How Much Does AI Consulting Cost in Australia? The 2026 Guide

By Greg Markowski / Sep 15, 2026 / Epic IT News

Quick answer: AI consulting cost in Australia runs from about $3,000 for a boutique fixed-scope project to $500,000+ for enterprise programs. Published hourly rates sit at $200 to $500+, strategy engagements at $20,000 to $50,000, and mid-market builds at $50,000 to $250,000. Almost nobody publishes these numbers, which is why we compiled every Australian rate card that is actually public, as at September 2026.

Ask five AI consultancies what a project costs and four will book you a call before showing a number. That is not because the number is unknowable. It is because opacity is a pricing strategy. This guide collects every published Australian figure we could verify, so you can walk into those calls already knowing the market.

Every published AI consulting rate card in Australia

These figures come from each firm’s own published pages, verified in September 2026. Firms not listed here do not publish pricing.

Provider Engagement Published price
Team 400 (Bris, Syd, Melb) Hourly rates $200 to $500+ per hour
Team 400 AI strategy and assessment $20,000 to $50,000 (2 to 4 weeks)
Team 400 Fixed-price Fast Packages From $25,000, 14-day delivery
Team 400 Custom projects $50,000 to $250,000
Sandlabs Discovery sprint $5,000 to $15,000
Sandlabs MVP build $15,000 to $60,000
Sandlabs Growth retainer $5,000 to $15,000 per month
Enterprise Monkey (Melb) AI strategy and roadmap $8,500 to $15,000
Forge & Lever (Perth) Fixed projects From $3,000; support from $1,500 per month
Source Digital (Perth) Consulting and projects From $3,000; projects $3,000 to $25,000

That is the entire public market. Everyone else, from the enterprise consultancies through most of the boutiques, scopes individually. Our guide to the best AI consulting companies in Australia maps who sits in each tier and what pricing model each firm runs.

What the tiers actually mean in dollars

Under $15,000 buys a fixed-scope assessment, a strategy roadmap, or a single small automation from a boutique. This tier answers “where should AI go in my business” or delivers one working workflow. It does not deliver an integrated system.

$20,000 to $60,000 is the proof territory: a proper strategy engagement, a proof of concept against your real data, or a first production build with clean requirements. A PoC at the bottom of this range assumes one use case and tidy data. Messy data, complex logic or a regulated environment pushes you toward the top.

$50,000 to $250,000 is the mid-market build: a production system integrated with your CRM, job management, document or accounting platforms, with testing, deployment and handover. This is where most 50-to-500-staff projects land.

$250,000 and up is enterprise program territory: multi-workstream transformations, governance frameworks for regulated institutions, and anything with a steering committee. If a firm will not publish prices, this is usually the tier it sells to.

Why the rates are high

AI consulting rates run 20 to 40 per cent above general software consulting, and the reason is labour. Senior AI engineers with production experience command salaries of $180,000 to $280,000+ in Australia, and consulting rates carry that cost. Two other multipliers hide in quotes: most model providers price in US dollars, so API costs land roughly 35 to 40 per cent higher for Australian businesses than their US peers, and regulated environments (health, finance, anything touching the Privacy Act) add compliance work that is invisible until the statement of work arrives.

Fixed price or time and materials

Most AI work is quoted one of two ways, and the sequencing matters more than the choice. Time and materials suits discovery and proof-of-concept phases, because you are paying to learn and the scope is genuinely unknown. Fixed price suits the production build, because by then the scope is defined and the risk should sit with the consultant. Be wary of the reverse pattern: a fixed-price discovery (which incentivises a shallow look) followed by an open-ended T&M build (which incentivises a long one).

The cost nobody quotes: month 13

Every figure above buys you a system at go-live. It does not buy monitoring, patching, access control, retraining, governance reviews or support, and AI systems need all of it. Budget at least two to three months of post-launch iteration, then an ongoing operational cost, whether that is a retainer with the builder, internal staff time, or a managed arrangement. If you are weighing whether to run models yourself, we have priced all three ways of running your own AI model separately.

The comparison the rate cards leave out

Every price in the table above assumes a standalone engagement: a firm that arrives knowing nothing about your business, discovers your systems at $200+ per hour, builds, and leaves. There is a second path for businesses that already have a managed IT provider. The discovery is largely already done, because the provider already runs your identity, data and security. The month-13 problem disappears, because operating systems is what an MSP does. And the work lands inside a managed AI arrangement rather than a standalone project premium.

We deliver AI this way, and we price it differently to everyone in the table: a per-seat monthly amount plus a platform fee, not a project rate card. We do not publish the seat rate because it genuinely depends on your environment; your identity setup, data estate and security posture all move it, and a number without that context would mislead you. So speak to us. A free readiness review gets you a fixed per-seat quote against your actual environment, with operation included, and our honest guidance stands either way: if your business is between 10 and 200 staff and you already pay an MSP, ask them for an AI quote before appointing anyone new, whether that MSP is us or not. If the answer is a blank look, that tells you something too, and our comparison of AI-led MSPs versus AI consultancies explains what to do with that information.

What you should do now

Anchor on the published numbers. Walk into any sales call knowing the market: $20,000 to $50,000 for strategy, from $25,000 for a fixed build, $50,000 to $250,000 for custom mid-market work. A quote far outside those bands needs a written justification.

Demand the month-13 line item. Ask every bidder to price the first year of operation, not just the build. A proposal without an operating cost is not cheaper, it is incomplete.

Speak to us before you sign elsewhere. Book a free AI readiness review and we will scope your project against your existing environment, with a per-seat quote and the first year of operation included. If a standalone consultancy is genuinely the better fit, we will say so.

Frequently asked questions

How much does AI consulting cost in Australia?

AI consulting cost in Australia ranges from about $3,000 for boutique fixed-scope projects to $500,000+ for enterprise programs. Published benchmarks: $200 to $500+ per hour, $20,000 to $50,000 for strategy engagements, fixed packages from $25,000, and custom builds of $50,000 to $250,000.

What does an AI proof of concept cost?

Roughly $20,000 for a single use case with clean data, rising toward $50,000 where data is messy, logic is complex, or the environment is regulated. A PoC answers one question: can this work with your data and constraints. It is not a production system.

Why do so few AI consultancies publish prices?

Opacity lets firms price each deal to the client rather than the market. Only a handful of Australian providers publish rates, and enterprise consultancies never do because their engagements are scoped programs. Treat a published rate card as a sign of confidence, and an absent one as a prompt to anchor on the market benchmarks before the first call.

Is AI cheaper through a managed IT provider?

Often, for businesses of 10 to 200 staff. An MSP already knows your systems, so you are not funding discovery at consulting rates, and ongoing operation folds into the existing agreement instead of a separate retainer. Managed AI is typically priced per seat per month plus a platform fee rather than as a project. The trade-off is depth: a novel, complex build may still need a specialist firm.

What ongoing costs does AI have after go-live?

Monitoring, patching, access control, model and prompt maintenance, governance reviews and user support, plus API usage costs that are priced in US dollars. Budget two to three months of post-launch iteration and then a recurring operational cost, whether internal, retained with the builder, or managed by your IT provider.

Want a real number for your environment?

Book a free AI readiness review and get a fixed per-seat quote against your actual environment, with the first year of operation priced in.

Book a Free AI Readiness Review

About the Author
Written by Greg Markowski, Founding Director of Epic IT, a CRN Fast50-recognised Microsoft Solutions Partner managing IT and cybersecurity for Perth businesses since 2003. Greg holds a Degree in Computer Science and a Diploma in Computer Systems Engineering from Edith Cowan University, and is ITIL certified.

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