AI Automation Pricing in Australia: What It Costs

One thing worth saying before the numbers. Most firms selling automation are marketing agencies. They will build you a workflow and hand it over. We are a managed service provider first, so we build the automation and then run, monitor and secure it under the same agreement that covers the rest of your IT. Our published response targets are 30 minutes for a critical incident and 2 hours for a high priority one during business hours. When an automation breaks at 7am and it is the thing that invoices your clients, that distinction is the whole ballgame.

What automation projects cost

These are averages, not a price list. They cover the work most small and medium businesses ask us for. Complex builds sit well outside them: a multi-site integration across legacy systems, or an automation carrying compliance and audit obligations, can run past $100,000. Every engagement starts with process discovery, because a fixed price on an unmapped process is a guess. Discovery is quoted separately and its output is a scope you can take to anyone.

• •Process discovery and automation audit: $1,500 to $3,000, fixed fee
• •Single workflow across 2 to 3 systems: $2,500 to $5,000
• •Multi-workflow build, 3 to 6 processes with custom API work: $8,000 to $20,000
• •AI agent or document processing build: $6,000 to $25,000
• •Changes and additions after handover: $120 to $250 per hour, depending on the work
• •Minimum engagement: $1,500

Timeframes track the bands. A single workflow runs 1 to 3 weeks from scope to live. A department-wide build runs 4 to 10 weeks. User numbers are scoped into the project rather than charged per seat, so a ten person team and a fifty person team pay the same for the same workflow unless the licensing genuinely differs.

Ongoing support and monitoring

Automations break quietly. An API changes, a credential expires, a vendor deprecates an endpoint, and nobody notices until the month-end numbers are wrong. A monitoring and support retainer runs $250 to $1,500 per month depending on how many workflows you are running and how business-critical they are. That covers alerting, fixes, credential rotation and small adjustments.

If you already have a managed IT agreement with us, automation monitoring folds into it rather than sitting as a separate line.

What it costs to run, separate from what it costs to build

This is the part most quotes leave out, and it is where budgets get broken. Running costs are passed through at cost. We do not mark them up.

Platform licences

Zapier, Make and their equivalents charge by task volume. A light setup sits at $30 to $150 per month. Once volume climbs, the same platform can reach $4,000 to $5,000 per year, which is often more than the build cost. Self-hosted n8n running on infrastructure you already pay for removes that line entirely, and it is the reason we ask about expected volume during discovery rather than after.

AI model usage

There is no honest fixed monthly figure here, and anyone quoting one is guessing. Model cost is metered by usage, and it comes in two shapes that businesses regularly confuse:

• •Seat subscriptions cover a person using an AI assistant at their desk. They are licensed per user and per month.
• •Metered API access covers an automation running without a person present. It is billed per million tokens of text in and out. Published rates sit around US$5 in and US$25 out per million tokens for the top tier models, dropping to roughly US$1 and US$5 for the small fast ones.

A staff seat does not cover an unattended workflow, so a business running both usually pays both. The saving grace is that most workflow steps are short, so a typical automation costs dollars to low tens of dollars a month to run rather than hundreds. We estimate it from your real transaction volume during discovery and put it in the quote as an estimate, clearly labelled, not as a fixed fee.

Plenty of automation has no AI running cost at all

Not everything labelled automation needs a language model. Syncing time entries from practice management software into Xero, keeping stock levels aligned across an online store and two shopfronts, routing a form submission into a CRM and triggering the follow-up: these are deterministic integrations. They run on rules, they cost nothing per transaction beyond the platform licence, and they are usually the highest return work in a business because they replace repetitive keying rather than judgement.

Bringing a model in makes sense where the input is unstructured, such as reading supplier invoices, classifying inbound email or summarising a call. Ask any provider which of your processes actually need a model. If the answer is all of them, keep looking.

What moves the price

Two businesses can ask for the same automation and get quotes that differ by a factor of three. These are the five things that account for most of that spread, and they are worth checking before you compare any AI automation pricing.

• •Whether the systems have an API. A platform with a documented API is straightforward. One that only exports CSVs, or has no API at all, can double the build.
• •How well the process is documented. If three people do the same task three different ways, discovery has to settle that before anything gets built.
• •Transaction volume. Ten records a day and ten thousand are different builds, and different platform tiers.
• •Error handling requirements. A workflow that can safely fail and retry is cheaper than one that touches money or patient records and cannot.
• •Compliance and data residency. Keeping data in Australia, restricting what leaves your tenancy, and meeting industry obligations all add scope. This overlaps directly with cyber security work.

Questions worth asking before you sign

• •What will this cost to run for twelve months, including platform licences and model usage?
• •Who fixes it when it breaks, how fast, and is that written down?
• •Do we own the automation and the credentials, or does it live in your account?
• •Where does our data go, and does any of it leave Australia?
• •Which of these processes genuinely need AI, and which are ordinary integrations?
• •What happens to the automation when a staff member leaves and their credentials are disabled?

That last question catches out more automations than any technical failure. A workflow built on one person's login stops the day they leave.

This article reflects best practices as of the publication date. Technology and security recommendations evolve, so verify current guidance with the original sources or our team before acting.