Preparing for AI regulations: how businesses can stay compliant in an evolving landscape

By The Tech Standard team On Jul 11, 2025

Artificial Intelligence (AI) is no longer just a competitive advantage — it’s becoming a regulated technology. Around the world, governments are crafting policies to ensure that AI systems are fair, transparent, and accountable. From the European Union’s AI Act to draft frameworks in India, the US, and elsewhere, companies deploying AI need to prepare for stricter oversight.

Here’s what you need to know about the emerging AI regulatory environment, and how to align your practices with the principles behind these new rules.

Why AI is being regulated

The widespread use of AI raises concerns about:

Bias and discrimination in automated decision-making
Lack of transparency in how algorithms operate
Privacy violations through data misuse
Potential misuse in sensitive sectors, like healthcare, defense, or law enforcement

Governments aim to mitigate these risks while still encouraging innovation.

Key regulatory developments to watch

The European Union’s AI Act

The EU has proposed the first comprehensive AI law, categorizing AI systems into risk tiers (unacceptable, high, limited, and minimal). High-risk systems — such as those used in hiring, credit scoring, or law enforcement — face stringent obligations for transparency, accuracy, and human oversight.

The US approach

In the US, there isn’t yet a federal AI law, but states and federal agencies are issuing guidance, and the White House released a “Blueprint for an AI Bill of Rights,” outlining principles for safe and ethical AI.

Other countries

China has issued guidelines on deepfakes, algorithmic transparency, and content moderation.
India is consulting on frameworks to ensure responsible AI that fosters innovation without compromising on ethics.

Best practices to stay ahead

1. Map your AI systems

Inventory all AI tools you build, buy, or deploy, and understand their purpose, data inputs, and decision-making processes. Knowing where and how AI is used in your organization is the first step to managing compliance.

2. Assess risk levels

Evaluate your AI systems against emerging risk categories. High-risk applications will likely require audits, impact assessments, and transparency measures.

3. Build transparency

Document how AI models work, what data they use, and how outputs are generated. Be ready to explain these processes to regulators, customers, or employees.

4. Monitor and mitigate bias

Regularly test and validate your models to ensure they do not discriminate against protected groups. Use diverse and representative datasets during training.

5. Establish human oversight

For critical decisions, ensure that humans remain in the loop and can override AI decisions if necessary.

Preparing your team

It’s not just a technical or legal issue — compliance with AI regulations requires collaboration across departments. Train your teams on the risks and responsibilities of using AI responsibly. Engage legal, compliance, data science, and business teams early in the process.

Final thought

AI regulations are coming — and in some places, already here. Businesses that proactively adopt responsible AI practices today will find it easier to comply tomorrow, while earning the trust of users, customers, and regulators.

Instead of viewing regulation as a burden, see it as an opportunity to strengthen governance, improve quality, and lead in a more ethical and sustainable AI-driven future.