A repeatable method for finding where AI creates commercial value.
The AI Growth Audit is not a generic website review. It runs on two pieces of repeatable IP: an evidence model that keeps every finding honest, and a nine-pillar maturity model that scores the full commercial system. Judge the method by its output, not by its promises.
The evidence model: Observed, Assumed, Recommended
Every finding separates what is verifiable from what is inferred, then proposes a specific change. It is what keeps the audit defensible and easy to act on.
Observed
What we can verify from the outside: your visible website, public signals, structured data, and the buyer path as it exists today. Observations are facts, not opinions.
Assumed
What we infer but would confirm with you: internal conversion rates, CRM reality, follow-up timing, and margin by segment. Assumptions are labeled so confidence is never overstated.
Recommended
The specific change we propose, with its expected commercial effect and the evidence it rests on. Every recommendation traces back to an observation or a clearly stated assumption.
The nine-pillar maturity model
We score nine pillars of the commercial system from 0 to 5. The score is a shared starting point, not a grade. It shows where the highest-leverage gap sits today and what a realistic near-term target looks like.
Buyer-facing clarity and positioning
Whether a visitor understands the fit, the offer, and the next step.
AI and answer-engine discoverability
Whether buyers and AI-assisted search can read, compare, and recommend you.
Website conversion and buyer journey
Whether the path from first visit to qualified action is clear and credible.
Lead capture and qualification
Whether forms and intake collect the context a real response needs.
CRM and follow-up discipline
Whether leads keep momentum through stages, handoffs, and response time.
Sales enablement and technical proof
Whether the proof a buyer needs sits where the decision happens.
Measurement and attribution
Whether you can see source, conversion, and where demand actually leaks.
Commercial workflow and automation readiness
Whether manual, repeatable work is ready for useful automation or AI assistance.
Data governance and security posture
Whether trust, privacy, and procurement answers are ready before they are asked.
How the method runs in five business days
Intake and commercial context, then a website and AI-visibility review, then lead capture and CRM gap analysis, then opportunity mapping, and finally a prioritized 30-day roadmap with an executive walkthrough. Each day removes uncertainty until the roadmap is specific enough to act on without a large transformation bet.
The deliverable applies the evidence model to each pillar: a ranked opportunity inventory, a priority matrix, and a roadmap that separates quick internal fixes from work worth implementing next.
See the method applied
The sample report shows the full method applied to an anonymized mid-market manufacturer. The audit applies it to your business, scored and prioritized, with a 30-day roadmap your team can act on.