From the Emergency Services edition of November 1, 2026
Türkiye creates a General Directorate of 112 Emergency Call and Coordination and plans AI-powered decision-making systems for a service handling nearly 100 million calls a year
Republic of Türkiye Ministry of Interior; General Directorate of 112 Emergency Call and Coordination; Provincial 112 Emergency Call and Coordination Directorates · Emergency call handling and multi-agency dispatch (112) · Türkiye (national, all 81 provinces)
- Publisher
- Daily Sabah (with Anadolu Agency)
- Original publication
- 2026-11-01
- Source retrieved
- 2026-11-02
- Event date
- 2026-10-31
What happened
Daily Sabah, reporting with Anadolu Agency on Nov. 1, says a presidential decree published in the Official Gazette on Saturday (Oct. 31) created a General Directorate of 112 Emergency Call and Coordination under the Interior Ministry, replacing a department-level unit. The 112 centres in all 81 provinces become independent provincial directorates reporting to governors' offices. The directorate will oversee upgrades to the national operations centre, switchboard and communications. Authorities plan AI-powered decision-making systems and big data analysis infrastructure, plus a cybersecurity and disaster recovery centre, along with staff training, regular assessments and drills. The system handles nearly 100 million calls and more than 31 million incidents a year with about 15,000 personnel.
Why it matters
A national single-number emergency system is putting AI decision support into its institutional plan at the same moment it restructures governance. For US state 911 offices and consolidated PSAPs, it is a reference for pairing AI plans with a governance body, cybersecurity and disaster recovery capacity, and staff assessment. Interpretation: transferability to the US is limited because Türkiye's 112 is a centralised, ministry-run model with governor-level reporting.
Evidence and measured results
Wire-based news report of a ministry statement and decree. No technical specification, vendor, budget, timeline or performance metric for the AI systems is given. Call, incident and staffing volumes are ministry figures as reported.
Limitations and uncertainty
Plans only; no AI system, vendor, budget, timeline, accuracy target or evaluation method is described. Single news report based on a government statement. The decree was published Oct. 31 and the report Nov. 1. National, centralised model; limited direct transfer to US county PSAPs.
Put this evidence to work
Lighthouse Advisory interpretation, grounded in this source. Enriched 2026-11-02; this does not change the original publication date. Each role follows the same checklist so takeaways compare across sources.
Sales
Role takeaway
- Customer problem
- A large multi-agency emergency call system wants faster dispatch and better coordination across many provincial centres, and is planning AI decision support without public evaluation criteria.
- Stakeholders
- National interior ministry or state 911 office
- Provincial or regional 112/911 directors
- Call-taking personnel
- Disaster management authority (AFAD-equivalent)
- Data protection authority
- Cybersecurity team
- Discovery questions
- Which decisions would AI support: call classification, resource selection or interagency coordination?
- What baseline dispatch and coordination times exist today?
- Who sets AI standards across many centres, and who evaluates them?
- How will multilingual and accessible channels be handled?
- Value hypothesis
- Interpretation: setting AI standards and evaluation in a central governance body before deployment may reduce uneven adoption across many centres; the source offers no evidence of outcomes.
- Potential engagement
- A governance and evaluation-framework design for AI decision support across a multi-PSAP or statewide 911 system, including baseline measurement.
- Unsupported claims
- AI will speed dispatch
- Any specific vendor or architecture
- Cost savings
- Accuracy of the planned systems
Pre-sales engineering
Role takeaway
- Fit
- Relevant to statewide or consolidated emergency call systems planning shared AI and data platforms across many centres.
- Architecture and integration
- AI decision-making and big data analysis layered over an upgraded national operations centre and switchboard, fed by voice, SMS, web and app channels, with a separate cybersecurity and disaster recovery centre.
- Prerequisites
- Unified call and incident data across centres
- Multichannel and multilingual intake data
- Baseline dispatch and coordination metrics
- Disaster recovery capacity
- Constraints
- No published architecture, vendor or metrics
- Centralised ministry-run model differs from US county PSAPs
- National data aggregation raises privacy obligations
- Security
- Plan access control, retention and data-protection impact assessment for nationally aggregated call data before analytics begin; the source names only a cybersecurity and disaster recovery centre.
- Proof of value
- Measure baseline dispatch times before any AI pilot
- Pilot AI decision support in a subset of centres against matched controls
- Test performance on non-voice and non-Turkish-language reports
Delivery
Role takeaway
- Work
- Stand up governance, data and assessment capability first, then pilot AI decision support with measured baselines.
- Dependencies
- Decree-level mandate and standards body
- Operations centre and switchboard upgrade
- Training programme for call personnel
- Ownership
- National 112 directorate (or US equivalent: state 911 office), with provincial or regional directors running operations.
- Skills and adoption
- The source cites preparatory and in-service training and regular assessments; AI use would need added training on when to override recommendations.
- Governance checkpoints
- Common AI use standards issued before deployment
- Data protection review for big data analysis
- Regular service-quality assessments
- Drills covering AI and system outages
- Acceptance criteria
- Proposed: documented baseline dispatch and coordination times per centre
- Proposed: pilot shows no rise in misclassified calls versus controls
- Proposed: equal performance on SMS, web and multilingual reports
- Risks
- AI plans with no evaluation criteria
- Privacy exposure from national data aggregation
- Uneven provincial adoption
- Single points of failure in a national platform
Implementation considerations
Lighthouse Advisory interpretation across the operating dimensions a public-sector buyer must settle before this evidence becomes a design. Each note answers the question under its heading for this specific source.
Architecture and integration
What must connect, and where does the AI sit in the workflow?
AI decision-making and big data analysis are planned on top of a national operations centre and switchboard upgrade, with a separate cybersecurity and disaster recovery centre. Intake already spans voice, SMS, web reports, the Hayat 112 and Engelsiz 112 services and the AFAD Acil app, so any AI layer would have to handle multichannel and multilingual inputs.
Governance
Who approves, reviews and stays accountable for outcomes?
A new general directorate will set common policies and standards for emergency call services. That creates a single place where AI use rules, evaluation and accountability could sit, though the report does not say any AI-specific rules exist.
Security and privacy
What data, permissions and controls need testing?
Big data analysis of call and incident records at national scale raises data-protection, retention and access questions that the report does not address. The planned cybersecurity and disaster recovery centre is the only named safeguard.
Accessibility and workforce
Who is affected, and what skills or accommodations follow?
About 15,000 personnel staff the system; the plan includes preparatory and in-service training and regular assessments. Engelsiz 112 and service in German, Arabic, English and Russian mean AI decision support would need to work for accessible and multilingual channels.
Procurement
What should contracts, pricing and exit terms secure?
No procurement details yet. Interpretation: a new directorate setting common standards is the likely buyer and standard-setter for AI decision systems and big data infrastructure across 81 provincial directorates.
Operating model
Which teams own the service once it runs?
Provincial 112 centres become independent directorates under governors while a national directorate sets standards, a federated model in which AI tools may be specified nationally but run provincially.
Publication history
- 2026-11-01Emergency Services · Issue 564 resources
Stable resource ID: dailysabah-turkiye-112-general-directorate-ai-decision-systems-big-data-plan-20261101