Why AI Adoption Is Slower Than You Think and How to Fix It

AI adoption in enterprise software faces significant friction due to governance, risk management, and legacy technical debt, often slowing progress despite the technology's transformative potential. Jason Jackson, Group AI Enablement Lead at Vesta Software Group, advocates for a scientific approach to experimentation that prioritizes business problems over technology while maintaining vendor and model agnosticism to navigate rapidly shifting capabilities. This evolution in software development integrates AI-driven workflows and prompt engineering, fundamentally redefining the developer's role. As AI permeates the software stack, incumbent SaaS providers must transition from human-first designs to AI-first architectures to remain competitive. Protecting core logic and systems of record while enabling flexible, AI-integrated user interfaces remains the critical path for businesses to maintain value and relevance in an increasingly automated landscape.