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Big Data and Analytics: Elevating Confidence in AI with Security and Risk Management

Artificial Intelligence (AI) is revolutionizing many industries, unlocking unimaginable possibilities and reshaping the way we do business. However, as we embrace AI and make it an integral part of our operations, security, risk and trust management become critical success factors.

According to Gartner, the world's leading technology research and advisory, organizations that effectively implement transparency, trust and security in AI will see their AI models achieve a 50% improvement in bottom line across adoption, business goals and user acceptance until 2026. But how to guarantee this? The answer lies in AI Trust, Risk and Security Management (AI TRiSM).


AI TRiSM: The Backbone of AI Reliability


AI demands new forms of trust, risk and security management that go beyond conventional controls. This is where AI TRiSM comes in, a set of capabilities that ensure the reliability, fidelity, security and privacy of AI models. AI TRiSM is the key to driving better results when it comes to AI adoption, business goals achieved and user acceptance.



Business strategies that support and benefit from AI TRiSM include:


Create secure foundations: AI security is not just about protecting data, it is also about ensuring the integrity of AI systems. A secure base is essential for the reliability and effectiveness of AI.


Maximize the value of data: AI thrives on data. However, proper data management is crucial to ensuring the quality and accuracy of AI-generated insights. AI TRiSM can help maximize the value of data by ensuring it is handled securely and reliably. Protect and extend your brand: AI can be a powerful tool to build your brand reputation. However, any failure in security or risk management can damage your brand. AI TRiSM helps protect your brand by ensuring that AI is used responsibly and safely, thereby minimizing potential risks. Transparency and Reliability: AI TRiSM not only drives security and privacy, but also promotes the transparency and reliability of AI models. For example, it can ensure that AI models are auditable and explainable, helping to build user trust and regulatory compliance. Transparency is also crucial to ensuring that AI is aligned with the organization's ethical values ​​and standards. Risk Management: Risks associated with AI can range from biases and prediction errors to security and privacy issues. AI TRiSM provides a structured approach to risk management, helping organizations to identify, assess and mitigate these risks. In doing so, it can help organizations avoid potential reputational damage, financial loss, and legal issues. Conclusion In short, AI Safety, Risk and Trust Management (AI TRiSM) is an essential component to ensure successful AI implementation. According to Gartner, by operationalizing AI transparency, trust and security, organizations can significantly improve the results of their AI models in terms of adoption, business goals and user acceptance. Therefore, as we move into an era increasingly dominated by AI, it is critical that organizations seriously consider implementing AI TRiSM to ensure they can safely, reliably and effectively harness the power of AI.


by Félix Muniz, CEO - Falqon Specialist in Strategy and Management for Technology Businesses; Startup Maker and Entrepreneur.

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