The Price Tag Reality
An energy company with 400 offshore assets and 12,000 workers now pays for 400 assets — not 12,000 user licenses. IFS just made per-user licensing obsolete for industrial operations.
On April 2, 2026, IFS announced a pricing model that fundamentally changes how enterprise AI is bought and deployed. Instead of charging per user, IFS now prices Industrial AI software based on the number of operational assets a company manages — vessels, production lines, infrastructure, equipment.
For CFOs managing AI budgets, this is the first major vendor to eliminate the per-user tax on AI adoption.
For CIOs deploying AI across operations, this removes the constraint of rationing access to control costs.
What IFS Changed
Old model: Per-user licensing
New model: Per-asset pricing
Example (energy company):
- Assets managed: 400 offshore platforms
- People + machines accessing data: 12,000
- Old pricing: 12,000 user licenses
- New pricing: 400 asset licenses
Cost reduction: ~97% fewer licenses (400 vs 12,000)
Why it matters: As AI drives automation, the number of "users" (humans + agents + machines) accessing enterprise software explodes. Per-user licensing makes AI adoption financially unsustainable. IFS pricing scales with operational reality (assets managed), not headcount or automation level.
Why This Pricing Model Exists Now
IFS's move reflects a broader shift in enterprise AI: software is no longer just enabling workers to do more — it's directly driving work and outcomes through AI agents.
When AI agents outnumber human users 10:1 (or 100:1), per-user licensing breaks. Every automated process, contractor login, and AI agent interaction triggers a license fee. The more you automate, the more you pay.
IFS CEO Mark Moffat: "Our customers should not have to choose between automating their operations and controlling their software costs. This progressive move on pricing removes that trade-off entirely. We're not pricing the workers. We're pricing the work."
The AI Adoption Paradox
Traditional per-user licensing penalizes AI automation. The more AI agents you deploy, the higher your software costs — even though automation is supposed to reduce operational expenses. IFS asset-based pricing breaks this paradox.
Who Benefits (and Who Doesn't)
✅ Asset-Heavy Industries (Winners)
Energy:
- Offshore platforms, pipelines, refineries
- High asset count, relatively low user count
- Example: 400 assets, 12,000 users → 97% cost reduction
Manufacturing:
- Production lines, machinery, equipment
- Automation-heavy environments with AI agents
- Per-user licensing penalizes automation; asset pricing rewards it
Transportation/Logistics:
- Fleets, vehicles, distribution centers
- AI-driven route optimization and predictive maintenance
- Asset pricing scales with operations, not workforce size
Utilities:
- Power plants, substations, grid infrastructure
- High asset complexity, extensive contractor access
- Asset licenses eliminate contractor seat fees
❌ User-Heavy Organizations (Losers)
Professional Services:
- Consulting firms, agencies, advisory practices
- Low asset count, high headcount
- Asset pricing doesn't apply (no meaningful operational assets)
Knowledge Work:
- Software companies, media, education
- Value creation tied to people, not physical assets
- Per-user licensing still makes sense for these industries
The CFO Decision Framework
When Asset-Based Pricing Saves Money
1. Calculate your asset-to-user ratio
- Assets managed: [number]
- Total users (humans + contractors + AI agents): [number]
- Ratio: [users ÷ assets]
If ratio > 5:1 → Asset pricing likely saves money
If ratio < 2:1 → Per-user pricing may be cheaper
2. Factor in AI agent growth
- Current AI agents accessing system: [number]
- Projected AI agents in 12 months: [number]
- Per-user licensing cost with agent growth: [calculation]
If AI agents will outnumber humans 3:1+ → Asset pricing protects against cost escalation
3. Assess contractor access
- Contractors needing system access: [number]
- Frequency: seasonal, project-based, ongoing
- Per-user cost for contractor seats: [calculation]
If contractors represent >20% of users → Asset pricing eliminates seat management overhead
Cost Predictability Analysis
Asset-based pricing advantages:
- Scales with business growth (more assets = intentional expansion)
- Immune to automation penalties (AI agents don't increase costs)
- Eliminates seat management (no tracking contractors, temps, agents)
- Transparent budgeting (asset count is measurable and auditable)
Per-user pricing risks:
- Automation tax (every AI agent = new license fee)
- Contractor overhead (seasonal workers trigger seat purchases)
- Budget unpredictability (user count fluctuates with projects)
- Rationing incentives (limiting access to control costs)
The CIO Perspective: Deployment Flexibility
IFS's pricing change removes the adoption constraint.
Under per-user licensing, CIOs must ration AI access to control costs. Deploy AI to 100 workers = 100 licenses. Deploy to 1,000 = 1,000 licenses. Deploy to 10,000 (humans + AI agents) = budget explosion.
Under asset-based pricing, deployment is unconstrained. If you manage 400 assets, you pay for 400 assets whether 100 or 10,000 users/agents access the system.
Mickey North Rizza, Group VP at IDC: "IFS moving into the next realm of pricing means buyers have flexibility in the Agentic world. IFS new pricing model helps companies operationally scale their investment to the value levers it needs to run the business."
Deployment decisions shift:
- Old question: "Can we afford to give 5,000 workers AI access?"
- New question: "Where does AI create the most value across our 400 assets?"
Competitive Pressure: Who Follows IFS?
IFS is the first major ERP/industrial software vendor to break with per-user licensing for AI. This creates competitive pressure on:
SAP: Dominant in manufacturing, still pricing per-user
Oracle: Cloud ERP leader, user-based licensing
Infor: Industrial software competitor, traditional seat model
Siemens: Industrial automation, per-user Teamcenter/Opcenter licensing
Vendor risk for customers:
- If competitors don't match asset pricing, IFS gains cost advantage
- If competitors match, per-user licensing becomes obsolete industrywide
- Either way, CFOs gain leverage in contract negotiations
Negotiation strategy for 2026:
- Asset-heavy buyers: Use IFS pricing as benchmark for SAP/Oracle renewals
- Multi-vendor environments: Pilot IFS asset model, compare TCO
- Contract renewals: Demand per-asset pricing or volume discounts matching IFS economics
Continue Reading
- AI-Powered SaaS Cost Management — How CFOs are using AI to audit enterprise software spend
- ConductorOne AI Access Management — Shadow AI creates license sprawl
- AI ROI Calculator — Model asset-based vs per-user pricing for your environment
The Broader Industry Shift
IFS's pricing change signals a fundamental rethinking of enterprise software economics in the AI era.
Traditional SaaS model (1990s-2020s):
- Per-user licensing
- Predictable costs tied to headcount
- Software augments human productivity
AI-native model (2026+):
- Per-asset or per-outcome pricing
- Costs tied to operational scale, not headcount
- Software autonomously drives work (not just enables workers)
Why the shift now:
- AI agents outnumber humans in many enterprise deployments
- Automation creates cost paradoxes under per-user models
- Agentic AI operates 24/7 without "users" in the traditional sense
Aly Pinder Jr., Research VP at IDC: "Asset-centric organizations have made the shift to expect to work with technology vendors that can align the partnership in a way for shared benefit and flexibility enabling growth as market conditions evolve."
Decision Criteria for Enterprise Buyers
Evaluate IFS Asset Pricing If:
- ✅ You manage high asset counts (manufacturing, energy, utilities, logistics)
- ✅ Your AI agent-to-human ratio is >3:1 or projected to reach that
- ✅ You have extensive contractor access needs (seasonal, project-based)
- ✅ Current per-user licensing creates budget unpredictability
- ✅ You want to deploy AI broadly without cost escalation
Stick with Per-User Pricing If:
- ❌ Low asset count, high headcount (professional services, knowledge work)
- ❌ AI agents remain <10% of total user base
- ❌ Workforce is stable, predictable, permanent
- ❌ Asset-based pricing doesn't align with your operational model
What This Means for 2026 Budgets
For CFOs:
- Asset-based pricing creates cost predictability tied to operational growth
- Budget for asset expansion (intentional), not user/agent proliferation (uncontrolled)
- Use IFS pricing as leverage in SAP/Oracle/Infor negotiations
For CIOs:
- Deploy AI wherever it creates value without rationing access
- Eliminate seat management overhead (contractors, temps, agents)
- Align software investment with operational assets, not headcount
For procurement teams:
- Benchmark IFS asset pricing vs incumbent per-user models
- Calculate TCO with AI agent growth projections
- Demand per-asset pricing or equivalent discounts from other vendors
Sources:
- IFS Official Announcement (April 2, 2026)
- PR Newswire
- IDC analyst quotes (Mickey North Rizza, Aly Pinder Jr.)
