Remove Cost-Benefit Remove Experimentation Remove Risk Management
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Where CIOs should place their 2025 AI bets

CIO Business Intelligence

CIOs were given significant budgets to improve productivity, cost savings, and competitive advantages with gen AI. CIOs feeling the pressure will likely seek more pragmatic AI applications, platform simplifications, and risk management practices that have short-term benefits while becoming force multipliers to longer-term financial returns.

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What Is Model Risk Management and How is it Supported by Enterprise MLOps?

Domino Data Lab

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.

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5 Tips to Stay Competitive as AI Technology Evolves

Smart Data Collective

AI technology moves innovation forward by boosting tinkering and experimentation, accelerating the innovation process. One of the biggest benefits of AI is that it has led to new breakthroughs in automation. Big data also helps you identify potential business risks and offers effective risk management solutions.

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5 best practices to successfully implement gen AI

CIO Business Intelligence

So, to maximize the ROI of gen AI efforts and investments, it’s important to move from ad-hoc experimentation to a more purposeful strategy and systematic approach to implementation. Here are five best practices to get the most business benefit from gen AI. In this regard, gen AI is no different from other technologies.

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AI on the mainframe? IBM may be onto something

CIO Business Intelligence

It’s a natural fit and will be interesting to see how these ensemble AI models work and what use cases will go from experimentation to production,” says Dyer. A combination of mainframe and cloud for different tasks might be a more flexible, cost-effective solution.”

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Generative AI copilots: What’s hype and where to drive results

CIO Business Intelligence

Many other platforms, such as Coveo’s Relative Generative Answering , Quickbase AI , and LaunchDarkly’s Product Experimentation , have embedded virtual assistant capabilities but don’t brand them copilots. Microsoft is heavily investing in AI capabilities and workflow integrations, so CIOs should expect and plan for improved capabilities.

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3 key digital transformation priorities for 2024

CIO Business Intelligence

Meanwhile, CIOs must still reduce technical debt, modernize applications, and get cloud costs under control. If CIOs don’t improve conversions from pilot to production, they may find their investors losing patience in the process and culture of experimentation.