Articles

AI Resiliency in an AI-enabled world – protecting your AI investments

Organisations need to be AI resilient to protect and maximise their investments in AI. Here’s a roundup of how Commvault’s new Cloud Unity Platform is transforming enterprise resilience by unifying data security, cyber recovery, and identity protection to help you achieve AI resilience. Learn about key features, real-world benefits, and why this matters for your organisation.

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AI Hallucinations: Why Data Quality Matters More Than Ever

Trust – but verify! AI hallucinations, which occur when AI generates false information confidently as fact, present significant challenges and risks for organizations. A recent case involving Deloitte illustrates the dangers of unchecked AI, highlighting the critical role of data quality and governance in preventing such issues. Striving for accuracy, relevance, and human oversight is essential to develop trust in AI systems.

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Typography-focused featured image for "Data Puddles, Lakes, or Swamps" by Jennifer Stirrup. Designed in the brand's signature Navy, Cream, and Teal palette using Fraunces Bold.

Do You Have Data Puddles, a Data Lake, or a Data Swamp? What This Means for Your AI Initiatives

Effective AI implementation relies on a well-structured data landscape. Organizations face challenges with “data puddles,” which create silos, “data lakes” that provide organized access, and “data swamps,” which hinder AI initiatives. Success requires governance, metadata management, and purposeful data strategies to transform chaos into a competitive advantage, maximising AI’s potential.

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AI for Executives

Six Essential Inquiries Every Board Should Ask Before Approving That Next AI Project

Executive boards must make informed technology investment decisions, especially regarding AI. In this article, Jennifer Stirrup discusses emerging best practices based on industry research. Essential inquiries include strategic alignment, data quality, risk assessment, ethical considerations, long-term impacts, and governance structure. Proactive oversight ensures competitive advantage and stakeholder trust.

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Security as a part of the AI Project Lifecycle

Lifecycle-based AI security needs to be a first-class consideration

Security needs to be a first-class citizen in every AI project. This means integrating security into every phase of the AI development lifecycle rather than relying on post-deployment fixes. It cites statistics indicating significant financial losses from AI security incidents and highlights real-world cases illustrating the risks of neglecting lifecycle security, urging organizations to adopt proactive, secure-by-design principles for responsible AI deployment.

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Orchestrating AI Agents: The Next Enterprise Challenge

Comet, Perplexity AI’s innovative Chrome competitor, enhances web searching by integrating AI assistants for tasks like reserving restaurants. As enterprises evolve, they are transitioning from using isolated AI models to orchestrating specialized agents, which improves efficiency across functions. This shift aims for optimal value from AI investments, resulting in better decision-making and customer experiences.

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