AI Readiness Score, our own assessment methodology

Every yesfor.ai audit ends with a single number: the AI Readiness Score. A number from 0 to 100, split across eight organizational areas. It shows where a company is ready and where it is blocked.

No interpretation. No "it depends". A number.

Why a separate methodology

The available AI readiness frameworks (Gartner AI Maturity Model, MIT Sloan AI Maturity, McKinsey AI Quotient) are good, but they have three problems in the Polish context:

• Technology-focused. Most models assess "AI capabilities", what a company has already done with AI. That is a question after the fact. We care about readiness before deployment.
• Too general. A 1-5 scale across five dimensions does not give a concrete roadmap.
• International. Western models do not account for the specifics of the Polish market.

The yesfor.ai AI Readiness Score is operational, it points to concrete blockers to fix.

Eight areas

The 100-point score is split across eight areas. The weights are uneven, reflecting the real criticality of each for a successful deployment.

Processes (15 points)

Are the company's key business processes documented, do they have owners, do they have metrics?

What earns points: BPMN documentation, clear ownership, monitored metrics. What loses points: "the processes live in people's heads", no owners, ad-hoc decisions.

Data (20 points, the heaviest weight)

The quality, availability, and governance of operational data.

What earns points: a data warehouse or lake with governance, one master record per entity, a quality audit. What loses points: data scattered across more than five systems with no integration, no owner, "Excel as a database".

IT architecture (10 points)

The state of the infrastructure, integrations, security, scalability.

Team (15 points)

Competencies, mindset, readiness to work alongside AI.

Governance (10 points)

Decisions around AI: who approves, who monitors, who responds.

Strategy (10 points)

Is AI part of the company's strategy, or an ad-hoc project?

ROI Framework (10 points)

Can the company measure the business effect of IT and AI projects?

Change Management (10 points)

The company's experience in carrying out organizational change.

How we measure it

In each area: several concrete questions on a 0-3 scale.

• 0, does not exist, no process
• 1, exists ad-hoc, not systematic
• 2, exists, systematic, but with gaps
• 3, exists, mature, monitored

Reading the result

0-39 NOT READY. An AI deployment means burning budget. Start with STRUCTURE.

40-59 CAUTIOUS. Selective deployments in single processes.

60-79 READY. You can start an AI pilot.

80-100 AI-READY. Scaling. Multiple use cases. ROI in weeks.

An example

A mid-sized freight forwarding company, 800 people, two years after a failed chatbot deployment. Audit result: Processes 8/15, Data 6/20, IT architecture 7/10, Team 9/15, Governance 3/10, Strategy 5/10, ROI Framework 4/10, Change Management 6/10.

Total: 48/100, CAUTIOUS.

Recommendation: a 6-week STRUCTURE phase (main focus: data and governance), and in parallel an AI pilot for one process that scores above 80%, automating quote preparation.

What comes next

The AI Readiness Score is not a one-off. It is worth repeating every 6 months. The number does not lie. Either the data is in one place or it is not. Either the teams know why, or they do not.

This is an audit, not a marketing workshop.