We’ve often talked about the (perhaps fabled) future land where software is sold on outcomes-based pricing. Admittedly, this appears to only ever be realistically achievable in extremely measured, stable and predictable deployment scenarios. IFS has gone some way to progressing this space with a new approach designed to change how enterprise AI is bought and deployed. The company’s new model aligns software investment with the operational assets customers manufacture, manage and maintain, such as vessels, components, infrastructure, or production assets.
Organisations now have the freedom to deploy what the company likes to call “Industrial AI” wherever it creates value, without constraint and without the fear of escalating costs.
By moving away from user-based licensing to a model grounded in what has been (arguably quite fairly) described as “operational reality”, IFS is enabling customers to pay by assets, rather than users. For example, an energy company managing 400 offshore assets pays based on those 400 assets rather than the 12,000 people and machines that need to access the data.
The result (says IFS) is that customers get more predictable costs that align with operations, enabling projects to expand and enterprises to grow without the constraints of user-based licensing. Ebullient about the prospects on offer here (and claiming to have potentially shaken up the enterprise software space at large) the company thinks that the move will force the broader industry to rethink how it packages and prices software.
Did somebody say outcomes?
Edging us tantalisingly close to talking about software-driven outcomes, IFS details its pricing model in more depth and says that IFS technology is no longer just enabling workers to do more; it is directly “driving work and outcomes” with a commercial model directly tied and aligned to the success of IFS’s customers.
The model is designed for “industrial systems of action” (which we can infer to include large-scale enterprise machinery that resides across IFS’ six key selected verticals: aerospace & defence, energy, utilities & resources, construction & engineering, manufacturing, service industries, telecommunications, life sciences and maritime), where software investment aligns with the operational environments a company manages rather than the number of users accessing the system.
Price the work, not the workers
“This is a clear message to our customers: rather than rationing users, IFS wants a business to be using AI everywhere it you can to create value. 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,” said Mark Moffat, CEO, at IFS.
Moffat and team talk about the need to drive greater value for customers by creating a system with metrics that are measurable, auditable and transparent, ensuring organisations pay for the operational value the system supports, not every individual, contractor, or automated process interacting with it.
This evolution in pricing directly supports IFS’s Industrial AI strategy and anticipates changing market needs. At its core, this shift is about enabling customers to navigate an increasingly AI-driven industrial landscape and capitalise on the opportunities it presents.
According to Mickey North Rizza, group vice-president for enterprise software 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. This new methodology will help clients sustain their economic value.”
Rizza’s colleague Aly Pinder Jr, a research VP for aftermarket services strategies back up that comment and says that asset-centric organisations 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.
A long-term shift is afoot
“In software, there’s an ongoing long-term shift away from charging for access (which includes seats, if you think about it) and towards charging based on value delivered. This includes usage-based pricing, but smart vendors are finding better value proxies. The best look and feel like outcome-based pricing,” said Griffin Parry, CEO and co-founder of m3ter, a data infrastructure company that specialises in usage-based billing and pricing software.
Eric Avery, head of global infrastructure and data at Sumo Logic largely agrees with this whole discussion. He says that AI pricing is one of the most heated and controversial topics in the industry right now for a few key driving factors.
“AI service offerings are relatively new in terms of consumer adoption and widespread generalization, which creates a market with very little historical data to draw on for what works and what doesn’t,” said Avery. “Additionally, the price point is often heavily dependent on a software solution’s specific data handling infrastructure and its customers’ engagement level. These two drivers lead to a recipe for AI processing success: be attuned to your customers’ usage profile, optimise your internal infrastructure and data costs and collect AI feature data rapidly by offering AI services quickly at low/no cost and price regulate later.”
He advises that attacking the problem in this way should us a well-informed and scalable pricing model out of the gate.
Why now?
So is now the right time to do this?
Yes, says IFS, because industrial organisations are on the “cusp of an unprecedented expansion” in terms of what they can produce, maintain, and deliver using Industrial AI. Therefore, says the company, there is no reason for it to be constrained.