Remove Experimentation Remove Optimization Remove Risk
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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.

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The key to operational AI: Modern data architecture

CIO Business Intelligence

While in the experimentation phase, speed is a priority, the implementation phase requires more attention to resiliency, availability, and compatibility with other tools. As a result, ​developers — regardless of their expertise in machine learning — will be able to develop and optimize business-ready large language models (LLMs).

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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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Where CIOs should place their 2025 AI bets

CIO Business Intelligence

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. CIOs should consider placing these five AI bets in 2025.

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Escaping POC Purgatory: Evaluation-Driven Development for AI Systems

O'Reilly on Data

The coordination tax: LLM outputs are often evaluated by nontechnical stakeholders (legal, brand, support) not just for functionality, but for tone, appropriateness, and risk. ML apps needed to be developed through cycles of experimentation (as were no longer able to reason about how theyll behave based on software specs).

Testing 174
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From project to product: Architecting the future of enterprise technology

CIO Business Intelligence

Just as state urban development offices monitor the health of different cities and provide targeted guidance based on each citys unique challenges, our portfolio health dashboard offers a comprehensive view that helps guide different business units toward optimal outcomes. Shawn McCarthy 3.

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AI agents will transform business processes — and magnify risks

CIO Business Intelligence

Adding smarter AI also adds risk, of course. “At The big risk is you take the humans out of the loop when you let these into the wild.” When it comes to security, though, agentic AI is a double-edged sword with too many risks to count, he says. “We That means the projects are evaluated for the amount of risk they involve.

Risk 136