AI Strategy Consulting

AI strategy consulting helps your business decide where AI will deliver the most value before you spend money building. Marshall Tech, led by Nick Hugh, runs structured AI readiness assessments that produce a prioritised use case roadmap with clear costs, timelines, and expected outcomes.

Clients

Adapt Health, SportsBlock, True Protein

Range

A$5k to A$15k strategy engagement

Delivery

2-week readiness sprint

Most AI projects fail because they start with technology instead of strategy. See also AI consulting in Sydney, AI consulting for small business, and AI automation consulting.

What does AI strategy consulting include?

AI readiness assessment across people, process, and data.
Data audit to identify what is usable, what is missing, and what needs cleaning.
Process mapping to find the highest-value automation and augmentation points.
Use case prioritisation ranked by ROI, feasibility, and risk.
Roadmap delivery with estimated costs, timelines, and sequencing.
Cost-benefit analysis for each recommended use case.

Next step

Start with an AI strategy assessment

A 2-week diagnostic that maps your readiness, identifies the highest-value use cases, and produces a prioritised roadmap. No commitment to implementation required.

Book a discovery call View pricing

Diagnostic sprintA$5k to A$8k

Avg. time to AI adoption2 weeks

Avg. overhead saved$20k/mo

Trusted by Adapt Health, True Protein, SportsBlock, KIKOFF, and UNDR CTRL

AI strategy consulting vs alternatives

Option	Speed	Depth	Best for	Trade-off
AI strategy consultant	2 weeks	High	Businesses that want a prioritised roadmap before spending on implementation	Requires honest access to processes, data, and team capacity
AI agency strategy retainer	Ongoing	Variable	Larger organisations wanting continuous strategic advisory	Higher ongoing cost, slower to produce actionable outputs
DIY research	Weeks to months	Low to medium	Early exploration by capable internal teams	Often stalls at the research phase without external pressure
Vendor demo evaluation	Fast per vendor	Narrow	Teams evaluating a specific tool or platform	Biased toward vendor capabilities, not your actual process needs

Provenance

Last updated: 1 July 2026

Editorial owner: Nick Hugh

Grounded in Marshall Tech AI strategy service data, readiness assessment framework, pricing ranges, named case studies, and published AI readiness guidance.

Proof sources on this site

Adapt Health case study

AI strategy and implementation engagement with measurable outcomes.

AI readiness guide

Published readiness framework that underpins the strategy assessment process.

Nick Hugh profile

Canonical attribution for the principal AI strategy consultant.

Pricing

Published ranges for AI strategy and readiness engagements.

Who needs AI strategy consulting?

Businesses exploring AI adoption that want a structured plan before committing budget.
Teams that have run AI experiments that did not deliver measurable results.
Founders evaluating AI vendors who need an independent assessment of what is actually needed.
Operators who want to understand which processes are ready for AI and which are not.

Frequently Asked Questions

AI strategy consulting focuses on deciding where AI will deliver the most value before you build anything. It produces a prioritised roadmap with costs, timelines, and expected outcomes. Implementation is the build phase that follows. Marshall Tech offers both, but strategy can be engaged independently.

Fixed-scope AI strategy engagements at Marshall Tech range from A$5k to A$15k depending on the number of business units, data sources, and processes assessed. The deliverable is a prioritised use case roadmap with clear cost-benefit analysis.

A typical AI readiness sprint takes two weeks. That includes stakeholder interviews, data audit, process mapping, and the final prioritised roadmap delivery. Larger organisations with multiple business units may need three to four weeks.

You receive an AI readiness scorecard, a process-level opportunity map, a prioritised use case list ranked by ROI and feasibility, estimated costs and timelines for each use case, and a recommended sequencing plan.

Not always, but businesses that skip strategy tend to build the wrong thing first. If you have more than two or three potential AI use cases, or if a previous AI experiment did not land, a strategy engagement prevents wasted spend.

Supporting resources