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Good practice Imported

Ukraine's Wartime AI-in-Education Guidance — A Four-Layer Soft-Law Framework

Ukraine · Kyiv · See the Ukraine profile · See the Kyiv profile

Evidence: Descriptive / self-reported Top 59% 47/100 · Ask Evidence Copilot about this practice

Amid the Russian invasion, Ukraine's Ministry of Education and Ministry of Digital Transformation issued joint AI guidance for schools in May 2024, since analysed as a four-layer soft-law system with EU AI Act-aligned risk rules and inclusion uses for displaced and special-needs

Ukraine's Wartime AI-in-Education Guidance — A Four-Layer Soft-Law Framework

Details

Maturity
Scaling
Promoter
Ministry of Education and Science of Ukraine (with the Ministry of Digital Transformation)
Period
May 2024–ongoing
Keywords
AI policy, wartime education, teacher guidance, soft-law governance, inclusion

Context

On 23 May 2024, Ukraine's Ministry of Education and Science, working with the Ministry of Digital Transformation, published recommendations for teachers and students on using artificial intelligence in schools. The guidance was issued as Ukraine continued to operate its education system under wartime conditions, including mass school displacement and disrupted access to in-person instruction.

Objectives

Give teachers and students practical guidance on classroom AI integration — including prompt-writing techniques, safety protocols and curated lists of recommended AI tools — while establishing risk-based rules for higher-stakes uses.

Activities

A 2026 academic analysis characterises Ukraine's approach as a deliberate choice of non-binding soft law over formal legislation, built in four layers: national guidance from the two ministries; sector-level codes translating principles into institutional templates; institutional policies governing data handling and procurement; and course-level rules such as syllabus clauses. The guidance applies an EU AI Act-aligned risk classification that flags high-stakes uses — admissions, grading, behavioural monitoring — as high-risk, and sets age thresholds of 13 for independent use, with parental consent required between ages 13 and 18. Ukraine has used AI-based tools such as speech-to-text and visual generation specifically to support students with special educational needs and children displaced by the conflict.

Results

The four-layer soft-law framework is publicly documented and has been independently reported by a news agency and analysed academically, with concrete inclusion applications (speech-to-text and visual generation for displaced and special-needs students) distinct from generic guidance.

Conclusions

The soft-law approach is explicitly a trade-off rather than a claim of comprehensiveness: the analysis frames it as pragmatic given wartime capacity constraints, while advising institutions not to wait for a formal statute or outsource pedagogical decisions to technology vendors — an acknowledgement that formal, binding regulation has not yet followed the initial guidance.

Implementation

Indicative cost
Low (< €50k) — Issuing guidance and analysis is low direct cost relative to infrastructure-heavy interventions; implementation cost is distributed across sector bodies and individual institutions building sector/institutional layers.
Time to results
Medium (1–3 years) — Guidance issued May 2024; the four-layer soft-law framework (sector codes, institutional policies, course-level rules) is still being built out under wartime capacity constraints as of the most recent (2026) academic analysis.
Staffing & skills
Ministry of Education and Science of Ukraine, Ministry of Digital Transformation, individual institutions (developing institutional policies), teachers (implementing course-level rules)

Conditions for success

  • multi-layer implementation from national guidance down to course-level rules
  • EU AI Act-aligned risk classification to flag high-stakes uses
  • age-based consent thresholds (13, and 13-18 with parental consent)
  • institutions not deferring pedagogical decisions to technology vendors

Common failure modes

  • deliberately non-binding soft law risks incomplete institutional follow-through, especially under wartime capacity constraints
  • formal, binding regulation has not yet followed the initial guidance

Where it fits

Governance type
national ministry soft-law guidance
Scale
national
Income level
lower-middle-income, wartime conditions

Commonly funded by

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Data sources

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