Smart cities are positioned as the vanguard of sustainable urban transformation. Combining artificial intelligence (AI), Internet of Things (IoT), and data-driven governance, they promise cleaner air, faster transport, and digital services at scale. But reality shows a more complex picture. Despite more than 1,000 active smart city initiatives globally, many are struggling with stalled execution, low public trust, and poor returns on investment.
China’s Xiong’an New Area is one such cautionary tale as we reported before. Designed as a model for future cities, it was forecast to house up to 3 million people. By 2024, it had reached just 1.2 million – showing a central flaw in the global smart city experiment: cities can be technologically advanced and yet fail socially, economically, and environmentally.
- 1 What Smart Cities Are Meant to Do
- 2 A Global Divide in Smart City Maturity
- 3 What This Means for Policy and Planning
- 4 Top Reasons Smart Cities Fail + Case Studies in Overreach
- 5 The Digital Tools That Could Still Save the Model
- 6 What Makes a Smart City Actually Work?
- 7 Cities Can’t Just Be Smart – They Must Be Human
What Smart Cities Are Meant to Do
At their core, smart cities integrate digital systems to improve urban services. Their technological foundation typically includes:
- IoT networks for monitoring air quality, traffic, energy, and water.
- AI platforms for automating public service delivery and emergency management.
- Big data analytics for infrastructure planning and citizen feedback analysis.
- 5G connectivity to enable real-time, high-volume data exchange.
These capabilities are intended to align with Sustainable Development Goals (SDGs), especially SDG 11 (Sustainable Cities and Communities), SDG 7 (Clean Energy), and SDG 13 (Climate Action)un_smart_city_outlook.
A Global Divide in Smart City Maturity
The Regional Smart City Performance Table from 2024 reveals striking disparities in how regions approach smart city development, particularly in terms of governance infrastructure, public engagement, funding models, and environmental accountability.
| Region | Smart City Units (%) | Active Citizen Engagement (%) | Private Sector Funding (%) | Environmental Monitoring (%) |
|---|---|---|---|---|
| North America | 92 | 34 | 18 | 79 |
| Europe | 88 | 45 | 21 | 90 |
| Asia | 75 | 28 | 14 | 85 |
| Africa | 36 | 15 | 9 | 62 |
| Latin America & Caribbean | 58 | 22 | 11 | 74 |
| Oceania | 71 | 30 | 16 | 80 |
Key Findings and Implications
1. Governance Capacity Is Uneven
- North America (92%) and Europe (88%) lead in establishing smart city governance units—typically specialized agencies or interdepartmental task forces with decision-making authority.
- In contrast, Africa lags at just 36%, indicating that more than half of municipalities in the region lack dedicated structures to oversee digital urban transformation. This correlates with limited project continuity and weak monitoring.
2. Citizen Engagement Is Critically Low Globally
- Even in leading regions like Europe (45%), fewer than half of cities report active or very active citizen participation.
- In Africa, just 15% of cities have meaningful public involvement. This reinforces concerns that many smart cities are being designed “for” rather than “with” residents.
- As noted in the World Smart Cities Outlook 2024, cities with higher citizen engagement often perform better on social resilience and service alignmentun_smart_city_outlook.
3. Private Investment Lags Behind Public Funding
- Globally, smart cities remain heavily dependent on public financing. Only 13% of all smart city projects globally are primarily funded by the private sector.
- Europe (21%) and North America (18%) show slightly stronger private investment, reflecting better-developed PPP frameworks.
- Africa (9%) and Latin America (11%) show constrained private participation, limiting innovation scalability and financial sustainability.
4. Environmental Accountability Varies by Region
- While Europe (90%) and Asia (85%) report high rates of environmental monitoring, Africa (62%) and Latin America (74%) lag.
- Inadequate environmental oversight undermines claims of sustainability and poses risks for climate adaptation, particularly in regions already vulnerable to climate impacts.
Regional Trends: Strategic Takeaways
| Region | Strengths | Gaps & Risks |
|---|---|---|
| North America | Strong governance; robust data platforms | Low civic engagement; moderate environmental oversight |
| Europe | Highest performance across most indicators | Overreliance on public funding; still low public input |
| Asia | Rapid tech integration and scaling | Participation and equity concerns |
| Africa | Emerging grassroots innovation | Severe infrastructure and governance deficits |
| LatAm/Caribbean | Mid-level maturity, innovation hubs in cities | Financial and organizational fragility |
| Oceania | Stable implementation, decent monitoring | Participation and funding still developing |
What This Means for Policy and Planning
To truly fulfill the smart city promise, policymakers must shift focus from tech-led to needs-led approaches:
- Build smart city units where absent, especially in Africa and Latin America, with donor support and national coordination.
- Boost civic participation using hybrid models of in-person and digital engagement—deliberative platforms, participatory budgeting, co-design labs.
- Facilitate private-public partnerships with transparent risk-sharing and outcome-based procurement.
- Standardize environmental monitoring, making it a non-negotiable requirement of all smart city plans.
Top Reasons Smart Cities Fail + Case Studies in Overreach
Smart cities often fail not because of a lack of technology, but due to deeper structural, social, and governance issues. One of the most common reasons is the absence of clearly defined, human-centered goals. Many initiatives prioritize the deployment of cutting-edge technologies over addressing the actual needs of residents. As a result, projects may deliver impressive digital infrastructure but fall short in areas like housing, mobility, public health, or social inclusion. This disconnect between technological innovation and everyday urban challenges often undermines public support and long-term impact.
Governance Fragmentation
Governance fragmentation is another major cause of failure. Smart city programs frequently suffer from siloed planning, where city departments operate independently without integrating efforts. This issue is compounded by misalignment between national and local strategies, leading to duplicated initiatives or competing priorities. Without strong interdepartmental coordination and participatory planning mechanisms, many projects struggle to deliver coherent or scalable results.
Data Governance
Data governance also poses a critical challenge. Successful smart cities depend on reliable, secure, and interoperable data systems, yet many lack open data standards, unified platforms, and robust privacy safeguards. These deficiencies not only hinder effective decision-making but also erode public trust—especially when data is collected without transparency or accountability.
Proprietary Technologies + Single-Vendor Ecosystems
A further obstacle is the reliance on proprietary technologies and single-vendor ecosystems. This creates vendor lock-in, which limits flexibility, raises long-term costs, and restricts the ability to adapt to evolving needs. Instead of building modular, open systems that cities can maintain and upgrade independently, many opt for quick deployments that come with significant strategic trade-offs.
Equity and Inclusion Overlooked
Crucially, equity and inclusion are often overlooked. Smart city efforts that fail to consider the digital divide risk deepening existing inequalities. Marginalized groups – whether due to income, age, disability, or geography – may be excluded from both access to services and participation in design processes. This exclusion not only undermines the legitimacy of smart city efforts but also reduces their overall effectiveness.
In addition to these core issues, many cities face challenges such as unrealistic timelines, vague performance indicators, limited digital literacy among staff and residents, underfunded public-private partnerships, and a lack of environmental foresight – particularly in terms of energy use and electronic waste generated by smart infrastructure. Taken together, these factors explain why many smart cities underdeliver, despite the promise of transformative technology.
The Smart Cities Outlook 2024 also identifies recurring causes behind failed or stalled initiatives:
- Xiong’an (China): Lacked economic gravity and social vibrancy. Despite full 5G coverage and AI-managed infrastructure, it failed to attract residents and investors at the expected scale.
- Masdar (UAE): Promised zero-carbon development but has missed nearly every major milestone and now operates as a partial, commercially driven zone rather than a fully realized urban ecosystem.
- NEOM (Saudi Arabia): Now scaled back due to human rights concerns, cost overruns, and doubts about its logistical viability .
These failures demonstrate that innovation without inclusion results in underutilized infrastructure, stranded assets, and reputational harm.
The Digital Tools That Could Still Save the Model
While the techno-centric model has its limits, smart technologies still offer essential tools for improving urban resilience—if deployed with governance reforms and community input.
AI for Equity
AI can dynamically adjust transit routes to serve lower-income neighborhoods or anticipate public health needs through predictive analytics. However, without transparency and fairness audits, algorithmic systems can reinforce bias rather than solve it.
IoT for Basic Services
In Nairobi and Bangalore, smart meters and microgrids have enabled access to clean water and electricity in informal settlements—through pay-as-you-go models tailored to irregular incomes.
Data + People = Better Outcomes
Cities like Bogotá and Paris have begun integrating citizen-generated data into municipal dashboards. This helps co-create policies—from bike lane placement to air quality alerts—that reflect real community needsun_smart_city_outlook.
What Makes a Smart City Actually Work?
The Old Model (Tech-Led)
- Centralized design
- Emphasis on hardware over governance
- Little to no civic participation
The New Model (Needs-Led)
- Community co-design
- Interoperable data governance
- Investment in long-term capacity, not just installations
The Smart Cities Outlook 2024 recommends embedding inclusive planning frameworks, participatory decision-making, and multi-level monitoring into every smart city policy to ensure impact beyond infrastructure.
Cities Can’t Just Be Smart – They Must Be Human
Without civic trust, inclusive funding, and ecological accountability, smart cities risk becoming “ghost grids” – well-connected but empty. Xiong’an is not an isolated case; it is a systems warning. Cities are complex ecosystems, not engineering projects.
To move forward, we must reframe success: not by megabytes transferred, but by lives improved, emissions avoided, and communities strengthened. If AI, IoT, and big data are to deliver on their promise, they must serve – not substitute – democratic, just urban development.
