Challenges in Internal Application Development and AI Limitations

This white paper discusses the complexities surrounding internal application development within enterprises and the limitations of generative AI in addressing these challenges. It outlines the common pitfalls that lead to the failure of custom software builds, emphasizing that issues often arise from systemic organizational frictions rather than a lack of technical talent. Key factors contributing to project stalling include scope creep, maintenance challenges, and talent turnover. The paper further explains why AI tools, despite their promise, do not effectively resolve these issues, as they primarily focus on code generation rather than the intricate architecture and integration required for enterprise applications. Additionally, the paper highlights the specific challenges faced in Claims Management Systems, illustrating how AI-generated solutions may fall short in meeting regulatory compliance and operational demands. Ultimately, the document advocates for leveraging established commercial software solutions to mitigate risks associated with internal builds.