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How PassCtrlAI scores your AI readiness

The PassCtrlAI scoring methodology — 6 pillars, weighted scoring, ROI calculation, and why vendor-neutrality is the foundation of everything we do.

How the assessment works

PassCtrlAI produces an AI readiness score for your business using a six-pillar framework, a weighted scoring model, and a deterministic ROI calculation. This page explains the methodology in full: what we measure, how we weight it, how we calculate ROI, and why we built it this way.

This isn’t marketing copy. It’s the actual explanation of how the system works — written for business owners who want to understand what they’re getting before they spend five minutes on it.

The problem with generic AI assessments

Most AI readiness tools are designed for large organisations. They ask the same 20 questions to everyone — regardless of industry, size, or operational context — and return a score that tells you roughly what you already knew: you could be using AI more.

The other common format is a vendor-sponsored assessment: a tool built by an AI software company that scores you against criteria that happen to make their product look like the answer. The output is a sales funnel, not a diagnosis.

We built something different. The PassCtrlAI assessment uses a proprietary scoring methodology powered by AI that generates a business-specific analysis — not a template, not a generic benchmark, not a lead magnet for a consulting engagement. The score is calculated from your specific answers, compared against anonymised Australian SMB data by industry and team size, and interpreted through industry-specific logic that understands the difference between a dental practice and a manufacturing business.

The six pillars

The framework measures six operational dimensions of AI readiness. Each pillar is scored on a 0–100 scale and weighted by its demonstrated impact on AI adoption outcomes across Australian SMBs.

Data 25%

The quality, accessibility, and integration of your business data. AI tools depend on data to produce useful outputs. A business with fragmented, inconsistent, or inaccessible data will get limited value from AI investment regardless of what tools it adopts. This pillar carries the highest weight because it is the most common bottleneck we see.

Process 20%

The maturity of your operational workflows and your current use of automation. This pillar identifies where your business is running manual processes that are candidates for automation, and whether existing tools are being used at full capability before new ones are recommended.

Tech 20%

The adequacy of your current tech stack and the degree to which your tools are integrated. A modern SaaS stack with poor integration creates more manual work than a simpler, well-connected setup. This pillar assesses whether your current platforms have APIs and integration capability.

Team 15%

The capability and capacity of your team to adopt and maintain AI tools. This includes current AI literacy, the presence or absence of shared practices around AI tool use, and whether the business has the internal bandwidth to implement changes.

AI Use-Case 10%

The specific AI opportunities most relevant to your business type, size, and operational profile. This pillar identifies where AI is most likely to generate measurable ROI for a business like yours — not generic AI applications, but specific use cases that match your industry, team structure, and identified process gaps.

Security 10%

Your current security and compliance posture, including how you handle sensitive data, what policies govern staff use of cloud and AI tools, and whether your practices meet the baseline requirements for your industry. This pillar is weighted lower than Data and Process because it is rarely the primary bottleneck to AI adoption — but it is a disqualifying risk if not addressed before deploying AI tools in sensitive contexts.

How we score

Your responses to the 23-question assessment are mapped to pillar scores using a deterministic scoring model — meaning the scores are calculated mathematically, not generated by an AI producing numbers it thinks sound right. The narrative interpretation of those scores is generated by our AI-powered assessment engine, but it interprets your calculated scores rather than inventing them.

Your overall AI Readiness Index score is benchmarked against anonymised data from Australian SMBs of comparable size and industry. The benchmark makes the score meaningful rather than abstract.

How we calculate ROI

The ROI projection in your report is a conservative estimate of the annual time and cost saving available if you close the specific gaps identified in your assessment. It is calculated as follows:

  1. Admin time identified — Based on your reported team size, role mix, and the specific manual processes you’ve indicated are present, we estimate hours per week consumed by tasks with clear automation paths.
  2. Loaded hourly cost — We apply a conservative loaded hourly cost estimate based on your reported team size and industry. For most Australian SMBs, this sits between $45 and $75 per hour depending on sector.
  3. Automation recovery rate — We apply a conservative automation recovery rate to the identified admin hours — typically 40–60% of identified manual time, not 100%, to account for partial automation and ramp-up time.
  4. Annual savings — The recovered hours multiplied by the loaded cost, annualised over 48 working weeks.
  5. Tool investment — The estimated monthly cost of the tools required to close the identified gaps, annualised.
  6. Net ROI — Annual savings minus annual tool investment.

The numbers are conservative by design. We would rather understate the ROI and have you find more value than overstate it and leave you sceptical.

What we don’t do

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Questions about the methodology? Email us at hello@passctrl.ai