The Industry 5.0 lesson from logistics: resilience before spectacle

Industrial innovation is often associated with visible technologies: artificial intelligence, robotics and new digital platforms. Logistics provides a useful counterpoint. In a network where one faulty handover can disrupt downstream activity, resilience depends first on dependable processes and connected information.

Modern logistics already relies on extensive digital infrastructure. Warehouse management, transport planning, enterprise systems and customer applications all contribute to the movement of goods. Yet these platforms are frequently acquired at different times, especially after business growth or acquisitions. Their interfaces can become the weakest part of the operation.

Digitalisation should remove friction

Research among 150 senior logistics and supply chain technology decision-makers, included in NashTech’s report Differentiating with Custom Software in Supply Chain and Logistics, found that 43% regarded improved integration with existing systems as a primary reason for developing custom software. Only 33% identified innovation or differentiation as the main driver.

This is a significant Industry 5.0 message. Technology does not create resilience simply by being advanced. It must support workers, preserve operational continuity and improve the quality of decisions. A focused integration layer can be more valuable than replacing every platform. Better data consistency, fewer manual exceptions and smoother operational handovers can reduce waste and prevent avoidable disruption. NashTech presents custom software in this practical role.

AI adoption must follow the constraint

Artificial intelligence brings considerable potential but also exposes the cost of weak foundations. Seventy-one per cent of surveyed leaders expect growing AI adoption to have a major impact on custom software development. However, 46% have struggled to integrate advanced AI with legacy systems, while 44% lack relevant internal expertise.

For industrial companies, the implication is clear: begin with the recurring operational constraint. It may be a warehouse handover, delivery exception or repeated reconciliation across systems. Once the problem is understood, AI can be assessed alongside integration, automation or a simpler redesign.

That approach supports resilience and responsible digitalisation. The most sustainable technology investment is not necessarily the most sophisticated one, but the one that improves performance without adding unnecessary complexity.