Where theory Meets reality

Australian water utilities manage over 139,000 km of aging mains and thousands of kilometres of process piping. Discover how AI, Monte Carlo simulation, and bow tie risk assessment are transforming pipe failure prediction and risk-based asset management for water infrastructure.

Delaying AI investment in asset management isn't free—it compounds. Learn the four hidden costs of waiting and how to prioritise where to start.

How SAS-AM helped GeelongPort transform a fragmented Maximo asset hierarchy into a consistent, scalable foundation for advanced asset management.

How SAS-AM used AI and NLP to analyse thousands of documents during a transport operator's maturity assessment, saving months of consulting time while improving insight quality.

Most organisations aren't as ready for AI as they think. Here are five honest signals that your asset management function is prepared to make AI work—and what to do if you're not there yet.

NVIDIA's CES 2026 GPU announcements aren't just for gamers. Here's what RTX 50-series and DLSS 4.5 mean for digital twins, predictive maintenance, and real-time asset analytics.

Discover why 2026 is the inflection point for AI in asset management. Learn what's driving adoption, what AI-powered maintenance actually means, and how to assess your organisation's readiness.

A practical framework for deciding where your asset intelligence should run - and why the answer is rarely straightforward.

Real-world examples of edge AI transforming maintenance decisions across healthcare, water, and transport sectors.

Why lightweight AI models running on existing PLCs and edge devices are outperforming cloud-dependent alternatives in the field.

How federated machine learning lets organisations improve AI models collaboratively without exposing sensitive operational data.

Real-time maintenance decisions for hospitals, water networks, and transport - without cloud dependency or latency risks.