Kongsberg’s thought leadership session reflected a clear shift in the industry from experimental AI initiatives to industrial scale deployment driven by necessity rather than curiosity. The presentation traced how heavy asset industries have moved beyond isolated pilots towards solutions that now influence day to day operations for tens of thousands of users, with value creation increasingly embedded in normal ways of working.
The session positioned AI, simulation, and digital twins as a combined response to mounting structural pressures facing energy and manufacturing organisations. Labour shortages, supply chain volatility, rising input costs, and increasing system complexity were presented not as future risks but as current realities that demand faster, more informed decision making. Against this backdrop, AI adoption was framed as essential to sustaining performance and resilience, rather than a discretionary technology investment.
Kongsberg highlighted the importance of grounding AI in first principles through physics based simulation, using high fidelity models to train faster, explainable AI systems that can operate at scale. By combining simulation, machine learning, and agent based architectures, the approach enables users to access advanced analysis through intuitive, conversational workflows while maintaining trust and transparency in the outputs.
A strong emphasis was placed on human feedback loops and domain centric design. Rather than centralised experimentation, successful AI initiatives were shown to originate from real operational workflows, with frontline users actively validating outcomes and shaping model behaviour. The session concluded with a call for industry leaders to view AI as a trusted partner that amplifies human intent, accelerates learning, and supports continuous improvement across increasingly complex industrial systems.
Speakers
