UN Digital Economy Governance Program Opens at BEDI: An Operations Playbook for City-Scale AI
The United Nations International Digital Economy Governance and Leadership Capacity Building Programme opened at Beijing Electronic Digital & Intelligence (BEDI). A delegation of 34 ministerial and municipal representatives from 17 countries toured the Beijing Digital Economy Computing Power Center, planned and operated by BEDI, to study how urban AI infrastructure can translate into measurable productivity.
Co-hosted by UNITAR, the Global Digital Economy City Alliance (DEC40), the Beijing Municipal Bureau of Economy and Information Technology, and the Administrative Committee of Beijing Economic-Technological Development Area, the program is organized by the Global SDGs and Leadership Development Center. It is guided by the UN Sustainable Development Goals and the Global Digital Compact, with an aim to share proven governance practices, support digital transformation in developing countries, and build an inclusive, sustainable digital ecosystem.
From Computing Power to Capability
In a session on scaling AI adoption, Zhao Hongyu, Vice President of Strategic Consulting at BEDI, and experts from the Global SDGs and Leadership Development Center focused on a practical question: how do cities move from investing in compute to building AI capability that delivers outcomes? With cities differing in maturity and industry mix, BEDI's Spark * Platform applies a full-stack model and a "one-strategy-per-locality" operating approach to solve the real bottlenecks of digital-intelligence upgrade.
The Spark Approach in One Page
- 1 city-level AI foundation: shared infrastructure, orchestration, and dynamic resource management.
- 4 core capabilities: integrated data, computing, model, and application layers that work as a single pipeline.
- N local scenarios: a portfolio of priority use cases driven by local demand and value.
- 6 priority fields: including technology, industry, and government services, with additional fields defined by each city.
This model creates a commercial closed loop through dynamic computing-power allocation and ecosystem enablement. It turns a central AI foundation into repeatable outcomes across departments and industries.
Use Cases Operations Teams Can Replicate
- Batch AI video generation for e-commerce and short-form content pipelines.
- AI-personalized home renovation design for the home furnishing sector.
- AI-powered digital profiles for city tourism and cultural creativity.
- AI courses for key primary and secondary schools in Beijing.
BEDI has partnered with more than 20 cities and built a diverse enablement map across healthcare, government services, education, manufacturing, and cultural tourism. The throughline: full-stack integration plus an industrial-operations layer that makes AI productive in the field.
What This Means for Operations Leaders
- Shift from assets to outcomes: Treat GPUs and models as means to an SLA. Frame every initiative around time-to-value, cost per task, and quality targets.
- Adopt "one-strategy-per-locality": Segment by site, region, or business line. Standardize the stack, localize scenarios and KPIs.
- Stand up an AI foundation: Central data access, model serving, feature stores, observability, and workload scheduling for elastic compute.
- Build the industrial-operations layer: Roles, runbooks, MLOps/LLMOps, security, procurement, and partner management across the ecosystem.
- Portfolio thinking for N scenarios: Start with a tight set of high-leverage use cases; scale with shared components and governance.
Metrics That Keep You Honest
- Unit economics: cost per inference/task, GPU hours per outcome.
- Service performance: latency, uptime, throughput by scenario.
- Quality: accuracy/recall or task-specific quality scores; drift rate and re-train cadence.
- Adoption: active users, automation rate, cycle-time reduction, rework rate.
- Time to deploy: from approved brief to first production output.
Risk, Trust, and Sustainability-Built Into Operations
- Trustworthy AI: model governance, evaluation gates, human-in-the-loop for high-impact steps, incident response.
- Secure data flows: data classification, privacy controls, lineage, and encrypted movement across environments and partners.
- Green digital transformation: workload placement, energy-aware scheduling, and utilization targets tied to cost and emissions.
BEDI plans to deepen cooperation with the United Nations and other international bodies on these fronts, sharing technology, playbooks, and talent development so more cities can scale safely and efficiently.
90-Day Implementation Checklist
- Identify 2-3 high-value scenarios; baselines and hard targets in place.
- Stand up core platform services: data access, model serving, monitoring, and access controls.
- Pilot dynamic compute allocation; set utilization and cost thresholds with auto-scaling.
- Assemble a cross-functional squad (ops, data, engineering, security, legal); define RACI and on-call.
- Ship pilots in 6-8 weeks; review against targets; codify runbooks; expand to the next N scenarios.
For practical playbooks and tools that help teams make AI productive across workflows, see AI for Operations.
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