Paid AI Audit Land-and-Expand
Diagnose business pain with AI, sell the audit, then implement the best solutions
- Difficulty
- Moderate
- Time to result
- ~weeks to results
- Steps
- 7
- Confidence
- 96%
The paid AI audit starts with a structured conversation about what the owner dislikes, cannot fix, or repeatedly struggles with in the business. With permission, the consultant records and transcribes the discussion, then asks an AI model to identify problems, automation opportunities, and candidate solutions. The consultant interrogates promising recommendations, checks their feasibility, and converts the analysis into a concise report prioritized by impact, cost, and implementation difficulty. The audit is sold as a useful standalone diagnosis rather than given away as disguised sales material. It also creates a land-and-expand path: once the business understands its best opportunities, the consultant can implement a voice agent, chatbot, custom skill, workflow, training program, or other appropriate solution.
Origin
Chris Koerner described paid AI audits as a current, validated service that can begin with business owners already inside a person's sphere of influence. Extracted from Marketing Against the Grain.
Core principles
- 01Begin with the owner's problems rather than a predetermined tool
- 02Record the discovery conversation so details are not lost
- 03Use AI to expand analysis, not replace judgment
- 04Make the audit valuable as a standalone product
- 05Use diagnosis to identify higher-value implementation work
How to run it
- 1
Find an accessible business
Start with a business owner in your existing network who is willing to discuss real operational problems.
Pro tip Choose a business with enough recurring activity for improvements to produce measurable value.
Watch out A friendly relationship does not remove the need to define confidentiality and scope.
- 2
Run pain-centered discovery
Ask what the owner hates, loves, cannot fix, and spends too much time or money doing.
Pro tip Follow vague complaints with questions about frequency, current workarounds, and financial consequences.
Watch out Do not force every issue into an AI-shaped solution.
- 3
Capture the conversation
Record the discussion with explicit permission and produce a transcript for analysis.
Pro tip Label speakers and preserve concrete examples, systems, constraints, and metrics.
Watch out Remove sensitive information before uploading material to services that are not approved for it.
- 4
Generate candidate interventions
Give the transcript and business context to a capable AI model and ask it to identify problems and possible AI-enabled responses.
Pro tip Ask the model to separate quick wins from integrations requiring engineering or process change.
Watch out Model suggestions are hypotheses, not validated recommendations.
- 5
Interrogate and prioritize
Explore the strongest suggestions, verify technical claims, and rank them by impact, feasibility, risk, and time to value.
Pro tip Discard clever ideas that do not solve a costly or frequent problem.
Watch out Do not recommend systems you cannot safely implement or support.
- 6
Deliver the paid audit
Present the evidence, prioritized opportunities, expected outcomes, requirements, and recommended sequence in a concise report.
Pro tip Include a first-action plan the owner can use even without hiring you again.
Watch out A long AI-generated PDF is not valuable unless it is specific, accurate, and prioritized.
- 7
Expand into implementation
Offer to build or coordinate the highest-value solutions after the owner accepts the diagnosis.
Pro tip Scope each implementation separately with success metrics and support terms.
Watch out Do not let the audit fee conceal pressure to buy unsuitable follow-on work.
In the wild
A consultant interviews a business owner at a coffee shop about missed calls, repetitive questions, and scheduling delays. After analyzing the authorized recording, the consultant identifies an inbound voice agent as the strongest quick win and documents the expected workflow and economics.
→ The owner receives a useful diagnosis and can separately hire the consultant to implement the voice agent.
A small company first buys an audit and basic training on Claude and ChatGPT. The audit then identifies two repetitive internal tasks suitable for custom skills, while a more complex integration is deferred until the company has engineering support.
→ The engagement expands in proportion to the company's readiness instead of overselling technical complexity.
Common mistakes
Uploading confidential data blindly
Recordings may contain customer, employee, financial, or proprietary information. Obtain permission, minimize sensitive data, and use appropriately governed tools.
Delivering raw model output
AI-generated suggestions require verification, prioritization, and business judgment. An unedited response is not a professional audit.
Prescribing before discovery
Starting with a favorite tool produces generic recommendations. Begin with the owner's actual problems and constraints.
Is it for you?
Best for
It is best for AI-literate consultants who can conduct discovery, validate recommendations, and coordinate implementation.
Not ideal for
It is not ideal for inexperienced sellers who would present unverified model output as expert advice.
From the transcript
“and that is AI audits, paid AI audits as a service.”
“What do you hate about your business? What do you love about your business? What problem can you just not seem to fix with your…”
“So it can be profitable as a standalone service, but it could be very profitable if you use that as a reason to show your…”
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