AI automation cost
How much does AI automation cost?
AI automation has no single price tag, and the honest answer starts with "it depends". What it depends on is knowable: the scope of the work, how many systems it has to connect to, whether you need a one-off build or ongoing managed support, and how it is run day to day. This guide sets out the real cost factors — and how good design keeps the running costs low.
The short answer
AI automation costs depend on scope, integration and ongoing support — not on a fixed price list.
A small, single-task automation that runs on a simple script and a local model is a very different proposition from a connected, multi-step system that touches several of your tools and needs monitoring around the clock. Both are "AI automation", and they sit a long way apart on cost. Rather than quote a number we cannot stand behind, we price each piece of work against what it actually involves. The sections below explain the factors that move the figure up or down, so you can form a realistic picture before a conversation — and that conversation, the free initial consultation, is where a real estimate comes from.
What actually drives the cost
Four things move the cost more than anything else.
How much the system has to do
Automating one repetitive task is modest work. Running a whole process end to end — many steps, decisions, exceptions to handle — is a larger build. Where a job sits on the AI maturity ladder, from a single task to a fully agentic workflow, is the biggest single factor in what it costs.
How many tools it must connect to
An automation that lives in one place is cheaper than one that has to read from your inbox, write to your CRM and update a spreadsheet. Every system it touches adds connection work and testing. Clean, well-documented tools you already use keep this down; tangled or closed systems push it up.
One-off build, or kept running
A build is a one-off cost. Keeping a system healthy — monitoring, fixing, adapting it as your needs change — is an ongoing one. Some clients want the build alone; others want us on hand. Our managed service is optional and priced separately, so you only pay for the support you actually want.
Cloud power vs private local models
Once live, a system has a running cost: the compute and tokens it consumes each time it works. Frontier cloud models are powerful but metered per use; private local models cost little to nothing to run once set up. Which you use, and where, is a design decision that sets your monthly bill for years.
How good design keeps the running cost down
The cheapest system to run is one designed not to waste AI in the first place.
Not everything needs AI. Where a simple, deterministic script does the job reliably and at no ongoing cost, that is what we use — AI is reserved for the problems that genuinely require it. When AI is the right answer, we match each task to the right model: cloud power where capability truly matters, and private local models where cost or data sensitivity call for it. That single discipline is what separates a system that runs up runaway token bills from one that stays cheap to operate.
The effect is real. A bookseller's inventory system we built runs its vision and data-extraction work on local hardware: a roughly nine-hour day of identifying and pricing books by hand became about an hour, processing cost fell by around 80%, and the system runs at roughly £0 ongoing because nothing leaves the machine. A single-family-office finance platform we built does its routine summarising on a local model and only hands the heavy reasoning to a frontier model — so 10-plus scheduled jobs a day run 24/7 without a frontier-sized bill for every step. Good architecture, not a bigger budget, is what makes automation affordable to keep.
To see the kinds of systems these figures come from, the case studies on our homepage walk through each one.
Build cost and running cost are two different things
Treat the one-off build and the ongoing running cost as separate lines — because they behave very differently.
The build is paid once: the design, the implementation, the integration and testing that turns a strategy into a working system. The running cost recurs: model usage, any hosting, and optional managed support. A well-designed system front-loads the thinking so the running cost stays low and predictable — and where we can move work onto local models or simple scripts, that recurring figure can be very small indeed. When you are weighing up AI automation pricing, ask for both numbers; a low build price with an open-ended cloud bill behind it is rarely the cheaper option over a year.
Getting a number you can rely on
A real estimate comes from understanding your specific workflow — which is exactly what the free consultation is for.
Because the factors above vary so much from one business to the next, an honest answer to "how much does AI automation cost" has to be a range until we have seen the actual process. So we start by listening: what the task is, what it touches, how often it runs, and how sensitive the data is. From there we can tell you what is worth doing, what is not, and a realistic cost for the part that is — including the running cost, not just the build. There is no charge for that first conversation and no pressure to proceed.
Frequently asked questions
How much does AI automation cost?
It depends on scope, the number of integrations, and whether you want ongoing managed support. A single-task automation on a local model is modest; a connected, monitored multi-step system is a larger build. We give a realistic figure after a free consultation, once we understand the specific workflow — rather than a headline price we cannot stand behind.
What are the ongoing running costs?
Running cost is the compute and model usage a system consumes each time it works, plus any hosting and optional support. Frontier cloud models are metered per use; private local models cost little to nothing to run once set up. Good design routes each task to the right model, which is what keeps the monthly figure low and predictable.
Is it cheaper to use local AI models?
For the right tasks, yes. Local models can run at close to £0 ongoing and keep data private, which is why we use them where cost or sensitivity calls for it — for example routine summarising. We reserve metered frontier models for the work that genuinely needs their capability, so you are not paying cloud rates for jobs that do not require them.
Do you charge for the initial consultation?
No. The first conversation is free, with no obligation to proceed. We use it to understand your process, tell you honestly where AI does and does not add value, and give you a realistic cost for the part worth doing — including the ongoing running cost, not just the one-off build.
Get a realistic estimate
Tell us about the process that eats hours every week, and we will give you an honest view of what it would cost to automate — and whether it is worth doing at all.