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Good practice Imported

TAMM — Abu Dhabi's AI-Native Proactive Government Services Platform

United Arab Emirates · Abu Dhabi · See the United Arab Emirates profile · See the Abu Dhabi profile

Evidence: Descriptive / self-reported Top 83% 40/100 · Ask Evidence Copilot about this practice

Abu Dhabi's DGE has deployed 100+ AI use cases across 40+ government entities on the TAMM platform, aiming for proactive, application-free services by 2027 — though published evidence so far is scale and investment figures, not independently measured outcomes.

100 use cases
AI use cases deployed (as of Oct 2025)
40 entities
Government entities using AI use cases (as of Oct 2025)
13 AED billion
Digital Strategy 2025-2027 budget (2025-2027)
95 %
DGE employees completing AI training (as of Oct 2025)

Details

Maturity
Scaling
Promoter
Department of Government Enablement – Abu Dhabi (DGE)
Period
2025–2027 (Digital Strategy 2025-2027; TAMM 4.0 launched Oct 2025)
Keywords
digital government, proactive services, public administration

Context

The Department of Government Enablement – Abu Dhabi (DGE) operates TAMM, the emirate's unified digital-government platform, under the Abu Dhabi Government Digital Strategy 2025-2027.

Objectives

The strategy aims to make government services proactive and application-free by 2027, automatically triggering entitlements based on citizen life events rather than requiring separate applications.

Activities

DGE has deployed more than 100 AI use cases across more than 40 government entities, including a multilingual virtual assistant, machine-learning-based approval prediction, and proactive service triggers. TAMM 4.0, unveiled at GITEX Global in October 2025, added real-time rules-based compliance automation and predictive resource allocation. Over 95% of DGE's 30,000-plus employees completed AI training, and every entity now has a Chief Data and AI Officer.

Results

All published figures — use-case counts, entity counts, training completion and budget — are self-reported by DGE and repeated without independent scrutiny by press coverage; no third-party measurement of processing-time reduction, error rates or citizen satisfaction attributable to the AI features has been published.

Conclusions

TAMM demonstrates large-scale operational deployment of AI across government services, but the 'fully AI-native by 2027' ambition remains a stated target rather than a verified outcome.

Implementation
Indicative cost
Very high (> €5M)
Time to results
Medium (1–3 years)
Staffing & skills
Department of Government Enablement – Abu Dhabi (DGE), Chief Data and AI Officer per government entity

Conditions for success

  • Dedicated AED 13 billion strategy budget
  • Emirate-wide mandate creating Chief Data and AI Officer roles across entities
  • Large-scale staff AI training (95%+ of 30,000+ employees)

Common failure modes

  • No independent oversight body, audit process or appeal mechanism for AI-driven decisions described
  • No third-party outcome measurement published for any AI feature specifically
  • Relies on a large dedicated budget and governance mandate that few jurisdictions can replicate

Where it fits

Governance type
emirate-level digital government agency
Scale
government-wide (40+ entities)
Income level
high

Commonly funded by

National / regional programmes

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Data sources

Where this practice's information was retrieved from, and when.

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