Score
AIRF Score
Assessment across five pillars with scores from 1 to 5 as a defensible baseline.
AI Responsibility Framework
Clarify responsibility in everyday AI.
AIRF makes responsibility visible, measurable and actionable. Not as ethics prose, but as a practical working instrument for use cases, roles, communication and evidence.
Video
AIRF in a short overview.
QuickStart
What you will have in your hands at the end.
Values
Value Alignment Sheet
A concrete translation of your values for a selected use case.
Register
Register light
Overview of the top five AI tools with risks, owners and review cycles.
Statement
Transparency statement
A first version of clear communication about AI usage for internal and external audiences.
Roadmap
30-60-90 plan
A roadmap with concrete actions for the next three months.
Fairness
Bias / fairness quick scan
Structured first assessment of critical scenarios across eight checkpoints.
Framework
From intention to routines and evidence.
Score / templates / routines / evidence
AIRF flow
A practical path that connects responsibility to real work.
Shared language
One language for executives, business and operational teams.
Maturity model
Five levels for a realistic baseline and target definition.
30-60-90 roadmap
Templates, routines and evidence you can start using immediately.
Daily operations
Responsibility becomes part of roles and routines, not an abstract debate.
The five pillars
A holistic system instead of isolated actions.
Values
Operationalize principles
Values like transparency, privacy or human dignity become concrete guardrails.
Capability
Enable teams
Knowledge and skills for responsible AI are built deliberately.
Governance
Structure and accountability
Clear roles, processes and decision paths make responsibility manageable.
Practice
Anchor in routines
Responsibility is stabilized through reviews, routines and communication formats.
Ethics & fairness
Protect vulnerable groups
Bias risks, escalation paths and impact monitoring are checked systematically.
90 days
A realistic path to visible progress.
30 days
Clarity and kickoff
Register light, value alignment, self-assessment and first responsibilities.
60 days
Capability and routines
Training path, reflection routine, transparency statement and first review cycles.
90 days
Steering and impact
Governance register, bias/fairness scan, lessons learned and KPI logic.
Next step
Responsibility in everyday AI does not have to remain vague.
AIRF is deliberately pragmatic as a QuickStart: with a clear workshop frame, concrete working documents and an actionable 90-day entry.