Alpha evaluates AI readiness at the business process level — not the organisation as a whole.

This distinction matters. An organisation may be highly ready in some functions and critically unprepared in others.

By anchoring the assessment to specific processes, Alpha delivers targeted, actionable intelligence rather than a superficial organisational score.

Process definitions across all Alpha Audit assessments are aligned with the APQC Process Classification Framework® (PCF) version 8.0 — the globally recognised open standard for business process taxonomy.

This ensures that the scope of every assessment is consistent, comparable, and industry-agnostic. When you select a business function (e.g. Finance, Human Resources), the processes in scope are drawn directly from the relevant PCF category — giving you a rigorous, standardised baseline for your diagnostic.

Before scoring begins, Alpha Audit captures qualitative context about your organisation:

• Organisation size — headcount and structural configuration
• Sector and operating context — industry background and function-specific considerations
• Current tooling — existing technology and data landscape
• Ambition level — your stated AI transformation objectives

This context shapes how your diagnostic is interpreted and informs the expert review where applicable.

Each process in scope is scored independently across five readiness dimensions:

Pillar	What It Evaluates
Strategy	AI vision, leadership buy-in, and process prioritisation
Data	Data quality, availability, lineage, and governance
Talent	Skills, training capacity, and organisational change readiness
Architecture	Technical infrastructure, integration capability, and tooling maturity
Governance	Accountability frameworks, ethics oversight, and compliance posture

Each pillar produces an independent score. Results are not collapsed into a single aggregate — the per-pillar breakdown is the insight.

In parallel with readiness scoring, Alpha Audit identifies process frictions — structural inefficiencies, manual bottlenecks, and data quality gaps that AI could address.

Frictions are evaluated using a weighted average model that accounts for:

• Frequency — how often the friction occurs
• Impact — the operational or financial cost when it does
• Remediation complexity — the estimated effort to resolve with AI

The resulting Friction Score surfaces where AI investment would generate the highest return — making it a core input to prioritisation.

Your final report contains:

• Per-pillar Readiness Scores for each process assessed
• Friction Score highlighting priority AI intervention areas
• Readiness Summary across all processes in scope
• Recommended Next Steps calibrated to your profile

The report is generated immediately on completion and rendered in-browser. It is secured behind a purchase token after 5 minutes or 80% scroll depth.

The Bundle tier includes a human expert review delivered by an idbokx consultant.

Building directly on your diagnostic data, the review provides:

• Situation overview and stakeholder mapping
• Taxonomy alignment and diagnostic interpretation
• Re-scored readiness assessment with consultant commentary
• Prioritised action plan with enabler notes
• Risk flags and implementation considerations

The review is delivered as a structured written document accessible via a private link, within 21 business days of purchase.