Category: AI Governance

EU AI Act: Transforming the Future of iGaming

The EU AI Act is set to revolutionize the iGaming sector by introducing a harmonized framework for AI use, particularly for high-risk applications like facial recognition. Operators must prepare for compliance by assessing risks, drafting internal codes of practice, and aligning their AI strategies with the new legislation.

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Italy’s Landmark AI Law: A New Era of Governance

Italy is set to make history with the implementation of its comprehensive national Artificial Intelligence Law on October 10, 2025, becoming the first EU member state to adopt such a framework. This landmark legislation emphasizes ethical guidelines and human oversight in AI systems, aiming to balance innovation with fundamental rights protections.

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AI Strategies for Competitive Advantage in Real Estate

Radian’s playbook for AI emphasizes the importance of governance, growth, and operational excellence in the mortgage and real estate sectors. As leaders navigate the complexities of AI adoption, they must balance innovation with compliance, ensuring that technology enhances human elements in the homebuying process.

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Federal Contractors: Embrace the GenAI Revolution

Generative artificial intelligence (GenAI) is transforming how federal agencies and their partners operate, with a significant percentage of federal respondents already using AI daily. As agencies move from pilot programs to full-scale deployment, contractors have new business opportunities to develop secure AI solutions tailored to government needs.

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Italy’s New Artificial Intelligence Law: Key Highlights and Implications

On September 23, 2025, Italy’s new law on artificial intelligence was signed into law, complementing the EU AI Act and establishing guidelines for the use of AI across various sectors. Key provisions include regulations on personal data usage for scientific research, employer obligations regarding AI in the workplace, and specific protections for minors accessing AI technologies.

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Learning from Past Failures in AI Governance

As global leaders gather in Tallinn for the Digital Summit 2025, reflections on Estonia’s Soviet past reveal important lessons for modern AI governance. The article argues for governance models that emphasize diversity, distributed authority, and community-informed design to avoid the pitfalls of past collective failures.

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AI Governance: Balancing Innovation and Global Cooperation

AI global governance is the system of rules and collaborations that countries and organizations are developing to manage artificial intelligence across borders, aiming to ensure its safety, fairness, and utility for all. The urgency for international cooperation arises from shared risks such as misinformation and economic disruption that transcend national boundaries.

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Global AI Governance Initiatives on the Rise

The UN has initiated a global dialogue on AI governance, creating an inclusive space for governments and stakeholders to address pressing AI challenges. As part of this effort, the Independent International Scientific Panel on AI has been established to assess the transformative impact of AI on society, with a call for nominations open until October 31, 2025.

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Ethics in AI Adoption: Avoiding the Trap of Ethics Washing

At the recent ICSAN conference in Lagos, AI governance expert Olajide Olugbade emphasized the importance of establishing effective governance systems for AI adoption to avoid “ethics washing.” He warned that many organizations create ethics offices that serve merely symbolic purposes, lacking the necessary authority to enforce responsible innovation.

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AI Shadow Risks: Protecting Your HR Data Integrity

The integration of GenAI into daily workflows poses significant challenges for Chief Human Resources Officers (CHROs) regarding policy and compliance, with over one-third of Australian professionals uploading sensitive company data into unauthorized AI platforms. This surge in “shadow AI” not only risks data leakage but also exposes organizations to serious regulatory compliance issues, highlighting the urgent need for robust AI governance.

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