AI in Practice / Public services · Source-led case

mAigov — public-service information assistant

Published evidence, operating questions and an evaluation plan for a comparable application.

Documented application · Source reviewed 6 November 2026

01

What is established

In a Ministry article dated 14 November 2024, Papastergiou reported that mAigov had answered over 1.3 million citizen questions. This is a historical usage figure, not a current total or an independently verified accuracy or transaction-completion measure.

Primary source ↗

02

The operating problem

Citizens need to understand which procedure applies and what action to take. A fluent answer has limited value when its source is obsolete, its requirements are incomplete or the user cannot reach the actual service.

Citizen questionCurrent authoritative proceduresAssistant responseSource and service hand-offCorrection / human escalation

Illustrative evaluation workflow by AIStrategy.gr; not a disclosure of the organisation’s internal architecture.

03

Design a comparable pilot

Select a small set of procedures with responsible content owners. Build questions covering eligibility boundaries, ambiguous requests, accessibility and recent changes. Test against the approved procedure and assess the hand-off to a human or the transaction.

04

What to measure

  • Correct answer and source coverage on a versioned test set
  • Unsupported or outdated answers
  • Successful hand-off to the right service
  • Accessibility and unresolved user needs
  • Correction time after a procedure changes
05

What the evidence cannot settle

Question counts can increase because a service is useful, confusing or repeatedly fails. Treat information assistance separately from an official administrative decision. Do not infer legal compliance, fairness or accessibility from usage volume.

06

Questions for the project owner

  • What is the baseline, comparison period and representative operating envelope?
  • Which data are missing, and how do those gaps affect decisions?
  • Who can override the system, stop the trial or correct an error?
  • What results remain after integration, review, training and support costs?
07

Scale, revise or stop

Agree thresholds before the trial. Expand only when the responsible team can reproduce useful outcomes, explain remaining errors and sustain the operating process. Revise the design when benefits depend on exclusions that do not reflect normal work.

Editorial boundary. The primary-source account above is distinct from our proposed pilot design. Reported outcomes have not been independently audited by AIStrategy.gr.

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