Accelerating Time to Market through Agile in AI Innovation - Susy Alestriani Sibagariang; Farisha Andi Baso; Nugroho Prihantoni; Noah Rangi (Pandawan Sejahtera Indonesia, 2026)
Rapid digital transformation, driven by the increasing integration of Artificial Intelligence (AI) into digital products and services, has intensified competition across industries and positioned Time-to-Market (TTM) as a critical success factor for digital innovation projects. AI-oriented development requires rapid iteration, continuous data processing, and frequent model refinement, which are often difficult to support using traditional project management approaches, leading to delayed deployment and reduced adaptability. In this context, agile methodologies have emerged as a flexible and adaptive framework that aligns well with the iterative and data-driven nature of AI development. This study examines the impact of agile adoption on TTM performance in digital innovation projects, particularly those involving AI-enabled components, using a qualitative multiple-case study design based on semi-structured interviews with product managers, developers, and agile practitioners, complemented by analysis of project documentation, AI workflows, and delivery metrics. The findings show that organizations adopting agile methodologies achieve a development cycle time reduction of approximately 25% to 40% within the first two years of implementation, supported by key practices such as iterative sprint development, cross-functional collaboration between engineering and data teams, continuous feedback loops, and early testing of AI components. Overall, the study confirms that agile methodologies serve as an effective strategic mechanism for accelerating TTM in AI-driven digital innovation projects.