In most companies today, AI is already inside. Sales drafts proposals with a chatbot, finance asks it for spreadsheet formulas, HR writes job ads with it. The problem: most of this is unofficial, uncontrolled and unmeasured. While the owner asks "should we invest in AI?", the company is already using it.
So the first question is not "which AI tool should we buy?" It is "how ready is our company to get value from AI?" The Digital and AI Readiness Audit answers exactly that.
What we measure
The audit looks at four areas. Each gets its own score, because a company can be strong in one and weak in another.
- Process and data maturity: Are workflows defined? Is data in one place, or scattered across email attachments and personal spreadsheets?
- Systems and integration inventory: Do your ERP, accounting, CRM, e-commerce, banking and production systems talk to each other?
- Team capability: How, how often and with what data do people use AI tools?
- Shadow AI: Which company data goes to which outside AI service, from whose account?
The last point surprises most executives. Pasting a customer list, a quote or a contract into a free AI tool is a serious risk, both for data protection and for trade secrets.
How we do it
The audit is not a survey form. It works on three layers:
- Interviews: Short, structured conversations with management, department heads and frontline teams. This is usually where the real bottlenecks show up.
- Technical review: We go through your system inventory, integration points, data flows and basic security settings.
- Scoring: We turn the findings into a score you can compare with similar companies in your industry.
Being ready for AI is not about buying the most expensive tool. It is about getting the right data to the right person, safely.
What you get
At the end of the audit you have three things:
- An AI Readiness score: A one-page summary across the four areas that you can take to your board.
- A prioritized roadmap: What to do first and what can wait, with estimated cost and impact for each step.
- 30-60-90 day quick wins: Concrete steps that deliver results in the first three months, without waiting for a big transformation program.
What comes after the audit
The audit does not have to end as a report. The findings usually point to one of these next steps: writing AI use and data security policies, bringing scattered systems into a single owner dashboard, putting WhatsApp and email under central control, setting up a private local AI model, or replacing an ageing web platform. The score decides which comes first, not guesswork.
Who it is for
- Companies that want to know where to start before investing in AI
- Leadership teams worried about uncontrolled AI use by employees
- Owners with many systems but no single picture
- Exporters starting to get AI and data security questions from foreign customers
For a first look, try our free AI Readiness Assessment. For an audit tailored to your company, talk to us.