IFS Cloud Industrial AI: What Asset-Heavy Enterprises Should Do in 2026

Jeet Poptani, Chief Transformation Officer at AumentoAI, on where IFS's Industrial AI push is real capability — and where it's still a roadmap slide.

Most of the AI-in-ERP conversation happening in 2026 is a conversation about SAP. That's a gap, not a reflection of where the interesting work is. For manufacturing, energy, utilities, aerospace & defence, construction and field-service-heavy organisations — the "moment of service" businesses IFS has always been built for — IFS Cloud's Industrial AI push deserves the same scrutiny CIOs are giving Joule, and I don't see enough of that scrutiny happening.

Why IFS is a different conversation than SAP

IFS's heritage is asset and service management, not general ledger. Enterprise Asset Management, Field Service Management and ERP have been unified in one suite for years, which means IFS's AI investment lands on a different kind of data than SAP's: work orders, technician schedules, asset telemetry, spare-parts inventory, compliance records. That's a genuinely different AI problem than automating a financial close, and it's why I'd caution against reading IFS's Industrial AI announcements as "IFS's version of Joule." The use cases and the risk profile are not the same.

What IFS has actually shipped

IFS Loops is the platform to watch. It deploys what IFS calls "Digital Workers" — agentic AI that handles field dispatch, supplier coordination, customer order management and inventory replenishment, with a stated roadmap of 10 Digital Workers and roughly 50 agentic skills available now, expanding toward 100+ skills, and a Loops Studio release that lets customers build their own digital workers rather than waiting on IFS's roadmap.

IFS.ai Logistics extends the same agentic approach into enterprise transport management — a genuinely underserved area of most ERP AI conversations, which tend to fixate on finance and customer service.

IFS Zero targets emissions data collection specifically, with IFS citing up to a 30% reduction in the manual effort of gathering that data — a smaller claim than the agentic workflow numbers, but a more immediately verifiable one, and relevant to any enterprise now navigating CSRD or equivalent reporting obligations alongside its AI programme.

The headline number from IFS's H1 2026 reporting is that 60% of agentic transactions across the Loops platform are now fully automated end to end, alongside 25% year-on-year ARR growth and cloud revenue growth of 24%, with recurring revenue now 84% of total revenue. Customer wins named for the period include Coca-Cola, China Airlines, Miele and First Solar — a genuinely asset-heavy, service-heavy customer base, which is the right base to be winning if the Industrial AI positioning is real rather than marketing.

What I'd actually verify before believing the pitch

A 60% automation rate on agentic transactions is a meaningful number — but it's a number about the transactions IFS's customers have chosen to route through Loops, not a number about your operation. Before treating any of this as a roadmap input, I'd want three questions answered specifically for your environment, not IFS's reference customers:

• Which of your actual workflows generate the volume and consistency Loops needs to be worth deploying? Agentic automation earns its keep on high-volume, well-defined decisions — dispatch, replenishment, standard supplier coordination. A workflow that's genuinely judgment-heavy or low-volume won't show the same 60% figure, and no vendor's reference number will tell you which category your workflow falls into.

• What does your data actually look like underneath the asset and service management modules? The clean-core problem isn't SAP-specific. If your EAM and FSM data has the same decade of local workarounds an ECC estate typically carries, a Digital Worker will automate your inconsistencies faster, not fix them.

• Who signs off when a Digital Worker's decision is wrong? IFS markets "audit-ready compliance" as a Loops feature. That's a starting point, not a governance framework — the human-in-the-loop design for a field dispatch agent still needs to be yours to own, especially in regulated aerospace & defence or energy environments.

Where this fits your AI strategy, not just your ERP roadmap

The organisations getting real value from IFS's Industrial AI push are treating it the same way the disciplined SAP customers are treating Joule: as a sequencing decision, not a platform decision. Pick the two or three workflows where volume and data quality genuinely support agentic automation, instrument the pilot well enough to produce your own number instead of borrowing IFS's, and build the governance model — decision rights, escalation, audit trail — before scaling Digital Worker count rather than after.

IFS's platform bet is a real one, and for the right operational profile it's arguably a more natural fit for agentic AI than a general-purpose finance ERP is. Whether it delivers for your enterprise specifically depends on the same discipline every agentic ERP rollout depends on, regardless of vendor.

AumentoAI advises CIO and COO offices across SAP, IFS and Infor environments on where agentic AI is genuinely ready for asset-heavy and service-heavy operations, and where it still needs a pilot before a platform commitment. Book a Value Advisory Session to pressure-test your Industrial AI roadmap.