Manual & Reactive
People are the integration layer.
AI tools may be present, but people still move information between systems and hold the process together.
Next: Choose one frequent, measurable workflow and make its data path explicit.
AI readiness assessment
Find your AI readiness phase.
An AI readiness assessment shows whether your workflows, systems, data, controls and operating ownership are ready to support AI in production. Our four-phase maturity model identifies where implementation is blocked and what needs to change next.
Built for established SMEs
Five operating dimensions
No stack replacement assumed
Readiness console
Operating foundations
Workflow design01
Systems and data02
Production delivery03
Governance and control04
Measurement and ownership05
01
02
03
04
Directional result across workflow, data, delivery, governance and ownership.
Assess
Workflow, data, delivery, governance and ownership
Understand
The phase you are in and the constraint holding it there
Act
A practical next move grounded in implementation readiness
The four-phase model
Readiness is not about how many AI tools you use.
It is about whether the business can connect data, redesign workflows, govern decisions and measure what runs. The model separates visible experimentation from the operating foundations needed to scale.
Piloting & Stuck
Useful pilots do not become operations.
Teams can demonstrate useful AI, but pilots depend on manual work, isolated data or one-off ownership.
Next: Define exception paths, controls, success measures and the route into production.
Scaling with AI
Connected workflows produce measurable value.
Priority workflows are connected, governed and measurable, with named owners and explicit controls.
Next: Standardise the connection and control layer so each new workflow is faster to deploy.
AI-Native
Operating capability compounds.
AI is embedded across core workflows with clear ownership, measurement and continuous improvement.
Next: Manage the portfolio continuously and govern change across workflows.
FragmentedAI-native ›
Five-dimension self-assessment
Score the foundations, not the ambition.
Choose the statement that best reflects how the business operates today. The result is directional, not a certification. It is designed to expose the implementation constraint that matters most.
Dimension 01
Workflow design
Dimension 02
Systems and data
Dimension 03
Production delivery
Dimension 04
Governance and control
Dimension 05
Measurement and ownership
01
Manual & Reactive
Map the workflow, establish a baseline and identify the systems, data and owner involved.
02
Piloting & Stuck
Define controls, exception handling, production ownership and the measurable outcome before scaling.
03
Scaling with AI
Standardise reusable data connections, controls and operating patterns across the next workflows.
04
AI-Native
Manage change, performance and risk across workflows while compounding reusable capability.
From direction to evidence
Discover tests readiness against a real workflow.
A self-assessment can show where to look. Discover validates the answer using a real operational bottleneck, the systems involved and a sample of your own data. We map the workflow, test the data path and build one working automation so the next decision is based on evidence rather than a slide deck.
Request a Discover callWorking proof
One automation built around a real operational bottleneck and sample of your own data.
Existing stack
The workflow is mapped around the systems your team already relies on.
Clear economics
Discover starts from €5,000 and is credited against Build if you proceed.
Governed delivery
EU-hosted infrastructure with explicit human decisions and inspectable controls.
30.4%
of medium EU enterprises used AI in 2025, compared with 17.0% of small enterprises. Adoption is growing, but adoption alone does not establish production readiness.
Eurostat sourceReadiness FAQ
Questions before you act.
Clear answers for operational, technical and economic buyers moving from AI interest into implementation.
What makes a business ready for AI automation?+
A business is ready when it has a bounded workflow, accessible data, clear decision rules, named ownership, exception handling, human controls and a measurable operating outcome. It does not need perfect data or a new technology stack before starting.
Is this assessment a certification or formal audit?+
No. It is a directional self-assessment based on &native.ai's implementation model. Discover is the deeper validation step because it examines a real workflow, systems and data.
Do we need to replace our ERP or CRM first?+
Usually not. Readiness is more often about making the data path and workflow explicit, then connecting the systems already in use. Replacement only makes sense where the current system creates a genuine constraint.
Can we start if our data is messy?+
Yes, if one bounded workflow has enough accessible data to test. Discover identifies which data problems matter for that workflow instead of treating a broad clean-up programme as a prerequisite.
How do GDPR and the EU AI Act affect readiness?+
Readiness includes knowing what data a workflow uses, what the model can see and do, where human approval is required, and how actions are logged. Governance belongs in the operating design, not as a separate paper exercise after deployment.
What happens after the assessment?+
You can use the result internally or validate it through Discover. If there is a fit, &native.ai maps the workflow and builds a working proof using real data before a larger Build decision.
Start with Discover
Show us the workflow that should work better.
Tell us where work is getting stuck. We will review the context and follow up to arrange a focused Discover call.
What happens next
- 01We arrange a call with the right operational and technical focus.
- 02We review the workflow, systems and business context together.
- 03If there is a fit, Discover starts from €5,000 and is credited against Build.