Consulting-grade methodology.
AI-powered execution.

myAIstrategy does not replace strategy consulting. It executes the same proven methodologies that top consulting firms use — strategic frameworks, structured interviews, multi-perspective analysis, and calibrated scoring — but at a speed, consistency, and cost that makes them accessible to every organisation.

Why this works

A Big 4 consulting engagement follows a well-established process: research the organisation, interview stakeholders, apply analytical frameworks, score against benchmarks, identify threats and opportunities, and synthesise findings into deliverables. The methodology is proven. What varies is who executes it, how long it takes, and how consistent the output is.

myAIstrategy follows the same process — every step. The difference is execution. Six specialist AI advisors apply the frameworks simultaneously rather than sequentially. Every score is calculated against calibrated rubrics with hard boundaries, not estimated by an analyst having a good or bad day. Every finding carries a confidence tag so you know what is verified and what needs validation. And every deliverable is reviewed by an automated quality agent that checks for ten specific failure modes before you see it.

Why six advisors, not one

A consulting team assigns specialists to different workstreams because strategy, technology, finance, workforce, revenue, and leadership require fundamentally different analytical lenses. A single generalist — human or AI — cannot hold all six perspectives at once without compromising depth.

Each of our six advisors operates from a distinct knowledge base with defined expertise, communication style, and analytical frameworks. They do not simply agree with each other. When the Strategy advisor identifies an opportunity, the Finance advisor stress-tests the business case. When Technology proposes an investment, People assesses the workforce impact. This cross-perspective tension is what separates a robust strategy from a slide deck.

Calibrated rubrics, not AI-generated numbers

The most common failure in AI-generated assessments is that scores sound plausible but are not grounded in anything reproducible. An AI model asked to “rate this company's AI exposure on a scale of 1–10” will produce a number. It will not produce the same number twice, and it cannot explain why it chose 7 instead of 6.

Our scoring model uses calibrated rubrics with hard boundaries for each dimension. A workforce replaceability score above 7 requires evidence that more than 50% of the organisation's work is knowledge work. A market velocity score above 7 requires evidence of sub-annual competitive cycles and visible AI-native competitors. These boundaries are not suggestions — they are constraints that prevent score inflation and ensure that different organisations receive meaningfully different scores.

Maturity scores derived from the strategy workshop use deterministic extraction — specific signal phrases in your responses map to specific score adjustments. The arithmetic is exact. The AI generates insight; it does not pick numbers.

Three-tier confidence system

Every finding in your assessment carries one of three confidence tags:

When you provide validated data through the strategy workshop — confirming or correcting an inference — the confidence tag upgrades and the underlying data changes across every analysis and deliverable. This is how a desktop assessment becomes a grounded strategy.

What happens before you see results

Before any strategy deliverable reaches you, an automated quality agent reviews it against ten specific failure modes:

Findings that fail the review are corrected automatically. Narrative tone is actively moderated — language severity is calibrated to each disruption band to prevent the analysis from being more alarming than the evidence supports.

Analysis that speaks your language

Government organisations do not have “customers” — they have citizens. They do not have “revenue” — they have appropriations. Universities measure enrolment, not sales. Not-for-profits track mission impact, not profit margins.

Our analysis adapts every dimension — language, metrics, benchmarks, scoring weights, and policy context — based on whether the organisation is a company, government agency, university, SME, or not-for-profit. Government analysis is grounded in current Australian policy frameworks including the National Framework for Assurance of AI in Government and the DTA's Policy for Responsible Use of AI. This is not a cosmetic word replacement. It reshapes how threats and opportunities are framed, what benchmarks are used, and what language appears in your deliverables.

Proven consulting methodologies, executed by AI

Our analysis is built on six proprietary strategic frameworks developed from established consulting methodologies:

These frameworks are applied to every assessment automatically, weighted for your industry and entity type. They provide the analytical structure that transforms raw data into strategic insight.

How the assessment is built

The sections below describe the specific steps, scoring dimensions, and generation process in detail.

AI Disruption Assessment

The initial scan takes approximately four to five minutes and produces an AI Disruption Snapshot based entirely on publicly available information. No organisational data is required at this stage.

The Eight Dimensions

The AI Disruption Score is calculated across eight weighted dimensions. Four measure exposure, one measures opportunity, and three measure defensibility. Weights reflect relative importance and sum to 10.0, so a perfect score across all dimensions equals 100.

Disruption Bands

AI Strategy Development

When an organisation upgrades to the AI Strategy Pack, the assessment is enriched with organisational data through three inputs: document uploads, a guided strategy workshop, and AI maturity self-assessment.