Dinis Guarda and Businessabc Launch AI Global Regulations Atlas & Whitepaper, Map AI Laws Across 109 Jurisdictions

The new AI Global Regulations Atlas and companion white paper bring together approximately 1,170 regulatory instruments across 109 countries and jurisdictions, international governance indices, and an interactive global map to help policymakers, urban leaders, and organisations understand the changing regulatory landscape of artificial intelligence.

London, 5 November 2026 — As cities increasingly integrate artificial intelligence into public services, transport systems, urban infrastructure, and digital administration, questions surrounding AI governance, accountability, and regulatory compliance are becoming central to the development of smart cities.

Dinis Guarda, founder and CEO of Ztudium Group and Businessabc.net, has launched the AI Global Regulations Atlas, an interactive regulatory intelligence resource accompanied by a 5,000-word technical white paper. The initiative maps AI legislation, governance frameworks, and regulatory readiness across 109 countries and jurisdictions, bringing together approximately 1,170 regulatory instruments.

The Atlas provides a comparative overview of how governments are regulating AI, from comprehensive risk-based legislation to sector-specific requirements, national strategies, and voluntary guidelines.

For cities investing in AI-enabled infrastructure and public services, understanding these differences is increasingly important. AI applications in urban mobility, public safety, resource management, healthcare, and digital administration can involve complex questions about data protection, transparency, human oversight, and accountability.

The Global AI Governance Gap

One of the central findings highlighted in the Atlas is the widening gap between AI adoption and effective governance.

According to the Global Index on Responsible AI (GIRAI) 2026, which assesses 135 countries using 38 indicators, the global average responsible AI governance score is approximately 35 out of 100.

Europe averages 54, while the Global South averages 27, revealing substantial differences in governance capacity.

Only 55% of active AI governance frameworks demonstrate evidence of implementation. The findings also indicate that 78% of AI frameworks in the Global South are non-binding, compared with 42% in the Global North.

Furthermore, only 54% of countries have a national AI policy, while just 18% require disclosure of AI systems used by governments.

These findings are particularly relevant for cities, where AI systems can directly affect residents through public-sector decisions, infrastructure management, and service delivery.

A city may deploy AI to improve traffic management, for example, but questions about procurement, explainability, public accountability, and data governance remain relevant regardless of the system's technical performance.

Different Regulatory Models for Different Cities

The Atlas identifies six regulatory classifications across its 109 jurisdictions:

32 jurisdictions classified under binding horizontal law
4 under targeted binding measures
2 under promotion laws
6 under sector-led regulation
11 with draft legislation in the pipeline
54 operating primarily through strategies and guidelines

These are Atlas classifications rather than a count of countries with standalone comprehensive AI statutes.

The European Union's AI Act represents a horizontal, risk-based approach, while the United Kingdom follows a more sector-led regulatory model. China has introduced targeted requirements addressing particular technologies and applications.

The EU's Digital Omnibus, Regulation (EU) 2026/1744, has also revised the implementation timetable for high-risk AI obligations. Requirements for Annex III systems will apply from 2 December 2027, while those for Annex I product-related systems will apply from 2 August 2028.

Dinis Guarda on the Need for Global Regulatory Visibility

"AI regulation has moved from principles to obligations in less than a decade, but it has not converged and remains fragmented and disconnected," said Dinis Guarda, founder and CEO of Ztudium and Businessabc.net.

He further explained the practical challenge facing organisations operating internationally:

"A company deploying AI across borders must look at the best regulatory infrastructure and now faces risk tiers in Brussels, compute thresholds in California, use-case rules in Colorado, and targeted measures in Beijing."

The Atlas seeks to make these regulatory differences easier to understand through comparative data, jurisdiction profiles, and direct references to regulatory sources.

Inside the Interactive AI Global Regulations Atlas

The interactive resource includes a world map covering 109 jurisdictions, with countries classified by regulatory model, maturity score from 1 to 5, and legal status.

Users can explore individual jurisdiction profiles, compare AI readiness and responsible governance rankings, and examine regulatory instruments through searchable tables and visualisations.

The Atlas also provides charts showing instruments by type, status, year, and jurisdiction; a regulatory timeline covering 2019 to 2028; comparisons of maximum penalties; and an exposure checker identifying potentially applicable regulatory instruments by market and AI use case.

Its underlying research combines GIRAI, the IMF AI Preparedness Index, Stanford HAI's AI Index 2026, public regulatory trackers including regulations.ai and CASRAI, and primary legislative sources.

The accompanying white paper examines regulatory models, international coordination, enforcement mechanisms, and seven practical compliance steps, including the use of ISO/IEC 42001 as a common AI management framework.

Why AI Regulation Matters for the Future of Cities

The IMF AI Preparedness Index covers 174 economies, with Singapore scoring 0.80, Denmark 0.78, and the United States 0.77. China scores 0.63 and India 0.49.

These differences illustrate the uneven capacity of economies to prepare for AI adoption and governance.

Meanwhile, the Stanford HAI AI Index 2026 reports approximately $285.9 billion in US AI investment in 2025, compared with $20.9 billion in Europe and $12.4 billion in China, alongside 362 documented AI incidents.

For urban leaders, the challenge is not simply to accelerate AI adoption, but to ensure that innovation is accompanied by appropriate safeguards and institutional capacity.

The AI Global Regulations Atlas provides a research resource for examining these questions across jurisdictions.