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AVEVA is positioning CONNECT as a broader industrial intelligence platform for resilience, AI-enabled decision-making, multi-cloud flexibility, and lifecycle integration
At AVEVA World 2026 in Milan, AVEVA used its CEO keynote to frame the next phase of industrial software around resilience, AI-enabled decision-making, and connected asset lifecycle intelligence. CEO Caspar Herzberg described the current industrial environment as a “new operating reality,” shaped by geopolitical instability, supply chain disruption, energy transition, electrification, data sovereignty, and the rapid rise of generative, agentic, and physical AI.
Caspar Herzberg, CEO of AVEVA, outlined the company’s industrial intelligence strategy at AVEVA World 2026 in Milan
The broader message was that industrial organizations can no longer optimize primarily for efficiency. They must now balance efficiency with resilience, sustainability, operational continuity, and human-centered decision-making. This framing reflects a broader shift in industrial software strategy, where suppliers are increasingly positioning their platforms around adaptability, optionality, and faster, better-informed decisions across complex operating environments.
CONNECT Remains Central to AVEVA’s Platform Strategy
AVEVA highlighted its multi-year platform strategy, moving from the 2024 foundation phase to expanded digital twin, AI, and ecosystem capabilities in 2025
AVEVA positions CONNECT as the foundation of its industrial intelligence strategy. The company described the platform as a way to bring together engineering, operational, time-series, event, and contextual data into a more unified environment for industrial decision support.
Herzberg also emphasized that AVEVA’s software strategy is focused on three core attributes: integrated, intelligent, and intuitive. This aligns with the company’s ongoing effort to connect design, build, operate, and optimize workflows while improving the usability and scalability of its software portfolio.
The company highlighted progress made over the past several years, including the expansion of CONNECT as an industrial intelligence platform, stronger cloud and hybrid-cloud capabilities, digital twin developments, edge AI capabilities, and broader partner ecosystem growth.
Key Announcements Focus on AI, Data Access, and Multi-Cloud Choice
AVEVA announced several strategic moves intended to strengthen its industrial AI and data platform position.
These include:
Agreement to Acquire TwinThread, subject to regulatory approval, adding predictive analytics, digital twins, and AI capabilities for industrial markets.
Strategic Collaboration with Snowflake to support more secure access to operational, engineering, and enterprise data without unnecessary duplication.
Expansion of CONNECT to AWS, reinforcing AVEVA’s move toward a multi-cloud strategy and giving customers more deployment choice.
Partnership with IFS to support Continuous Asset Decision Intelligence by connecting operational insight with enterprise execution, maintenance, service, and capital planning.
AVEVA announced an agreement to acquire TwinThread, subject to regulatory approval, to add AI, predictive analytics, and digital twin capabilities to its industrial software portfolio
AVEVA’s planned expansion of CONNECT to AWS supports its broader move toward multi-cloud deployment and customer choice
Together, these announcements indicate that AVEVA is moving beyond individual product integration toward a more open, partner-integrated industrial software architecture. The emphasis is on enabling governed data sharing, cloud flexibility, digital twin development, and AI-supported decision-making across operations and enterprise functions.
AVEVA and IFS Target Closed-Loop Asset Lifecycle Intelligence
A major theme of the keynote was the partnership between AVEVA and IFS. The two companies positioned the collaboration as a way to connect engineering, operations, maintenance, field service, and capital planning into a continuous intelligence loop.
IFS CEO Mark Moffat described the goal as closing the gap between operational insight and capital investment decisions, especially in asset-intensive industries where equipment performance, maintenance needs, safety, and resilience have direct financial and operational consequences.
Herzberg described the combined approach as “a closed loop from sensor to the boardroom,” linking real-time operational data with maintenance, service, and investment decisions.
This is strategically important because many industrial organizations still struggle to move insights from operations into enterprise-level decision-making. Predictive analytics may identify asset risk, but those insights often remain disconnected from maintenance execution, spare parts decisions, field service planning, or capital allocation. The AVEVA-IFS partnership is intended to address that gap.
Industrial AI Requires Context and Human Judgment
AVEVA’s keynote also reinforced the importance of keeping people at the center of industrial AI adoption. Herzberg argued that while AI will be transformative, human judgment remains critical in industrial environments where decisions affect safety, reliability, uptime, and operational risk.
This is a relevant distinction for industrial companies. Unlike many consumer or office productivity AI use cases, industrial AI must operate within environments that involve physical assets, regulatory requirements, process safety, engineering constraints, and mission-critical infrastructure. AVEVA’s positioning suggests that AI value will depend not only on model capability, but also on contextualized data, trusted workflows, and clear links between insight and action.
Roadmap Points to AI, Digital Twins, and Improved User Experience
AVEVA also highlighted several roadmap priorities for 2026. These include continued investment in industrial AI, cloud-native analytics, digital twins, AI-enabled workflow support, and improved user experience.
Planned and highlighted capabilities include:
Industrial AI capabilities built around CONNECT.
Cloud-native analytics and AI applications.
Digital twin builder capabilities.
Industrial knowledge graph development.
Enhanced PI-related capabilities.
AI support for PI and PI Vision.
Improved CONNECT user experience.
Unified engineering and visualization capabilities.
These roadmap priorities show AVEVA’s intent to make CONNECT a contextual layer for industrial intelligence, in addition to a cloud destination for operational data. The company is also signaling that the next phase of competition in industrial software will be shaped by how effectively suppliers can connect data models, engineering context, operational systems, and enterprise workflows.
ARC View
ARC views AVEVA’s announcements in Milan as strategically significant because they address several persistent barriers to scaled industrial AI adoption: fragmented IT/OT data, limited operational context, disconnected enterprise workflows, and constrained deployment flexibility.
AVEVA is making a shift from being primarily a provider of a broad collection of industrial software products toward becoming a platform orchestrator for industrial intelligence. The strategy is credible, particularly given the company’s large installed base, CONNECT platform investments, PI System heritage, and expanding partner ecosystem. Execution will be critical.
AVEVA is emphasizing that its ecosystem-led approach can deliver additional repeatable customer value across heterogeneous installed bases, diverse cloud preferences, and regulated operating environments. The partnerships with Snowflake, AWS, and IFS, along with the planned acquisition of TwinThread, will strengthen the company’s strategic direction. Customers will measure success through faster deployment, better data contextualization, improved asset performance, and clearer links between operational insight and business outcomes.
As AVEVA translates these platform investments, ecosystem partnerships, and the planned TwinThread acquisition into measurable customer results, it will further strengthen its position in industrial software and in the broader market for AI-enabled operational and asset lifecycle decision support.