Development of Applications with Artificial Intelligence: Expert Perspectives and Recommendations - Julien Florkin (Lembaga Komunitas Informasi Teknologi Aceh (KITA), 2025)
Artificial intelligence (AI) applications are accelerating significantly, supported by three pillars: core technologies, cost efficiency, and strategic direction. A comparative analysis reveals critical contributions from three technologies: (1) Machine Learning (ML) enhances user engagement by 35% through personalized recommendation systems on e-commerce platforms; (2) Natural Language Processing (NLP) reduces customer service operational costs by 47% via intelligent chatbots in the banking sector; and (3) predictive analytics improves cardiovascular disease diagnosis accuracy by 27% based on multicenter clinical data. Estimated AI application development costs range from 50,000 to 250,000, depending on algorithm complexity and computational infrastructure requirements. Future AI development will be shaped by two trends: (1) Edge AI, which reduces data processing latency by 60% through local computation, and (2) Explainable AI (XAI), which enhances algorithm transparency to comply with GDPR and ISO/IEC 23894 regulations. The study underscores that successful AI implementation requires multidisciplinary integration among data scientists, software engineers, and business stakeholders. Strategic recommendations include allocating 15–20% of R&D budgets for continuous learning, establishing an AI ethics committee aligned with OECD principles, and adopting an agile development model for market responsiveness