AI 우선 개발 설명 : 최신 소프트웨어 개발의 새로운 패러다임을 뒷받침하는 핵심 개념

This IDC Market Perspective discusses the significance of AI-first development. This paradigm embeds intelligence into applications through machine learning frameworks, natural language processing (NLP), predictive analytics, and foundation models, allowing developers to deliver and modify intelligent capabilities effectively. By breaking down applications into smaller, independent services, known as microservices, AI-first development promotes modularity and scalability, facilitating easier AI integration. It emphasizes data-centric insights, enabling developers to manage training data for machine learning models and valuing both structured and unstructured data sets. In addition, it leverages DevOps, MLOps, and other tools to automate technology updates, ensuring applications can quickly adapt to environmental changes. Continuous learning is another critical aspect, allowing applications to evolve by learning from new data, user feedback, and real-world interactions, thereby improving performance over time. "AI-first development is a transformative paradigm that integrates intelligence as a core attribute of applications from the outset, ensuring they are smart, adaptable, and scalable," notes Arnal Dayaratna, research vice president, Software Development at IDC.

Executive Snapshot

New Market Developments and Dynamics

• Definition
  • Embedded Intelligence
  • Microservices
  • Data Centricity
  • Automation
  • Continuous Learning

IDC's Point of View

• The Evolution from 12-Factor and Cloud-Native Methodologies to AI-First Development
  • The 12-Factor Methodology: Modular and Adaptable Design
    • Cloud-Native Development: Building the Foundation
• Conclusion

Learn More

• Related Research
• Synopsis