WHODjibouti
Evidence Review for AI-Assisted Age-Friendly Environments (Readvertisement)
WHO is seeking a qualified, eligible and competent proposer for the Evidence Review for AI-Assisted Age-Friendly Environments (Readvertisement) The review will support WHO's work to frame, test and communicate how artificial intelligence can help scale proven age-friendly practices through coordinated, accountable action. For this assignm...
Submission deadline: August 21, 2026 (expired)Type: Tender
Research Contracts, Social Research, Digital Innovation, Feasibility Studies
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Content at a glance
- Tender type:
- Tender
- Contracting authority:
- WHO
- Published:
- August 14, 2026
- Deadline:
- August 21, 2026
- Topic:
- Research Contracts
Tender description
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WHO is seeking a qualified, eligible and competent proposer for the Evidence Review for AI-Assisted Age-Friendly Environments (Readvertisement) The review will support WHO's work to frame, test and communicate how artificial intelligence can help scale proven age-friendly practices through coordinated, accountable action. For this assignment, an AI-assisted age-friendly environment is understood as a human-governed operating model that uses AI-supported data integration and decision support to help communities detect risks earlier, connect older people to appropriate supports, allocate resources fairly, and learn continuously from outcomes. AI is not the intervention itself rather it serves as a coordination layer over prevention, social prescribing, integrated care, age-friendly planning, environmental risk reduction and community-based support. The review should take a broad scoping approach to identify relevant evidence and examples on AI-assisted approaches that support healthy ageing, age-friendly environments, prevention, community-based support, integrated care, social prescribing, environmental risk reduction, and data-informed planning. The four-layer concept developed by WHO WPRO should be used as an initial analytical framework to organize and interpret the evidence, rather than as a restrictive eligibility criterion. The review should also identify relevant evidence or use cases that do not fit neatly within the current framework and advise whether the framework should be refined. The provisional analytical layers are: Layer 1: Place and Environmental Intelligence — AI-supported use of geospatial, climate, built-environment, environmental and service-access data to understand place-based risks, inequities and planning priorities. Layer 2: Individual Change Detection — AI-supported use of opt-in, low-burden individual or household-level data, such as wearables, sensors or other digital signals, to detect meaningful changes in function, wellbeing, risk or
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