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What CIOs can do: Avoid and reduce data debt by incorporating data governance and analytics responsibilities in agile data teams , implementing data observability , and developing data quality metrics. AI debt that will require significant rework Gen AI tools and capabilities are introducing new sources of technical debt.
In a report released in early January, Accenture predicts that AI agents will replace people as the primary users of most enterprisesystems by 2030. Still, enterprises are already reporting success deploying AI agents for several use cases. The top use case for AI agents was software development, cited by 87% of respondents.
If last years Huawei Industrial Digital and Intelligent Transformation Summit was about exploring the opportunities and challenges of industrial intelligent transformation, the 2025 edition was about how rapid AI development has changed the landscape. Lastly, open-source AI models are simply becoming more competitive.
Embedded AI Embedding AI into enterprisesystems that employees were already using was a trend before gen AI came along. And as it gets cheaper and easier to customize AIs, more companies will begin doing it for smaller use cases, says Greenstein, making it truly pervasive in the enterprise.
Generative AI can help businesses achieve faster development in two main areas: low/no-code application development and mainframe modernisation. Developers can create and modify applications independently, reducing the burden on IT teams to focus on more strategic and complex tasks.
It’s no exaggeration to say that modern enterprises run on DevOps. Rapidly moving markets and constantly changing business conditions require development teams to work closely with operations and end-users in a flexible, agile manner. Continuous improvement and continuous development (CI/CD) cycles are the DevOps way of life.
Since those early inhouse iterations, BPM systems have evolved into excellent full-fleged platforms for tracking and fine-tuning everything that happens inside an organization, complete with a wide variety of interfaces for working with other standard enterprisesystems such as accounting software or assembly line management systems.
If you reflect for a moment, the last major technology inflection points were probably things like mobility, IoT, development operations and the cloud to name but a few. Open-source implementations for machine learning invite obvious and hidden costs if your organization is not prepared to manage them.
Other typical components required for an enterprisesystem are access control (so that each user only sees what they are entitled to) and security. We are beginning to see commercial products for LLM Orchestration, as well as commonly used open-source frameworks such as LangChain and LlamaIndex.
As 5G and B2B services for vertical industries start to take deeper root, Nokia and Telenor are among the companies launching new initiatives to protect enterprisesystems from emerging security threats. called Omny, which is setting out to “develop software that helps secure industrial operators and critical infrastructure.”
Nvidia has introduced a new set of opensource Llama Nemotron reasoning models during its GTC event, aimed at enhancing agentic AI workloads. Nvidia’s market position faced challenges earlier this year with the introduction of DeepSeek R1, which promised an opensource reasoning model with superior performance.
Developers Can Create, Deploy and Publish Apps in the Cloud for Free. “Cloudcuity AppDeployer is a game changer for the software development industry,” said Kevin L. ” A key component of AppDeployer empowers developers with point-and-click tools to rapidly prototype and deploy applications without programming. .”
With tightening budgets, IT departments are looking for more affordable, high powered enterprisesystems and ERP software solutions such as the web based ERP applications.
The six founders of Flexagon worked for years in the trenches of enterprise software platforms. We have a combined 100+ years of experience dealing with the complexity of enterprise software development and operations across infrastructure, database, middleware, and applications. source control tools such as Git and SVN .
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