The problem

No AI pilot fails because of the technology

It fails because of what’s missing to bring it into operation: clear ownership, an approved architecture, a security concept that actually holds up.

Over 46% of prototypes are discarded before reaching production. Not because of poor models, but because of missing structures.

Governance gap in production readiness

46% of prototypes never make it to production. The most common reason: no one can answer who’s actually accountable for the outcome.

Decisions no one makes

Who approves the system for release? Based on what criteria? In most organizations, there’s no solid answer to that until someone asks.

The regulatory clock is ticking

The EU AI Act is in force. Transparency and competency obligations have applied since August 2026. Waiting is more expensive than acting.

Governance on paper doesn’t work

Gartner calls this state ‘governance on paper’: the framework exists, but operational control doesn’t.

Close the governance gap

AI without control isn't progress.

“Companies that delay governance don’t avoid risk. They accumulate it.”

– Andreas Tschauner, Managing Partner, Auvaria

Facts and Figures

Numbers worth Knowing

8

Questions that determine production readiness

9

TAP dimensions for controlled AI operations

5

Phases to the signed-off approval

3

Maturity levels: Viable, Repeatable, Audit-Ready

The answer

Trusted AI Production Readiness (TAP)

Auvaria’s TAP Framework describes how organizations bring AI systems into operation in a structured way: with clear ownership, a shared platform foundation and an approval that is documented and repeatable.

TAP structures the path to production readiness across five phases and nine dimensions from mobilization to acceptance. The result isn’t a checklist, but a signed-off decision.

Leading companies trust Auvaria

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What does the whitepaper offer?

Orientation, not a checklist

This whitepaper doesn’t tell you which model to choose. It shows what determines success before and after the model: structures, roles, decisions and how operational control is actually built.

  • Why pilots never go live
    What the most common governance gaps are and why they're rarely about the technology.
  • What the EU AI Act really requires
    Which obligations have applied since August 2026 and what the Digital Omnibus on AI actually changed and what it didn't.
  • Eight questions on production readiness
    A direct diagnosis: where governance already works and where the gap lies.
  • TAP fully explained
    Five phases, nine dimensions, three maturity levels and four autonomy levels (A0–A3) with the decision logic for every situation.
  • Steering autonomy deliberately
    How much should an AI system decide on its own? And what that means for platform, approval and control.
Read the whitepaper now

The path to production approval

Five phases, one signed-off decision

Phase 1:
Mobilization

Phase 2:
Requirement Assessment

Phase 3:
Architecture

Phase 4:
Implementation

Phase 5:
Approval and handover

White­paper: Scaling AI means mastering governance

This whitepaper is for decision-makers who have already piloted AI and want to understand why scaling hasn’t happened yet and what can concretely be done to change that.

Free. No account required.

Ready to take the next concrete step?

Let's talk about your AI project

Whether it’s a readiness check, an individual assessment of your AI project or initial questions about concrete implementation, our sales team is here for you directly and will take the time to understand your situation.

We speak openly about effort, timeline and the right starting point. No obligation and no detours through a contact form.

Andreas Tschauner

Managing Partner, Co-Founder