AI consulting and strategy

Readiness is four stages, and we build you through every one.

AI consulting is the work of deciding where AI pays back in a business and how to get there: readiness assessment, strategy, and workshops. Ours ends in a build, not a deck.

Michael Batko
Co-founder, Hourglass AI
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AI consulting is the work of deciding where AI pays back in a business and how to get there. It spans readiness assessment, strategy, and workshops, and in most firms it ends in a document. Ours ends in a build, because a strategy that never ships is just a well-formatted opinion.

What they want from a consultant, and what they get

Businesses arrive with a mix of fear of missing out, operational fatigue, and risk anxiety. What they want is concrete: how does this save my team ten hours a week, is my stack ready, will I breach the Privacy Act. What the industry sells them is often the opposite: a maturity model, a slide deck, and a follow-on engagement to interpret the first one.

My blunt diagnosis of the local market: Australian businesses are stuck in pilot hell, because they lack the AI infrastructure to graduate anything. Pilots run on borrowed data and enthusiasm. Production runs on grounded systems, owners, and governance. Consulting that doesn't build that bridge leaves you exactly where it found you, minus the fee.

Readiness is four stages

Our assessment frame, and we build you through every one of them:

StageThe questionWhat passing looks like
DataCan an agent reach your systems of record?APIs and scoped credentials, not exports
ProcessAre the workflows mapped and priced?Repetitive hours costed honestly
PeopleWho owns the automation once it runs?A named owner inside your team
GovernanceWhat must a human still approve?Explicit gates, an audit log, privacy handled

Security framing matters more than most consultants admit, especially selling into regulated industries: security framing kills the objection, and its absence kills the deal. The compliance layer, the Privacy Act, the OAIC's principles, safe data boundaries, belongs in the plan from day one, not bolted on at deployment.

Right-sized engagement

At small business scale, the engagement should start small enough to be a test, not a commitment. That's the shape of our audit: flat fee, 7 to 14 days, ranked roadmap with a spec and ROI figure per build, credited toward the build itself. What happens after the strategy is the point: the builds live in AI development, the delivery model in automation services, and if you're weighing consultants against doing it in-house with tools, the comparisons section is the honest version of that shortlist.

Common questions

What does an AI consultant actually do?

Maps where AI pays back in your specific business, checks whether your data and systems can support it, and sequences the work. The test of a good one is what you hold at the end: a ranked roadmap with priced builds is an asset, a trends presentation is an expense.

How do I know if my business is ready for AI?

Readiness is four stages: your data is reachable, your processes are mapped, your team has an owner for the work, and your governance rules are explicit. Most businesses discover they're at stage one with messy data, which is fixable and exactly what an assessment is for.

How much should a small business spend on AI consulting?

Start small enough to be a test, not a commitment. Our audit is a flat $2,500, takes 7 to 14 days, and is credited toward the build, doubled to $5,000 credit if you build within 30 days. If a consultant's minimum engagement is a six-figure transformation program, you're buying their process, not your outcome.

Where to start
$2,500flat, AI Audit
  • Every AI opportunity in your business, mapped in 7 to 14 days
  • Ranked roadmap with a spec and ROI figure for each build
  • The fee is credited toward your build, doubled to $5,000 if you build within 30 days
How the audit works

Turn this into real leverage.

We map where AI pays back in your business and build the agents that get you there.

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