Worldwide Low-Code, No-Code, and Intelligent Developer Technologies Forecast, 2024–2028
This IDC study provides a worldwide forecast for 2023–2028 for the LCNCIDT market. It provides the market size of the worldwide LCNCIDT market in 2023 and a five-year forecast through 2028 by geographic region and deployment type. This document updates the market forecast included in Worldwide Low-Code, No-Code, and Intelligent Developer Technologies Forecast, 2023–2027 (IDC #US50224723, August 2023).“IDC forecasts exceptional growth for the low-code, no-code, and intelligent developer technologies market for 2023–2028, with a CAGR of 37.6%,” said Arnal Dayaratna, research vice president, Software Development at IDC. “The growth of this market will be primarily driven by intelligent developer technologies, which have a CAGR of 47.3% over the forecast time period, while low-code and no-code developer technologies have a corresponding CAGR of 13.9%. That said, IDC expects that growth of the low-code and no-code developer technologies landscape will accelerate further in forthcoming years given that these technologies are pivoting to deepen their support for the development of intelligent applications.”
IDC Market Forecast Figure
Executive Summary
Advice for Technology Suppliers
Provide Developers with Technologies That Facilitate Model Selection for Large Language Models
Enhance Developer Experience in AI Coding Assistant Technologies
Invest in Agentic Builder Technologies to Complement AI Coding Assistants
Recognize the Role of Low Code in Accelerating AI and Generative AI Development
Support the Development of Integrated Development Stacks for AI and Generative AI Development
Market Forecast
Market Context
Drivers and Inhibitors
Drivers
Productization of Model Transformation Technologies Such as RAG and Fine-Tuning
Advancements in Model Quantization, Model Pruning, and Model Distillation
Proliferation of Open and Open Source Large Language Models
Proliferation of Specialized Coding Assistants
Inhibitors
The Variability of Generative AI Across Different Contexts and Tasks
Significant Market Developments
Mastering RAG Becomes Essential for Developers as Generative AI Matures
Low-Code and No-Code Standardize the Generative AI Development Stack
AI Agents Catalyze Innovation in Generative AI Development
Low-Code, No-Code, and Command-Line Platforms Converge
Changes from Prior Forecast
Market Definition
Methodology
Functional Versus Competitive Markets
Historical and Forecast Market Values and Exchange Rates
Related Research
Research Assistance
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