Remove Experimentation Remove IT Remove Risk
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IDC chief research officer: GenAI, from experimentation to adoption

CIO Business Intelligence

Its been a year of intense experimentation. Now, the big question is: What will it take to move from experimentation to adoption? We expect some organizations will make the AI pivot in 2025 out of the experimentation phase. This approach requires a partnership between business and IT.

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9 IT resolutions for 2025

CIO Business Intelligence

One of them is Katherine Wetmur, CIO for cyber, data, risk, and resilience at Morgan Stanley. Wetmur says Morgan Stanley has been using modern data science, AI, and machine learning for years to analyze data and activity, pinpoint risks, and initiate mitigation, noting that teams at the firm have earned patents in this space.

IT 140
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88% of AI pilots fail to reach production — but that’s not all on IT

CIO Business Intelligence

Half of the organizations have adopted Al, but most are still in the early stages of implementation or experimentation, testing the technologies on a small scale or in specific use-cases, as they work to overcome challenges of unclear ROI, insufficient Al-ready data and a lack of in-house Al expertise. Its going to vary dramatically.

ROI 127
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It’s 2025. Are your data strategies strong enough to de-risk AI adoption?

CIO Business Intelligence

If 2023 was the year of AI discovery and 2024 was that of AI experimentation, then 2025 will be the year that organisations seek to maximise AI-driven efficiencies and leverage AI for competitive advantage. Lack of oversight establishes a different kind of risk, with shadow IT posing significant security threats to organisations.

Risk 111
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What Are ChatGPT and Its Friends?

O'Reilly on Data

What is it, how does it work, what can it do, and what are the risks of using it? ChatGPT, or something built on ChatGPT, or something that’s like ChatGPT, has been in the news almost constantly since ChatGPT was opened to the public in November 2022. A quick scan of the web will show you lots of things that ChatGPT can do. It’s much more.

IT 346
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Bringing an AI Product to Market

O'Reilly on Data

Without clarity in metrics, it’s impossible to do meaningful experimentation. If you’re an AI product manager (or about to become one), that’s what you’re signing up for. Identifying the problem. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about.

Marketing 364
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Practical Skills for The AI Product Manager

O'Reilly on Data

AI PMs should enter feature development and experimentation phases only after deciding what problem they want to solve as precisely as possible, and placing the problem into one of these categories. Experimentation: It’s just not possible to create a product by building, evaluating, and deploying a single model.