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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. 54% of AI users expect AI’s biggest benefit will be greater productivity. That pricing won’t be sustainable, particularly as hardware shortages drive up the cost of building infrastructure.

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Rethinking enterprise architects’ roles for agile transformation

CIO Business Intelligence

CIOs often have a love-hate relationship with enterprise architecture. On the one hand, enterprise architects play a key role in selecting platforms, developing technical capabilities, and driving standards.

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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. To benefit from this wider range of RAG services, organizations need to ensure their data is AI-ready. I see this taking shape in 5 key areas.

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How to calculate TCO for enterprise software

CIO Business Intelligence

When organizations buy a shiny new piece of software, attention is typically focused on the benefits: streamlined business processes, improved productivity, automation, better security, faster time-to-market, digital transformation. It can help uncover hidden costs that could come back to bite you down the road.

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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications. However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs.

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Should I Stay or Go? Migrating to AI-Enabled Applications

David Menninger's Analyst Perspectives

However, many enterprises have existing on-premises applications that, in most cases, will not get AI-enablement from the software provider. Those customers should be evaluating if, when and how they will tap into the benefits that AI and GenAI can provide to improve operational and financial performance.

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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.