Public-Sector AI Readiness

Definition

Public-Sector AI Readiness is the systematic design and evaluation of public-sector ai readiness within the capacity of public institutions to procure, govern, deploy and evaluate AI in ways that deliver public value.

Why this matters

Weak public-sector ai readiness can lead to unsafe deployment, unlawful or unauthorised action, wasted public resources, loss of rights, poor accountability and declining institutional trust.

Research questions

Which controls, evidence and institutional arrangements make public-sector ai readiness effective in practice, and how do outcomes vary by sector, system risk, organisational maturity and operating context?

Hypotheses

An explicit, testable and continuously evidenced approach to public-sector ai readiness, with clear ownership, independent review, runtime telemetry and recovery, will outperform policy-only or periodic compliance approaches.

Proposed methods

capability maturity assessment; procurement review; service-design research; workforce study; benefit evaluation; rights-impact assessment; stakeholder interviews; document and control review; fault and incident simulation; longitudinal implementation assessment; methods adapted specifically to Public-Sector AI Readiness

Stakeholders and beneficiaries

citizens; public servants; executives; boards; regulators; auditors; legal and risk teams; technology teams; service users; civil society; suppliers