The RightTime Governance Framework — proportional, auditable AI governance delivered at the right time, in the right way.
Four failure modes that make traditional AI governance unworkable for organisations moving at pace.
9-12 months to implement a governance framework. By the time it's finished, your AI portfolio has changed beyond recognition.
9-12 months typicalOne-size-fits-all frameworks that apply the same controls to a chatbot and a credit scoring model. Proportionality is absent.
One-size-fits-allBig 4 consulting rates of £5-8k per day. A governance implementation costing £750k-£2m before a single control is operational.
£5-8k/dayGovernance bolted on after deployment. Retrospective risk assessments. Evidence assembled after the fact. Regulators see through it.
Bolted on after deploymentNot a framework. Not a methodology deck. Four principles that change how governance actually works inside your organisation.
Governance intensity scales with risk. A low-risk chatbot gets lightweight, automated governance. A high-risk credit scoring model gets intensive oversight, mandatory review cycles, and senior accountability.
Governance embedded at every stage — design, build, test, deploy, operate, retire. Not applied retrospectively. Entry gates at each stage ensure governance travels with the AI system, not behind it.
Audit trails built as you go. Every governance activity produces structured, machine-readable artefacts — not narrative documents assembled under pressure before an audit.
Named humans accountable for AI decisions. Tied to SM&CR for regulated firms. AI accelerates governance operations, but critical decisions remain with people who can be held responsible.
RightTime Governance is aligned to the regulatory and standards frameworks your organisation is measured against.
High-risk AI classification, conformity assessments, technical documentation, and audit trails. Penalties up to 6% of global revenue.
AI and ML model risk management for UK banks. Immediate demand for governance infrastructure and evidence trails.
AI-driven decisions must demonstrate good customer outcomes. SM&CR creates personal liability for senior managers.
The de facto AI management system standard. Certification demand accelerating. Becoming a baseline for regulated organisations.
US risk management framework increasingly referenced by global organisations and regulators as a governance baseline.
AI-specific data protection obligations. DPIAs for automated decision-making. Rights to explanation and human review.
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