Hitachi Supports Municipal Policy Planning with AI and Future Scenario Simulation Technology
Hitachi, Ltd. has launched an initiative to support municipal policy planning using AI and its proprietary future scenario simulation technology. By modeling causal relationships among indicators such as population, tax revenue, and welfare, and running approximately 20,000 simulations, the project visualizes the impact of policies on the future and identifies key turning points, supporting evidence-based policy making (EBPM).
📋 Article Processing Timeline
- 📰 Published: May 28, 2026 at 11:00
- 🔍 Collected: June 1, 2026 at 01:21 (86h 21m after Published)
- 🤖 AI Analyzed: June 1, 2026 at 23:15 (21h 54m after Collected)
Hitachi, Ltd. (hereinafter referred to as Hitachi) has officially launched an initiative today to support municipal policy planning for complex social challenges using AI and Hitachi’s proprietary future scenario simulation technology.
In this initiative, Hitachi first models the causal relationships between indicators (causal relation model) based on municipal-specific policy considerations such as population, tax revenue, environment, and welfare, as well as past KPI data and survey data from residents and employees. Based on this model, Hitachi runs approximately 20,000 simulations using its unique future scenario simulation technology. AI analyzes and visualizes how the town's future will change when multiple policies are combined, such as "prioritizing child-rearing support" or "prioritizing industrial promotion." It can also specifically indicate future turning points and key events, such as "2030 will be an important turning point for decision-making." Municipalities can use these visualized scenarios to analyze and compare options, thereby examining the direction of high-level plans such as comprehensive plans and specific measures.
Furthermore, this can be utilized to review policies that have already been formulated or are currently being implemented. Since the causal relation model can be used while being revised, it reduces the burden on municipalities in data collection and simulation implementation.
Throughout this process, Hitachi conducts workshops with municipal employees to provide hands-on support for selecting indicators, building causal relation models, and interpreting simulation results. In addition, Hitachi collaborates with partner companies possessing expertise in municipal plan formulation and DX support to assist in incorporating measures and building consensus within the organization. By doing so, Hitachi supports municipalities in examining highly effective policies, creates an environment where staff can grasp issues more personally and promote policies, and contributes to the realization of Evidence-Based Policy Making (EBPM) and better community development.
In this initiative, Hitachi first models the causal relationships between indicators (causal relation model) based on municipal-specific policy considerations such as population, tax revenue, environment, and welfare, as well as past KPI data and survey data from residents and employees. Based on this model, Hitachi runs approximately 20,000 simulations using its unique future scenario simulation technology. AI analyzes and visualizes how the town's future will change when multiple policies are combined, such as "prioritizing child-rearing support" or "prioritizing industrial promotion." It can also specifically indicate future turning points and key events, such as "2030 will be an important turning point for decision-making." Municipalities can use these visualized scenarios to analyze and compare options, thereby examining the direction of high-level plans such as comprehensive plans and specific measures.
Furthermore, this can be utilized to review policies that have already been formulated or are currently being implemented. Since the causal relation model can be used while being revised, it reduces the burden on municipalities in data collection and simulation implementation.
Throughout this process, Hitachi conducts workshops with municipal employees to provide hands-on support for selecting indicators, building causal relation models, and interpreting simulation results. In addition, Hitachi collaborates with partner companies possessing expertise in municipal plan formulation and DX support to assist in incorporating measures and building consensus within the organization. By doing so, Hitachi supports municipalities in examining highly effective policies, creates an environment where staff can grasp issues more personally and promote policies, and contributes to the realization of Evidence-Based Policy Making (EBPM) and better community development.
FAQ
日立が自治体政策検討向けに提供するシミュレーション技術とは？
自治体固有の指標（人口、税収、福祉など）の因果関係をモデル化し、AIを活用して約2万通りの未来シナリオをシミュレーションする技術。
自治体は本取り組みでどのような分析が可能になるか？
「子育て支援」や「産業振興」などの施策を組み合わせた際に、将来どのようにまちが変化するかを分析・可視化し、意思決定の重要な分岐点やターニングポイントを把握できる。
本取り組みは既存の政策見直しにも活用できるか？
はい、策定済みや実施中の政策の見直しにも活用可能です。因果連関モデルは改訂可能で、自治体のデータ収集やシミュレーションにかかる負荷を低減します。
日立はどのように自治体をサポートするか？
指標選定からモデル構築、シミュレーション結果の解釈まで、自治体職員とワークショップ等を通じて伴走型で支援します。
本技術の活用実績はどれくらいあるか？
これまでさまざまな自治体やエネルギー・製造分野などの民間団体を含め、20件以上の活用実績があります。