AI in IFS Cloud

IFS Cloud applies AI inside the processes that run service, manufacturing and asset-intensive businesses. Scheduling optimization assigns and re-plans technician work against skills, parts availability, travel and SLA commitments. Forecasting helps planners anticipate demand across large item portfolios. Condition-based and predictive maintenance use asset data to raise work before failures happen. Anomaly detection highlights the transactions and patterns that need attention, and embedded assistance helps users find information and complete tasks faster. Because the AI works inside the platform, the benefit appears directly in the work people are already doing.

The strongest results come where AI improves high-frequency operational decisions. In field service, optimized scheduling increases the number of jobs completed per technician and improves first-time-fix rates by matching the right person and the right part to every job. In planning, better forecasts support healthier inventory levels and higher service levels. In asset management, predictive maintenance reduces unplanned downtime and extends asset life. Across the organization, exception-based working means people spend their time on the cases that genuinely need them. ESS can demonstrate these capabilities on scenarios drawn from your own operation.

They complement each other. IFS Cloud embeds AI within its own processes — scheduling, planning, forecasting and maintenance. ESS Fusion AI extends IFS with capability for the work that arrives from outside the ERP and the questions people want to ask of it: an AI vision agentic system reads customer orders, purchase order acknowledgements and supplier invoices in any layout, validates them against live IFS master data and creates the records directly in IFS Cloud or IFS Applications, while conversational access lets teams ask questions of live ERP data in plain language. Together they automate more of the business end to end.

Yes. AI operating on transactional data is governed through confidence scoring, thresholds that determine what proceeds automatically and what is routed for human review, validation against master data before anything posts, and a full audit trail of what was proposed, who reviewed it and what changed. On the ESS Fusion AI side, the platform is deployed in your own cloud tenant or fully air-gapped, and your data is never used to train public models — the details are covered on the security page. That combination lets organizations adopt AI confidently while keeping people in control.

Start with the use case that delivers the clearest value for your business — often technician scheduling for service organizations, forecasting for manufacturers, predictive maintenance for asset-intensive operators, or document automation for any team re-keying orders and invoices. ESS will demonstrate the capability on scenarios from your operation, help prepare the data it relies on, and implement it as part of your IFS Cloud program or as an enhancement to an existing IFS environment. Because IFS Cloud is evergreen, new AI capability continues to arrive with each release, and ESS helps you adopt it as it does.