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CIOs weigh where to place AI bets — and how to de-risk them

CIO Business Intelligence

There are a lot of risks and a lot of land mines to navigate,” says the analyst. Coming to grips with risk The first step in making any bet — or investment — is to understand your ability to withstand risk. The opportunity is too big. According to IDC , core IT spending for AI will grow from $235.6 billion in 2024 to $521.0

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Essential skills and traits of chief AI officers

CIO Business Intelligence

Driving business benefits Companies seeking CAIOs are looking to reap myriad benefits from AI adoption, ranging from improved decision-making, to increased efficiency of business processes, higher-quality services, profitability, talent management, customer experience, and innovation.

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How to use foundation models and trusted governance to manage AI workflow risk

IBM Big Data Hub

As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. It encompasses risk management and regulatory compliance and guides how AI is managed within an organization.

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ServiceNow boasts industry-first gen AI general availability with Vancouver release of Now

CIO Business Intelligence

Now Assist for IT Service Management, Customer Service Management, and HR Service Delivery add new text creation and summarization features and an interactive chatbot interface to help workers get to relevant information more quickly. Cost in question The new gen AI features do come at a cost.

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Combine transactional, streaming, and third-party data on Amazon Redshift for financial services

AWS Big Data

The solution should be scalable, cost-efficient, and straightforward to adopt and operate. Amazon Redshift features like streaming ingestion, Amazon Aurora zero-ETL integration , and data sharing with AWS Data Exchange enable near-real-time processing for trade reporting, risk management, and trade optimization.

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Top financial services trends of 2024

IBM Big Data Hub

Since AI has an ability to find trends in data, AI helps insurers create personalized products which could lead to more accurate risk assessments and ease insurance costs for individuals. Mitigation efforts and having the proper risk management tools will be vitally important as threats increase.

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Automating Model Risk Compliance: Model Validation

DataRobot Blog

To start with, SR 11-7 lays out the criticality of model validation in an effective model risk management practice: Model validation is the set of processes and activities intended to verify that models are performing as expected, in line with their design objectives and business uses.

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