At Marino, we've long believed that technology only earns trust when it's built with people at the centre. "Software Made Human" captured that. But software was always the medium. It is the application layer.
What regulated industries are now grappling with directly, is intelligence. How it reasons, makes decisions, and acts in the world. That's the core layer we’re working in. AI is the material we are now working with - and "Intelligence Made Human" is our focus.
Right now, nowhere is that idea more visible, than in AI governance. As we work with clients across financial services, healthcare, and the public sector to deploy AI responsibly, understanding the global regulatory landscape is core to how we think and operate.
It's also central to Evident, a platform for compliant and governed AI deployment in regulated industries, created by the Marino team.
Here's how the major frameworks compare and what they mean in practice.
We previously posted about how the EU AI Act is the world's first comprehensive AI legislation. Enforcement began April 2, 2025.
The US takes a more fragmented approach.
For agentic AI, the lack of federal uniformity creates complexity. If you're building agents for US deployment, you need to navigate both sectoral regulations (e.g. healthcare HIPAA, financial regulations) and emerging state laws.
China has taken one of the more prescriptive regulatory approaches:
The data sovereignty requirements are particularly relevant for agentic AI. Any agent operating in China must comply with data localisation requirements, government alignment and content review obligations, and security assessment requirements for models with public influence.
The UK's self-styled pro-innovation, non-statutory approach centres on five principles -- safety, transparency, fairness, accountability, and contestability -- with sector-specific regulators (CMA, ICO, MHRA) overseeing AI in their respective domains. The AI Safety Institute leads world-class frontier AI testing, particularly relevant for agentic systems.
For agentic AI, financial services agents are regulated by the FCA, healthcare agents by the MHRA, and so on. It is light-touch at the framework level. But sector-specific regulation can still carry real weight.
Singapore has been proactive with its Model AI Act (2024). That was the first draft framework of its kind. It takes a risk-based approach similar to the EU. But is more guidance-oriented, with practical tools like AI Verify for testing AI systems. The focus on transparency, fairness, and accountability makes it one of the more developer-friendly frameworks globally.
Brazil's AI Bill of Rights (PL 2338/2023) is notably human-centred, emphasising transparency, non-discrimination, and the right to human review. A new national AI regulatory authority (SANAI) will have enforcement powers. For agentic AI, the emphasis on human review rights and transparency aligns closely with how we approach responsible deployment at Marino -- the human always needs to remain meaningfully in the loop.
If you're deploying agentic AI globally, your checklist expands:
Global agentic AI deployment requires multi-jurisdictional competence. The EU AI Act sets a high bar. Many other countries are developing their own frameworks.
At Marino Software, we are building platforms specifically to help regulated-sector organisations navigate this complexity - so that compliance becomes an enabler of confident AI adoption. Building in governance from the start, is our default. It avoids costly remediation later. Intelligence Made Human means building that trust from the ground up.
EU AI Act / NIST AI Risk Management Framework 2.0 / China Interim Measures for Generative AI / UK AI Regulation: A Pro-Innovation Approach / Singapore Model AI Governance Framework / Brazil AI Bill
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