The integration of artificial intelligence (AI) with legacy software often leads to compatibility issues and performance slowdowns, as businesses struggle to adapt aged systems for modern AI demands. While AI adoption surged to 72% in 2024, many companies are not seeing a return on investment. The solution lies in developing AI-native software, which incorporates AI and machine learning from the ground up, enabling applications to improve and adapt continuously. This shift requires a new DevOps approach that supports these evolving AI technologies and methodologies, moving away from the static nature of traditional systems.
Integrating AI onto legacy software presents significant challenges, such as compatibility issues and performance slowdowns, hindering expected AI functionalities despite rising adoption rates.
AI-native software integrates AI and machine learning at its core, allowing systems to evolve and adapt, a stark contrast to older, static applications.
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