There is a conversation happening inside most large organisations right now that no vendor wants you to have out loud: the per-user licensing model for enterprise software is fundamentally broken for AI.

IFS, the industrial software company, said it out loud on April 2. They announced a new pricing model that scraps per-user licensing and replaces it with pricing based on operational assets. An energy company managing 400 offshore platforms pays for 400 assets. Not the 12,000 people and automated processes that touch those systems every day.

IFS CEO Mark Moffat was direct about the intent: “This is a clear message to our customers: rather than rationing users, IFS wants you using AI everywhere you can to create value.”

Why Per-User Pricing Breaks AI

The problem is structural. Traditional enterprise software was built around human users. You counted seats. You licensed software to the number of people who logged in. That model made sense when every interaction required a human.

AI changes the interaction model entirely. An intelligent agent can touch a system thousands of times a day. AI assistants interact with platforms on behalf of users, on behalf of other systems, and autonomously as part of automated workflows. Count each interaction as a user, and the costs explode before the value is visible.

The result is what IFS calls “rationing.” Organisations limit where they deploy AI not because the technology isn’t useful but because every expansion triggers a licensing cost spike. The CFO kills the rollout before it scales.

IFS’s new model prices around assets managed, vessels in a fleet, production assets in a plant, infrastructure components in a network, rather than the humans and systems interacting with those assets. The company says this creates metrics that are measurable, auditable, and actually aligned with the value the software provides.

What This Signals for the Industry

IFS is not the largest player in enterprise software, but they work in industries where this problem bites hardest: energy, aerospace, defence, manufacturing, and utilities. These are complex operational environments where a single asset generates interactions across dozens of systems, roles, and automated processes.

That is also exactly where AI has the most to offer. Predictive maintenance, anomaly detection, autonomous scheduling, and supply chain optimisation all generate high-frequency data interactions. Per-user licensing penalises you for deploying AI in the places where it would do the most work.

The broader signal here is that enterprise software pricing is about to face serious pressure. As agentic AI becomes the default way enterprise systems operate, the old model of counting human seats stops reflecting anything meaningful. Vendors that don’t adapt will watch their customers find creative ways around the model or switch to alternatives that don’t penalise deployment.

SAP, Oracle, and ServiceNow have all been grappling with versions of this problem quietly. IFS has made the argument publicly, which puts pressure on everyone else.

What Business Leaders Should Take From This

If you are evaluating enterprise AI platforms right now, licensing structure should be a top-three question in every vendor conversation. Not just what you pay today, but how costs scale as your AI deployment expands.

The right question to ask is: if we automate 30% of our operational interactions with AI agents over the next 18 months, what happens to our software costs? If the answer involves a per-user spike, that vendor’s model does not fit an agentic world.

The companies that will get the most from AI over the next few years are the ones that can deploy it broadly across their operations without cost structures that fight against scale. IFS has positioned itself as a vendor that understands this. Whether their competitors follow is the question worth watching.

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