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7 signs it’s time to modernize your IT systems

CIO

The bad news, however, is that IT system modernization requires significant financial and time investments. On the other hand, there are also many cases of enterprises hanging onto obsolete systems that have long-since exceeded their original ROI. Kar advises taking a measured approach to system modernization.

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Security is dead: Long live risk management

CIO

Information risk management is no longer a checkpoint at the end of development but must be woven throughout the entire software delivery lifecycle. They demand a reimagining of how we integrate security and compliance into every stage of software delivery. 2025 Banking Regulatory Outlook, Deloitte The stakes are clear.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

As systems scale, conducting thorough AWS Well-Architected Framework Reviews (WAFRs) becomes even more crucial, offering deeper insights and strategic value to help organizations optimize their growing cloud environments. In this post, we explore a generative AI solution leveraging Amazon Bedrock to streamline the WAFR process.

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How Tech Leaders Are Using AI to Solve 10 Procurement Challenges

CIO

And yet, three to six months or more of deliberation to finalize a software purchasing decision. No wonder 90% of IT Executives in North America see software sourcing and vendor selection as a pain point. Read on to gain insights that can help you procure a strategic advantage with AI.

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IT leaders brace for the AI agent management challenge

CIO

Agentic AI systems require more sophisticated monitoring, security, and governance mechanisms due to their autonomous nature and complex decision-making processes. Durvasula also notes that the real-time workloads of agentic AI might also suffer from delays due to cloud network latency. IT employees? Not so much.

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Ground truth generation and review best practices for evaluating generative AI question-answering with FMEval

AWS Machine Learning - AI

Ground truth data in AI refers to data that is known to be factual, representing the expected use case outcome for the system being modeled. By providing an expected outcome to measure against, ground truth data unlocks the ability to deterministically evaluate system quality.

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How to know a business process is ripe for agentic AI

CIO

Does [it] have in place thecompliance review and monitoring structure to initially evaluate the risks of the specific agentic AI; monitor and correct where issues arise; measure success; remain up to date on applicable law and regulation?

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