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7 types of tech debt that could cripple your business

CIO Business Intelligence

Accenture reports that the top three sources of technical debt are enterprise applications, AI, and enterprise architecture. These areas are considerable issues, but what about data, security, culture, and addressing areas where past shortcuts are fast becoming todays liabilities?

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What gives IT leaders pause as they look to integrate agentic AI with legacy infrastructure

CIO Business Intelligence

We actually started our AI journey using agents almost right out of the gate, says Gary Kotovets, chief data and analytics officer at Dun & Bradstreet. In addition, because they require access to multiple data sources, there are data integration hurdles and added complexities of ensuring security and compliance.

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CIOs are rethinking how they use public cloud services. Here’s why.

CIO Business Intelligence

The reasons include higher than expected costs, but also performance and latency issues; security, data privacy, and compliance concerns; and regional digital sovereignty regulations that affect where data can be located, transported, and processed. So we carefully manage our data lifecycle to minimize transfers between clouds.

Cloud 349
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The 5 S’s of cyber resilience: How to rethink enterprise data security and management

CIO Business Intelligence

The patchwork nature of traditional data management solutions makes testing response and recovery plans cumbersome and complex. To address these challenges, organizations need to implement a unified data security and management system that delivers consistent backup and recovery performance.

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5 top business use cases for AI agents

CIO Business Intelligence

There are also pure-play agentic AI platform providers such as CrewAI and intelligent automation providers like UiPath. In a report released in early January, Accenture predicts that AI agents will replace people as the primary users of most enterprise systems by 2030. And the data is also used for sales and marketing.

CTO Hire 359
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Have we reached the end of ‘too expensive’ for enterprise software?

CIO Business Intelligence

These required specialized roles and teams to collect domain-specific data, prepare features, label data, retrain and manage the entire lifecycle of a model. Companies can enrich these versatile tools with their own data using the RAG (retrieval-augmented generation) architecture. An LLM can do that too.

Software 321
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Redefining enterprise transformation in the age of intelligent ecosystems

CIO Business Intelligence

What we consistently overlooked were the direct and indirect consequences of disruption to business continuity, the challenges of acquisitions and divestitures, the demands of integration and interoperability for large enterprises and, most of all, the unimpressive track record for most enterprise transformation efforts.