Accelerating Industrial AI in 2026: The Report
Industrial teams are eager to apply AI, but the survey shows readiness still lags ambition, largely because organizations lack a real-time, contextualized, governed data foundation.
What Respondents are Prioritizing for 2026
Top focus areas include agentic AI and autonomous operations (67%), edge computing and real-time data processing (63%), digital twins and simulation (51%), and data governance/contextualization tools (36%).
Adoption is Still Early-Stage
Only 7% say AI is embedded in most core processes. Many are still in pilots/POCs (36%) or research with no concrete plans (32%).
The Biggest Barrier: Data, not Models
Respondents cite data quality/availability and legacy integration + silos as key challenges. Just 34% report production systems with real-time data streaming today.
The 2026 Playbook
The report recommends: improving data quality and governance, strengthening IT/OT collaboration, expanding real-time data streaming, modernizing brittle integrations, and tracking ROI with clear KPIs to scale what works.
If you are looking to get hard data on what industrial teams are actually prioritizing for 2026, such as agentic AI, edge + real-time processing, digital twins, governance, and where adoption really stands today, download this report now!
The report also helps you avoid common “AI pilot purgatory” mistakes by pinpointing the biggest blockers (data quality/availability, legacy integration, silos, lack of real-time streaming) and outlining practical recommendations to build readiness and prove ROI. Watch our webinar, Accelerating Industrial AI in 2026, for more insights.
