generative AI; witness C3 AI delivering actionable, explainable analytics that boost engineer confidence in AI-driven decisions.

“Industrial sectors are under growing pressure from retiring workforces, costly downtime and the demand to deliver higher-quality outputs at lower cost. To address these challenges, firms must move beyond pilot projects and embed predictive intelligence at scale, enabling faster decisions, higher productivity and measurable sustainability gains”, said Henry Kirkman, Industry Analyst at Verdantix. “To stay competitive, AI analytics vendors must provide trusted, explainable insights that demonstrate deep industry expertise, scalable deployment and seamless system integration, to address customer priorities and core maintenance challenges”.

To find out more, read the full report.