AVEVA, in collaboration with IMD Business School, has released its inaugural Industrial Intelligence Report, examining how enterprises are building AI-driven digital ecosystems to transform industrial operations, supply chains, and infrastructure management.
The report, based on insights from more than 275 senior leaders across 12 industries, highlights a growing shift towards what AVEVA defines as industrial intelligence—the integration of operational technology (OT), information technology (IT), and AI to create connected, data-driven industrial ecosystems.
A key finding is the widening gap between strategic intent and execution. While 74% of leaders consider digital ecosystems a top strategic priority, only 27% report substantial data sharing with ecosystem partners, underscoring persistent barriers around governance, interoperability, legacy infrastructure, and trust.
The report suggests that enterprises are increasingly moving beyond isolated digital transformation initiatives towards ecosystem-scale operational models, where data, AI, and connected platforms coordinate activities across suppliers, operators, infrastructure systems, and industrial partners in real time.
From a technology perspective, industrial intelligence represents the convergence of AI, industrial IoT, cloud platforms, operational analytics, and connected digital twins into a unified decision-making layer. This enables organisations to improve operational visibility, strengthen resilience, optimise resource usage, and respond faster to disruptions across global operations.
The study also highlights how sectors such as logistics, energy, manufacturing, ports, and infrastructure are leveraging connected ecosystems to address complex challenges, including supply chain volatility, decarbonisation, operational efficiency, and large-scale industrial coordination.
Several case studies in the report demonstrate how industrial ecosystems are evolving into real-time intelligence networks, where organisations share operational data, coordinate decisions collaboratively, and use AI-powered analytics to improve planning and execution across distributed environments.
However, the research notes that technological capability alone is insufficient. The biggest barriers to ecosystem maturity remain integration complexity, fragmented governance structures, and siloed organisational models, which often prevent enterprises from scaling collaborative digital operations effectively.
According to Caspar Herzberg, enterprises now need frameworks and leadership models capable of enabling adaptive, ecosystem-driven operating structures that transcend traditional organisational silos.
Michael Wade highlighted that the next phase of industrial transformation will depend less on algorithms alone and more on how effectively organisations manage data sharing, ecosystem governance, collaboration models, and operational coordination.
The report ultimately points towards a broader industrial shift—from standalone digital transformation projects to interconnected, AI-enabled industrial ecosystems, where operational intelligence is continuously shared across networks to support resilient, efficient, and sustainable industrial operations at scale.