Remove Marketing Remove Risk Remove Testing
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Risk Management for AI Chatbots

O'Reilly on Data

Welcome to your company’s new AI risk management nightmare. Before you give up on your dreams of releasing an AI chatbot, remember: no risk, no reward. The core idea of risk management is that you don’t win by saying “no” to everything. Why not take the extra time to test for problems?

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How resilient CIOs future-proof to mitigate risks

CIO Business Intelligence

This year saw emerging risks posed by AI , disastrous outages like the CrowdStrike incident , and surmounting software supply chain frailties , as well as the risk of cyberattacks and quantum computing breaking todays most advanced encryption algorithms. To respond, CIOs are doubling down on organizational resilience.

Risk 106
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The Race For Data Quality in a Medallion Architecture

DataKitchen

When data from various sources does not reach the Bronze layer on time, it can lead to stale insights and missed opportunities in the Gold layer, especially for time-sensitive applications like inventory tracking or marketing campaigns. Data Drift Checks (does it make sense): Is there a shift in the overall data quality?

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Product Management for AI

O'Reilly on Data

These articles show you how to minimize your risk at every stage of the project, from initial planning through to post-deployment monitoring and testing. What you need to know about product management for AI Practical Skills for the AI Product Manager Bringing an AI Product to Market. That’s true at every stage of the process.

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Put Your Data to Work: The Complete Playbook

They rely on data to power products, business insights, and marketing strategy. From search engines to navigation systems, data is used to fuel products, manage risk, inform business strategy, create competitive analysis reports, provide direct marketing services, and much more.

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Accelerating AI for financial services: Innovation at scale with NVIDIA and Microsoft

CIO Business Intelligence

Financial institutions have an unprecedented opportunity to leverage AI/GenAI to expand services, drive massive productivity gains, mitigate risks, and reduce costs. GenAI is also helping to improve risk assessment via predictive analytics.

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88% of AI pilots fail to reach production — but that’s not all on IT

CIO Business Intelligence

The proof of concept (POC) has become a key facet of CIOs AI strategies, providing a low-stakes way to test AI use cases without full commitment. Companies pilot-to-production rates can vary based on how each enterprise calculates ROI especially if they have differing risk appetites around AI. Its going to vary dramatically.

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