AI implementation faces hurdles in corporate in-house development

A survey on corporate AI implementation reveals significant hurdles in transitioning to AI-driven development. While approximately 80% of developers report improvements in developer experience and speed, evaluations regarding quality enhancement and technical sophistication remain relatively low.

Key challenges identified include the inability to quantitatively measure the effects of AI and difficulties in promoting active usage after initial implementation. These issues make it difficult for management to understand Return on Investment (ROI) and hinder the identification of bottlenecks during problem resolution.

Research by TWOSTONE & Sons highlights a critical struggle with in-house AI initiatives, with 91.9% of respondents reporting that their company-led AI projects have experienced stagnation or failure. To overcome these obstacles, experts suggest that organizations must first focus on quantifying and visualizing AI usage and effectiveness to drive successful organizational transformation.