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Beyond “Prompt and Pray”

O'Reilly on Data

TL;DR: Enterprise AI teams are discovering that purely agentic approaches (dynamically chaining LLM calls) dont deliver the reliability needed for production systems. A shift toward structured automation, which separates conversational ability from business logic execution, is needed for enterprise-grade reliability.

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CIOs face mounting pressure as AI costs and complexities threaten enterprise value

CIO Business Intelligence

CIOs are under increasing pressure to deliver meaningful returns from generative AI initiatives, yet spiraling costs and complex governance challenges are undermining their efforts, according to Gartner. hours per week by integrating generative AI into their workflows, these benefits are not felt equally across the workforce.

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Unlocking the full potential of enterprise AI

CIO Business Intelligence

Research from Gartner, for example, shows that approximately 30% of generative AI (GenAI) will not make it past the proof-of-concept phase by the end of 2025, due to factors including poor data quality, inadequate risk controls, and escalating costs. [1] Reliability and security is paramount.

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What to expect from AI in the enterprise in 2025

CIO Business Intelligence

This is particularly true with enterprise deployments as the capabilities of existing models, coupled with the complexities of many business workflows, led to slower progress than many expected. Focus on data assets Building on the previous point, a companys data assets as well as its employees will become increasingly valuable in 2025.

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The key to operational AI: Modern data architecture

CIO Business Intelligence

From customer service chatbots to marketing teams analyzing call center data, the majority of enterprises—about 90% according to recent data —have begun exploring AI. For companies investing in data science, realizing the return on these investments requires embedding AI deeply into business processes.

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Generative AI in the Enterprise

O'Reilly on Data

In enterprises, we’ve seen everything from wholesale adoption to policies that severely restrict or even forbid the use of generative AI. AI users say that AI programming (66%) and data analysis (59%) are the most needed skills. 54% of AI users expect AI’s biggest benefit will be greater productivity. What’s the reality?

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Where CIOs should place their 2025 AI bets

CIO Business Intelligence

We may look back at 2024 as the year when LLMs became mainstream, every enterprise SaaS added copilot or virtual assistant capabilities, and many organizations got their first taste of agentic AI. CIOs were given significant budgets to improve productivity, cost savings, and competitive advantages with gen AI.