**Hannover Messe 2025**: Helena Jochberger of CGI outlines how generative AI will drive manufacturing transformation by enhancing data integration, accelerating R&D, boosting supply chain resilience, and fostering sensing factories, while stressing responsible AI and robust data strategies as essential for Industry 5.0 success.
At Hannover Messe 2025, a leading global event for industrial technology, Helena Jochberger, Vice President and Global Industry Lead of Manufacturing at CGI, shared insights on the evolving role of artificial intelligence (AI) in the manufacturing sector. Speaking to IIoT World—the first publication globally dedicated solely to Industrial Internet of Things (IIoT) topics—Jochberger outlined a pragmatic strategic pathway for how generative AI can transform manufacturing from ambitions grounded in data to fully realised, sensing factories.
Manufacturing has been engaging with AI technologies for several decades, initially through approaches like robotic process automation (RPA) and decision automations tied to frameworks such as ISA-95 introduced in the mid-1990s. However, Jochberger emphasised that a new era is dawning, characterised by a shift from task-based, rule-driven automation to goal-oriented intelligence. Generative AI enables manufacturing systems not only to execute predefined tasks but to adapt dynamically to complex operational goals. This development promises heightened autonomy, accelerated processes, and improved precision within industrial production environments.
Despite enthusiasm surrounding AI applications, a key impediment continuing to challenge manufacturers is insufficient data readiness. Jochberger described data as the “little brother of AI,” highlighting that without mature data governance frameworks, AI efforts frequently underperform. She advises companies to create digital continuity that links enterprise resource planning (ERP), manufacturing execution systems (MES), and aftersales services; to dismantle data silos limiting organisational insight; and to customise data models tailored for use cases spanning research and development (R&D), supply chains, and production. According to Jochberger, a clear and scalable data integration strategy is now indispensable—it forms the backbone of successful AI adoption in what is sometimes termed Industry 5.0.
An illustrative example provided during the discussion involved accelerating product development cycles for complex systems such as aircraft and ships. By integrating large language models (LLMs) with internal knowledge databases, manufacturers can automate and streamline ticketing and communication between design and production teams. This integration leads to faster iteration cycles, reduces bottlenecks, and shortens time-to-market, demonstrating one of the earliest and most promising use cases for generative AI in industrial R&D settings.
Another focal point of CGI’s work, as highlighted by Jochberger, is enhancing supply chain resilience through AI-powered solutions that rely on real-time data exchange between original equipment manufacturers (OEMs) and suppliers. Achieving this requires widespread adoption of shared data standards and adherence to principles of data sovereignty, where organisations maintain control over the conditions under which their data is shared. Such transparency supports dynamic, demand-driven supply chain adjustments, allowing manufacturers to respond swiftly to disruptions or fluctuating customer demand.
Looking to the future, Jochberger envisions the emergence of “sensing factories” — manufacturing environments where interconnected AI, Internet of Things (IoT) devices, and data systems interact continuously to learn, adapt, and optimise operations autonomously in real time. Realising this vision depends on current efforts to integrate diverse systems, standardise data protocols, and prepare high-quality data to feed advanced AI models, creating a responsive industrial ecosystem that minimises human intervention in feedback loops.
Jochberger also stressed the importance of embedding responsibility and human-centric values into AI deployment across the manufacturing sector. She advocated for comprehensive risk assessment frameworks and transparent, explainable AI models, supported by ongoing human oversight and collaboration. Reinforcing that AI is a tool rather than an end in itself, she underscored that as Industry 5.0 technologies advance, their innovation must be anchored in supporting and enhancing human expertise rather than replacing it.
Summarising key guidance for industrial leaders, Jochberger outlined the following takeaways:
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Prioritise robust data strategies, focusing on quality, integration, and governance, as fundamental to AI success.
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Recognise generative AI’s capacity to deliver measurable value, notably in reducing cycle times in R&D and supply chain management.
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Prepare for the evolution toward sensing factories by investing in connectivity infrastructure and real-time intelligence today.
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Approach responsible AI not simply as a compliance necessity but as an essential component of long-term trust, usability, and business value.
This comprehensive overview delivered at Hannover Messe 2025 reflects current industry thinking on how manufacturers can transition from data-driven ambitions to truly intelligent and adaptive production systems using generative AI. The path laid out by Helena Jochberger and CGI offers a roadmap for integrating advanced AI within manufacturing processes while maintaining a balanced focus on data maturity, operational goals, and ethical considerations.
Source: Noah Wire Services
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