INDUSTRY-two-stage

Leadership in frontier technologies such as Artificial Intelligence, Quantum, Photonics and Semiconductors is essential to Europe’s economic security and global competitiveness. Building on the ambition of becoming the “AI Continent” and in line with the concrete actions devised in the Apply AI Strategy^[1], the EU will consolidate its world-class research ecosystem through initiatives like the RAISE network of AI science labs, the development of safe and efficient frontier AI models, and the deployment of next-generation AI agents and robotics in strategic sectors. In parallel, a long-term quantum strategy will reinforce Europe’s excellence across quantum computing, sensing and communication, supported by new infrastructures and standardisation to secure technological sovereignty. Photonics and semiconductor technologies will remain critical enablers for the digital and green transitions, with investments in advanced integrated photonic devices and resilient semiconductor ecosystems ensuring Europe’s capacity to innovate, scale and compete globally. Foresight and support to emerging materials and technologies will further strengthen Europe’s position at the cutting edge to make sure Europe’s does not miss the emergence of new disruptive technologies, aligning with the Draghi report and the Competitiveness Compass to secure a cohesive, sovereign and future-proof European industrial base.

Legal entities established in China are not eligible to participate in both Research and Innovation Actions (RIAs) and Innovation Actions (IAs) falling under this destination. For additional information please see “Restrictions on the participation of legal entities established in China” found in General Annex B of the General Annexes.

[1] COM(2025)723 Apply AI Strategy

Expected Outcome:

• Increased competitiveness and productivity, through innovative AI-enabled advanced manufacturing processes and operations, including real-time monitoring and adaptive optimisation; and
• Reduction of emissions and alignment with Clean Industrial Deal objectives.

Scope:

AI approaches in manufacturing processes hold the potential to significantly enhance circularity, process and operational efficiency as well as sustainability of modern factories. Current state-of-the-art technologies have already paved the way for more streamlined operations, yet there remains untapped value in e.g. quality improvement, definition of optimal process operating conditions, reduction of scrap, optimization of energy usage. Real-time monitoring and adaptive optimisation using AI models can enable agile responses to production variability and support sustained, high-performance operations.

New solutions based on innovative enabling technologies such as deep learning, large language models, digital twins, synthetic data, and data-driven models allow manufacturers to improve production system efficiency, elevate product quality, and proactively address critical challenges in energy consumption and carbon footprint. This dual focus on operational excellence and sustainability ensures that factories can maintain competitive advantage while also contributing to specific environmental goals, e.g. reducing the pressure on ecosystems and natural resources. Since innovation capacity and competitiveness also requires a systemic understanding of an organization’s value creating structure, novel AI solutions should be implemented such that they can support all structures and phases of operation, in technical and non-technical terms.

Proposals should produce dedicated innovative explainable AI based solutions in advanced manufacturing for at least two of the following:

• improve processes and operational efficiency, and reduce climate and environmental impact of processes and factories through dynamic selection of optimal processes and production parameters, exploiting AI for process modelling and/or optimisation;
• avoid the production of defective parts using AI to detect process drift and anomalies and correct proactively defects in real time; and
• maximise the fraction of regenerated components or materials used in the production using AI to optimise the material flow.

Proposals should demonstrate potential for these AI tools to adapt to changing production needs and real-time data, and should describe how industrial data access, confidentiality, and secure data-sharing will be addressed.

Projects are encouraged to link with AI Factories, including the Data Labs. The results may be validated in Testing and Experiment Facilities (TEFs), and further deployed via European Digital Innovation Hubs (EDIHs). This topic is linked to the Apply AI Strategy, therefore proposals should seek collaboration with relevant initiatives.

Proposals can optionally address the conditions for implementing the novel AI solutions within an organisations structure and value creating models, thereby contributing to systemic approach of implementing a smart organisation.

This topic is linked to the Apply AI Strategy, therefore proposals should seek collaboration with relevant initiatives.

Proposals should include a business case and exploitation strategy, as outlined in the introduction to Destination ‘Leadership in materials and production for Europe’.

This topic implements the co-programmed European Partnerships Made in Europe and AI, Data and Robotics.

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