• • • DEFENCE TECHNOLOGY • • •


The importance of trust Autonomous systems must increasingly demonstrate not only what decision was made, but why it was made and what information was available at the time. Reliable logging and traceability are becoming important engineering considerations alongside traditional performance metrics. Without traceability, engineers cannot


reconstruct why an autonomous system behaved the way it did, making validation and post-mission analysis significantly more difficult. As autonomous capabilities mature, trusted data will become as important to mission assurance as AI performance itself.


Building Physical AI


on trusted foundations Physical AI represents an enormous opportunity for defence. Autonomous systems promise greater operational flexibility and reduced risk to personnel. However, achieving those benefits requires looking beyond the AI model itself. Success will increasingly depend on


infrastructure that ensures data remains available, resilient and trustworthy throughout every stage of operation. This requires platforms that can survive power failures, support secure software evolution, maintain data integrity and withstand decades of continuous service.


Equally important is recognising that AI is not a


substitute for engineering judgement and autonomous systems should augment human decision-making rather than operate without appropriate safeguards. Ultimately, Physical AI will be judged not simply


by how intelligently autonomous systems behave, but by how predictably they perform when conditions are at their worst. Organisations that invest in trusted and deterministic data architectures today will be better placed to reduce operational risk, simplify diagnostics, minimise costly field failures and modernise platforms with confidence over decades of service.


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ELECTRICAL ENGINEERING • JULY/AUGUST 2026 33


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