AVEVA, a global leader in industrial software, and IFS, a global leader in AI-powered enterprise software for asset-intensive industries, announced a technology partnership to enable complex industrial organizations to connect operational intelligence, enterprise execution and strategic capital planning. CEOs Caspar Herzberg and Mark Moffat shared the first wave of the collaboration at AVEVA World in Milan: Continuous Asset Decision Intelligence. This new solution is designed to turn real-time operational and asset data into smarter maintenance, investment and execution decisions across the integrated asset lifecycle. The benefit for customers is simple: less guesswork and timelier, evidence-based decisions.

Caspar Herzberg, CEO of AVEVA, commented: "Industrial intelligence only becomes real when you have the complete picture. Our partnership with IFS connects data and insights in powerful new ways, from sensor to boardroom. The architecture is right, the customer need is urgent, and the AI opportunity is now practical. This is what radical collaboration looks like in reality."

Mark Moffat, CEO of IFS, commented: "IFS helps customers turn asset insight into action across maintenance, service, workforce and capital planning. Together with AVEVA, we can give customers the operational context and enterprise AI they need to decide what work to do, when to do it, and whether to repair, defer or replace — with evidence from signal to outcome."

Insight is still too far from action

One of the biggest challenges reported by industry leaders is that live operational data often sits with operations teams, while maintenance history, outage plans, spares, crew capacity and investment priorities are elsewhere. That data separation makes it hard to gain a holistic understanding of a complex asset or portfolio, slowing the time it takes to move from insight to action.

A reliability engineer, for example, sees an anomaly, however it falls to the maintenance planner who only has partial information to determine: Is there a fix already in the work plan? Has the asset failed in this same way before, or is this a one-off event? Should we expect similar failures at our other sites? Finally, should we repair, defer or replace? The AVEVA-IFS partnership is designed to answer those questions in one connected decision flow where every participant in the value chain has the information and AI-enriched insight that they need to act with speed and confidence.

Jeffrey Hojlo, Research Vice President, Future of Industry Ecosystems, Innovation Strategies, & Energy Insights of IDC, commented: "AVEVA and IFS are addressing one of industrial AI's biggest gaps: the distance between insight and action. By unifying real-time operational intelligence with enterprise execution and capital planning, their partnership promises to deliver Continuous Asset Decision Intelligence across the asset lifecycle. The closed loop enterprise-to-production-to-edge digital thread that this partnership enables also provides a foundation upon which generative, agentic, and predictive AI can advance data analysis and federation, enhance knowledge sharing, and improve both planning and risk management."

Craig Resnick, Vice President of ARC Advisory Group, commented on: "What makes this AVEVA–IFS partnership compelling is that it closes the distance between insight and action. By connecting real-time operational intelligence with enterprise execution and strategic capital planning, 'Continuous Asset Decision Intelligence' turns often thousands of data points into a single, evidence-based decision flow—so teams can decide what work to do, when to do it, and whether to repair, defer, or replace with greater speed and confidence. Just as importantly, it creates an auditable chain from asset condition to decision to outcome, which is increasingly critical for boards, investors, and regulators."

What this looks like in practice

The joint solution uniquely connects three layers in a single architecture: operational and engineering intelligence with strategic capital planning. For a utility operating hundreds of substations, an emerging transformer issue at one substation becomes a portfolio decision rather than a local firefight. For example, rising temperature alarms and abnormal dissolved gas readings can be detected, actioned and remediated through decision workflows that bring together the maintenance history, criticality, spares, crew availability, outage plan and capital programme context. This enables stakeholders to prioritise the right work, compare repair-defer-replace options against fleet-wide precedent, schedule the right personnel and parts, and retain an evidence trail from inception of the issue to remediation.