Artificial intelligence (AI) has significantly advanced in recent years, driving intelligent automation across various industries. However, traditional AI development often demands specialized coding expertise, prolonged development cycles, and high costs, limiting its accessibility and widespread adoption. The emergence of low-code and no-code (LCNC) platforms is revolutionizing AI decisioning by enabling non-technical users and citizen developers to create and deploy AI-driven applications with minimal programming knowledge. These platforms offer intuitive drag-and-drop interfaces, pre-built AI models, automated workflows, and seamless integrations with existing enterprise systems, thereby accelerating AI deployment, reducing costs, and democratizing AI capabilities across different sectors.
This study explores how LCNC platforms enhance AI decision-making processes by simplifying model development, improving operational agility, and fostering rapid innovation. By comparing traditional AI development approaches with LCNC-based AI solutions, this paper highlights key efficiency gains, cost reductions, and performance enhancements. Through a comprehensive industry analysis, we examine the role of LCNC platforms in healthcare, finance, retail, supply chain, and manufacturing, demonstrating their impact on workflow automation, decision intelligence, and predictive analytics.
Furthermore, this paper investigates the challenges and limitations associated with LCNC AI, including customization constraints, security concerns, and scalability limitations, while also discussing emerging trends such as AutoML, Edge AI integration, and advanced security mechanisms to mitigate these challenges. The findings suggest that as LCNC platforms continue to evolve, they will play an increasingly critical role in AI-driven business transformation, bridging the gap between AI capabilities and enterprise automation needs.
Ultimately, this research underscores that low-code and no-code AI platforms are not just simplifying AI development but are also reshaping the future of intelligent automation, enabling businesses to optimize processes, enhance decision-making, and gain a competitive edge in the digital economy.
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