IFS launches AI‍-‍powered logistics platform

IFS has announced the launch of IFS.ai Logistics, an AI-powered logistics intelligence platform purpose-built for enterprises operating complex, multi-carrier, multi-region transport networks. The company says the solution extends industrial AI into the physical movement of materials and goods — adding a logistics intelligence layer that connects operational decisions to financial outcomes across the full supply chain.

Building on 7bridges technology, which was acquired in 2025, IFS.ai Logistics is said to provide a single closed operational loop spanning transport planning, automated execution, freight audit, cost governance and continuous network optimisation. It operates within IFS Cloud, alongside Enterprise Asset Management, Field Service Management, Enterprise Resource Planning and Supply Chain Management, and is composable with third-party platforms, reducing adoption friction for enterprises managing complex multi-system environments.

Companies today spend 5–10% of revenue on transportation, yet logistics remains one of the hardest costs to govern. Data is fragmented across carriers, regions, legacy systems and spreadsheets. The result is often that logistics teams are in reactive mode, unable to act on data they cannot see, trust, or compare. For large manufacturers and logistics providers, a 1% inefficiency in freight spend can represent tens or hundreds of millions of dollars in avoidable annual cost.

IFS said that IFS.ai Logistics addresses this directly across four capability areas. AI-driven transport planning and carrier selection replace manual decision-making with intelligence-led optimisation across modes, legs and trade lanes, while zero-touch automated execution eliminates booking errors and operational overhead with real-time shipment visibility and intelligent exception handling. A finance-grade freight audit engine validates every invoice at line-item level, applying automated GL coding, surfacing billing discrepancies and managing dispute workflows to recover leakage, while a network intelligence and simulation layer enables continuous what-if scenario modelling, from carrier strategy and cost forecasting to emissions planning and procurement consolidation.

Underpinning all four capabilities is a logistics-native data model that standardises and harmonises fragmented transport data into a single trusted intelligence layer with one source of truth for reporting, forecasting and continuous network improvement.

“Logistics is one of the largest, most frequently disrupted and least-governed cost categories in global industry, and the consequences show up directly in EBITDA,” said Philip Ashton, President, IFS.ai Logistics. “Over the last five years we have seen that when AI is applied at scale, directly inside specific industry applications, like enterprise logistics operations, customers can capture value within weeks — they begin to protect margin, improve service reliability and increase operational agility.”

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