Demand for Faster App Development

Across both startups and enterprises, application development has slowed sharply, even as expectations for rapid product delivery accelerate. This has created a widening execution gap: ideas increase, but the ability to turn them into production-ready software continues to decline.

Software development cycles are lengthening: Research shows that building a new software application now takes 7–12 months for startups and 12+ months for enterprises, driven by growing tooling and infrastructure complexity. More than 60% of startups fail because they cannot build or iterate fast enough to reach market fit.

Developer time is dominated by non-building work: IDC’s 2025 analysis finds developers spend only 16% of their time creating new product features, with 84% absorbed by CI/CD pipelines, infra setup, debugging, compliance, and security.

Despite the rapid rise of AI adoption, these tools have not reduced this operational burden. 72% of engineering teams report that AI features require more infrastructure, security reviews, and orchestration than traditional development, and 68% say AI components take longer to integrate due to complex model management and data pipelines.

Surveys also show that over 50% of AI initiatives encounter delays because of privacy and governance requirements, further increasing delivery complexity rather than eliminating it.

The result is a systemic velocity crisis: Despite AI spending rising 34% year-over-year, 70%–85% of GenAI and software initiatives still never reach production, primarily due to slow development cycles and operational constraints.

The number of AI models is growing rapidly, but so is the complexity. Small teams spend too much time dealing with API integration, model calls, and context handling, making it hard to focus on building products. Many ideas get stuck before reaching production. NativelyAI automates this backend work, allowing developers to build AI apps in just a few days with full ownership of their data.