Verdantix Industrial AI Green Quadrant: Vendors Seize The Industrial AI Opportunity

The recently published Verdantix Green Quadrant: Industrial AI Analytics Software report evaluates the technical capabilities and market momentum of 19 prominent vendors of industrial-focused AI analytics software. The report includes data from Verdantix operational excellence and industrial transformation global corporate surveys of hundreds of practitioners, most notably, the 2025 industrial transformation budgets, priorities and tech preferences survey of 304 industrial executives. In addition to prior research, this first industrial AI Green Quadrant is based on two-hour product demonstrations, a 105-point questionnaire, and 11 buyer interviews. Key findings show that:

• Nine vendors place in the Leaders’ Quadrant.

  In a highly competitive and saturated market for industrial AI solutions, the Verdantix Green Quadrant limited inclusion to vendors with functionality across all three core industrial AI analytics capabilities: user-configurable acquisition of industrial data; transformation and contextualization for preparing data for analytics; and generation of insights through AI-based methods. Vendors were also required to have a minimum of 10 named asset-heavy customers and at least $5 million in revenues from industrial AI analytics solutions. Of the 19 solution providers assessed, nine placed in the Leaders’ Quadrant – ABB, Augury, AVEVA, C3 AI, Cognite, GE Vernova, IBM, Seeq and SymphonyAI.

• GenAI copilots are here, but end-to-end agentic automation is roadmap.

  The market is innovating rapidly: GenAI is the front door, with agentic automation following. Most industrial AI platforms have shipped or are piloting copilots that speed diagnosis, guidance and reporting, and many have agents for multi-step workflow orchestration on their roadmaps. Vendors such as ABB, C3 AI and SymphonyAI showcase agents alongside copilots for analysis and prescriptive recommendations. Cognite’s Atlas adds an AI agent library, plus a workbench for custom agents, while Nanoprecise’s ReKurv.ai provides conversational insights into equipment behaviour. That said, end-to-end agentic autonomy is not yet proven at market scale – near-term value is concentrated in assistive GenAI with clear guardrails.

• Leaders win on quality data and contextualization.
  Leaders out-execute by turning messy OT/IT/engineering signals into a single, navigable asset model at ingestion. Without a shared, context-rich model, copilots hallucinate, analytics chase the wrong tags, and teams burn cycles on pre-model data wrangling – stalling value. The fix is an industrial knowledge graph that fuses tags, time-series, P&IDs, documents and work orders, so that AI can move seamlessly from a sensor to its drawing, live trend and maintenance context. Cognite and Seeq exemplify this graph-led approach through strong contextualization and high-throughput indirect access (including asset-tree normalization). In parallel, C3 AI strengthens data quality with near-real-time validation and cleansing, to enforce customer standards – complementary to the knowledge-graph layer.

To learn more about the 19 most prominent industrial AI software vendors in the market, read the full report here.