ModelOp, a leader in AI lifecycle automation and governance software, has unveiled its 2025 AI Governance Benchmark Report, titled “AI’s Time-to-Market Quagmire: Why Enterprises Struggle to Scale AI Innovation.” The report gathers insights from 100 senior AI and data leaders across multiple sectors, including Financial Services, Healthcare, Life Sciences, Pharma, Biotech, Manufacturing, and more. It sheds light on the operational challenges enterprises face in scaling AI, particularly generative AI, and highlights a growing disconnect between AI ambitions and actual production results.
Findings and Pointers:
- Time-to-Market Delays in Generative AI:
- 56% of generative AI projects take 6–18 months to move from intake to production.
- Despite 80% of enterprises having over 51 generative AI use cases in the proposal phase, many struggle to get even a few into production.
- AI Use Case Development and Quality Assurance:
- While 72% of enterprises have fewer than 20 AI use cases in production, many enterprises have 21 or more use cases either in development or quality assurance, signaling a wave of initiatives in progress.
- Fragmented Systems Challenge AI Governance:
- 58% of enterprises identify fragmented systems as a significant challenge to AI governance adoption, hindering consistent policies across teams and systems.
- Inconsistent Reporting and Duplicate Work:
- 86% of enterprises face risks like inconsistent reporting and duplicate work due to a lack of AI assurance at the enterprise level.
- Increased AI Governance Spending:
- 36% of organizations have budgeted $1M or more annually for AI governance software, showing a trend toward investing in robust AI governance.
- Return on Investment and Early Governance Adoption:
- Early adoption of AI governance correlates with faster deployment and stronger ROI. One case study demonstrated a 50% reduction in time-to-market and 80% reduction in issue resolution time after adopting ModelOp’s software.
The 2025 AI Governance Benchmark Report from ModelOp highlights critical challenges in scaling AI initiatives, particularly in generative AI. Enterprises are realizing that effective AI governance is not just a bureaucratic hurdle, but a strategic advantage that accelerates innovation. Implementing AI lifecycle automation early on can help companies streamline their processes, reduce time-to-market, and improve overall AI adoption. The report serves as a call to action for C-suite executives to prioritize AI governance as a fundamental part of their AI strategy.
