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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. Build up: Databases that have grown in size, complexity, and usage build up the need to rearchitect the model and architecture to support that growth over time.

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Where CIOs should place their 2025 AI bets

CIO Business Intelligence

Build toward intelligent document management Most enterprises have document management systems to extract information from PDFs, word processing files, and scanned paper documents, where document structure and the required information arent complex.

CTO Hire 356
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Kyndryl extends Google Cloud partnership for AI-based mainframe modernization

Network World

With the new service, the idea is to offer customers generative AI-driven code analysis and documentation of mainframe applications. However, genAI has enhanced reengineering and rewriting processes with rich documentation and extended testing while reducing the time required to complete modernizations, ISG stated.

Google 447
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Reimagine application modernisation with the power of generative AI

CIO Business Intelligence

GenAI can also harness vast datasets, insights, and documentation to provide guidance during the migration process. Alignment: Is the solution customisable for -specific architectures, and therefore able to unlock additional, unique efficiency, accuracy, and scalability improvements?

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Rethinking enterprise architects’ roles for agile transformation

CIO Business Intelligence

CIOs often have a love-hate relationship with enterprise architecture. In the State of Enterprise Architecture 2023 , only 26% of respondents fully agreed that their enterprise architecture practice delivered strategic benefits, including improved agility, innovation opportunities, improved customer experiences, and faster time to market.

Agile 363
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The future of data: A 5-pillar approach to modern data management

CIO Business Intelligence

Not my original quote, but a cardinal sin of cloud-native data architecture is copying data from one location to another. Every SQL query, script and data movement configuration must be treated as code, adhering to modern software development methodologies and following DevOps and SRE best practices.

Data 278
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IT infrastructure: Inventory before AIOps

CIO Business Intelligence

To be able to develop future topics such as AI and observability at all, they first need modern architectures and data management platforms. In addition, there is often a lack of clear documentation and a deep understanding of the existing architecture. Only in this way can companies manage the enormous amounts of data at all.