AI Will Break Property-Based Pricing
And What this Means for the Local Government Software Market
I’ve been asked a lot about TechnologyOne’s AI offering, PLUS, since it was announced in October last year. Most of the questions start in a similar place. How does it compare on price? What does it actually cost to run? And increasingly, how well does it fit, architecturally and commercially, against other AI platforms? They’re good questions. But the moment you start pulling on PLUS, you’re analysing something slightly deeper than an AI product. You’re analysing the business model underneath it.
It has taken a while, but everyone is comfortable calling TechnologyOne a SaaS company now. They offer a form of cloud delivery, they have built into a subscription revenue business model, and they provide continuous updates. On the surface, it fits. But there has also always been a quiet mismatch sitting underneath both the architecture and the economics, and AI will increasingly expose it.
TechnologyOne doesn’t price like SaaS in the way the market now understands it. It anchors pricing to the economic footprint of the organisation (rateable properties), not the consumption footprint (users) of the system. That has allowed it to avoid the classic SaaS mechanics of seat expansion, licence optimisation, and user churn. It behaves less like a SaaS platform and more like a utility tied to the size of the council. That has allowed it to be stable, predictable, and highly effective in the ERP era.
The infrastructure architecture reinforces this position. Running on Amazon Web Services with managed environments is not the same as operating a fully shared, multi-tenant runtime. Platforms like Salesforce and ServiceNow are designed to share everything except the data. That’s what allows them to align product, pricing, and scale so tightly. TechnologyOne sits somewhere different. A single code line, delivered as a service, but with enough separation in the environment to justify a different economic model.
None of this is a flaw. If anything it explains their success both in the customer and equity markets. In fact, it even explains something more important. It explains why they haven’t had to change. Local government is a market defined by stability, low risk tolerance, and slow structural change. TechnologyOne’s model has been almost perfectly tuned to that reality.
They’ve captured stable customers and delivered predictable growth by leveraging high switching costs. It has allowed them to modernise delivery in their own way and at their own pace, but without needing to modernise economics. They moved to cloud, adopted global SaaS language, and evolved the product without fundamentally disturbing how company (i.e. investor) value was captured. That has worked while the unit of value has remained stable. But now AI is changing the unit of scale.
In a traditional ERP environment, system activity is a rough proxy for organisational size. More properties equals more transactions equals more staff interactions. You could price against the size of the council and be broadly aligned to the amount of work being done. But in an AI-driven environment, that link breaks.
A council with 10,000 properties could generate vastly different levels of system activity depending on how aggressively it adopts automation. One might use AI to assist staff at the margins. Another might automate entire decision pathways, compliance processes, and customer interactions. The difference in system workload is no longer marginal. It’s exponential. That creates a structural tension inside the current model.
Therefore if pricing remains anchored to properties while the volume of work being executed by the system increases dramatically, the cost to serve rises without a corresponding increase in revenue. That’s why the cost question about AI is so important. AI can pretty quickly stop looking like a margin enhancer and start to look like a margin risk. Not because the technology doesn’t work, but because the commercial model isn’t designed to capture it. That is, unless those costs are pushed on to the client.
This is why the shift we are seeing from vendors like Microsoft and ServiceNow and Salesforce is so important. Their pricing models are moving, however imperfectly, toward consumption signals like per-user copilots, per-workflow execution, and usage-based constructs. They are aligning to the unit that actually scales in an AI world. That unit is “the work”.
Which naturally leads to the question many are now asking. Can TechnologyOne partner its way through this? On the surface, it’s a compelling path. Let Microsoft, ServiceNow and others provide the high-frequency AI execution layer. Let TechnologyOne remain the trusted system of record. Integrate the two and move forward without disrupting the core model. And in the short to medium term, that works.
In fact, it’s already happening. In many cases, it appears to be driven by the customer base themselves, rather than centrally led by TechnologyOne. Councils are experimenting with AI well beyond PLUS. Whether that be through Microsoft layers, or automation through ServiceNow, or marketing or customer engagement through Salesforce, or even content coherence through Glean. All of whicvh give broad access to every LLM available in the market, at the pace of the market.
Meanwhile TechnologyOne continues to defend its anchor position in finance, regulatory, assets and core records. This is creating a clean conceptual split between systems that store the truth and systems that act on it. But while that split holds for a long time if architected by the client, it doesn’t hold forever in a partner model.
Because the system that sits in the flow of work becomes the one handling requests, and decisions, and the automation, and the interactions and inevitably becomes the centre of gravity. It begins to own the experience and shape the workflows and captures the operational data that increasingly defines value. It becomes obvious to everyone where the value lies.
Over time, the commercial fear is that the system of record risks becoming a dependency rather than the platform. So partnerships, in that sense, don’t resolve the tension. They do defer it, and in other cases, amplify it.
Regardless, the volume of work still increases and the cost to serve still rises. But the value created by that work begins to accumulate in the partner layer. Which means the conversation about PLUS, and about AI more broadly, cannot stop at capability or partnership but has to come back to the operating model.
TechnologyOne will continue to introduce AI capabilities. And it follows that every successful AI capability will increase the amount of work being executed by the AI system. In the current model, that increased activity has no natural economic expression (because TechnologyOne’s model doesn’t price activity). That creates a disconnect. System usage can scale rapidly, while revenue remains anchored to relatively static measures like the rate base.
In the short term, we see what’s happening now. AI modules drive an uplift in ACV and ARR at contract renewal time. But without a mechanism to price the underlying activity, that uplift risks being episodic rather than structural.
Over time, this puts pressure on both Revenue Per Customer (RPC) and Net Revenue Retention (NRR). Revenue per customer becomes even less reflective of actual system usage (broadly tracked today as module access), and expansion depends more on discrete pricing events than on organic growth in workload determined by cost.
That leaves two options. They absorb the increasing cost to serve, or introduce new charges to recover it. Neither is comfortable when undertaken as “make good” or “reckoning” provisions in the contract. Especially where pricing predictability has been a core tenet of the sector. But also in a market where competitors are aligning pricing more closely to consumption, it’s definitely not a position that holds indefinitely.
Which means the question is no longer whether TechnologyOne can “do AI”, we’ve already seen it can at some level. The question is whether its current model can absorb it. And that’s where the idea of “reinvention” starts to appear.
But this isn’t reinvention in the way people instinctively think about it. There will be no collapse of the current platform or a sudden pivot away from ERP. It can be something far more subtle, albeit more difficult. And that is realignment from how value is captured to how value is now created.
Because for most of its history, TechnologyOne has been able to anchor value in what a council is based on its size, structure and footprint. But AI shifts that anchor point. Value will increasingly sit in what the system does and the decisions it makes and the work it executes and the interactions it automates.
That shift doesn’t require TechnologyOne to stop being what it is. But it does require it to finally evolve and improve how it participates in that work. It could be a commercial model that introduces a second axis tied to usage or automation. Or a product narrative that moves from system of record to system of execution. And over time, an architectural direction that supports better higher-frequency, lower-friction work across the platform. So also improvements in the underlying content, service and identity ontologies.
Partnerships can help accelerate that journey by bringing capability and keeping TechnologyOne connected to the flow of work. But they are only a bridge, because ultimately, this is not a question of capability but one of realigning from pricing based on what a council is to pricing based on what a council’s systems actually do. That is why property-based pricing, which once looked like a perfect fit for the sector, now starts to look less like a strength, and more like a constraint on its future.
The important thing for councils to understand is that vendors will evolve because they have to. But councils don’t need to wait for that evolution to be complete. The ones that move early won’t just adopt AI faster, they’ll define where value sits in their environment before someone else does. And in relation to AI, that may be the most important decision of all.