As Artificial Intelligence (AI) systems increasingly permeate emotionally sensitive and caregiving domains—such as eldercare, education, therapy, and family life—there is a growing need to assess national readiness beyond infrastructure, research output, or innovation metrics. Existing AI-readiness indices often prioritize technical capacity while neglecting caregiving ethics, emotional integration, symbolic trust, and cultural adaptability. Simultaneously, many national AI policies and strategies articulate ethical aspirations without corresponding real-time implementation in relational contexts.

These tensions expose two critical and underexplored gaps: (1) the disconnect between national AI policy and real-time practice in AI–Family Integration (AFI), and (2) the misalignment between conventional AI indices and relational readiness metrics based on AFI.

To address these blind spots, this study introduces the AI–Family Integration Index (AFII)—a ten-dimensional benchmarking framework designed to evaluate countries on emotional, ethical, legal, symbolic, and caregiving preparedness. The AFII comprises dimensions such as emotional literacy, caregiving equity, symbolic legitimacy, youth-AI exposure, consent frameworks, and cultural receptivity. Each dimension was scored on a 0–10 scale using mixed-method analysis, including secondary qualitative and quantitative data, policy reviews, and narrative synthesis. Equal weighting was applied across dimensions to ensure conceptual balance and reflect the interconnected importance of each component. This methodological choice mirrors best practices in composite indices (e.g., the Human Development Index), while also maintaining interpretive equity across culturally diverse nations.

To bring the framework to life, the study integrates real-world examples—such as Singapore’s emotionally intelligent robotics in eldercare and Japan’s symbolic AI design in companionship—to ground abstract dimensions in lived, culturally contextual practices. These narrative insights enhance both the interpretability and policy relevance of the scores.

The AFII was applied to a sample of thirteen culturally and economically diverse countries, including all top 10 countries ranked in the Stanford AI Index (2024). The results reveal striking contrasts between innovation-driven AI adoption and human-centered readiness. While Singapore (9.6) leads globally, nations such as South Korea (8.8) and Japan (8.7) closely follow. The top five countries—Singapore, South Korea, Japan, Sweden (8.6), and the United Kingdom (8.4)—all score above 8.4, reflecting strong alignment between AI policy, emotional intelligence, cultural values, and caregiving integration. In contrast, middle performers like the United States (7.4) and China (7.6), though technologically dominant, exhibit shortfalls in symbolic trust, emotional safety, and caregiving ethics. At the lower end, India (6.0), Brazil (5.2), and South Africa (4.8) show emerging promise but require substantial investment in emotional-AI literacy, inclusive infrastructure, and ethical governance.

A key finding is the gap between ethical policy intent and real-time relational deployment. Singapore, South Korea, and Japan exemplify strong alignment between governance vision and practical rollout. Conversely, France and Germany, despite policy sophistication, reveal slower execution in emotionally grounded domains. This disjunction reveals the need for a robust policy–practice alignment matrix, which the AFII introduces as a diagnostic typology for guiding national strategy.

Another notable insight is the divergence between AFII rankings and the Stanford AI Index. Countries like the U.S. and China rank in the global top two for AI power, yet place 8th and 9th respectively on the AFII. Conversely, relationally advanced nations such as Singapore and Sweden achieve top AFII scores despite more modest technical power rankings. This contrast underscores that AI excellence must incorporate emotional and ethical dimensions—not merely computational strength or research volume.

By embedding emotional and symbolic metrics into a comparative framework, the AFII offers a timely, multidimensional tool for policymakers, ethicists, and technologists. It reframes AI discourse from technocratic performance to relational intelligence, ethical resonance, and caregiving responsibility—defining a path for AI systems that not only think or learn, but relate, care, and belong.