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From Prototype to Production: How to Build Responsible and Safe AI for Companies (in Simple Terms)
Artificial intelligence can be a reliable asset for companies, but only if implemented responsibly. Learn what it takes to move from prototype to production and the basic rules for safe, governed, and trustworthy AI. This article explains in simple terms how to use AI with confidence.
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Robust Practices for the Responsible Adoption of Artificial Intelligence in Financial Institutions
The adoption of AI in the financial sector brings major benefits, but also significant risks if not managed responsibly. Robust governance, transparency, and risk assessment practices are essential to turn AI into a safe and competitive advantage. Discover concrete steps for the responsible implementation of AI in your financial institution.
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AI in June 2026
If May 2026 was about integrating AI into products and applications, June brought a new theme: control. While AI kept advancing rapidly, discussions on security, access, limits, controlled rollout, and governance became much more prominent. In June 2026, the focus was not just on more powerful models, but on who controls them and how they…
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AI Governance for Autonomous Systems in the Physical World: Challenges and Solutions
AI governance for physical autonomous systems introduces new challenges of safety, accountability, and ethics, surpassing the boundaries of traditional software-focused frameworks. The article explores specific risks and proposes best practices for responsible regulation of AI interacting with the real world.
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