CHICAGO, March 11, 2026 (GLOBE NEWSWIRE) — ModelOp, the leading AI lifecycle management and governance platform for enterprises, announced today the findings of its 2026 AI Governance Benchmark Report: The AI Portfolio Explosion — When Activity Creates the Illusion of AI Value. Based on a global survey of 100 senior AI leaders, the report reveals a dramatic increase in the number of enterprise AI use cases and decrease in delivery timelines. However, this increased activity is not translating into scalable AI value, which indicates a widening gap between AI ambition and delivery at enterprise-scale.
This rapid expansion of AI portfolios is fueled by a surge in GenAI, Agentic, and third-party vendor tools. The data shows that development timelines are compressing, and many organizations now report moving new AI initiatives into production in a matter of months rather than years.
This raises a paramount question for AI leadership: What measurable value is AI delivering once it’s live in production?
“Enterprises are piloting AI use cases faster than ever,” said Dave Trier, CEO of ModelOp. “But the reality is there is a massive disparity between ‘AI activity’ and transformational business value. Business units may hit a few singles when leadership is looking for a homerun on their AI investments. They struggle to turn AI experimentation into trusted, operational systems at enterprise-scale.”
The report finds that AI portfolios are expanding at an unprecedented rate: 67% of enterprises now report 101–250 proposed AI use cases — up sharply year over year — but 94% report fewer than 25 in production.
Activity Does Not Equal Value
The research highlights what ModelOp defines as an emerging “AI value illusion.” As deployment speed increases and portfolios expand, visibility and accountability often lag.
Key findings include:
- More than two-thirds of organizations rely on manual or projected ROI tracking, even for production AI systems.
- Most enterprises connect agentic AI systems to 6–20 external tools and services, expanding third-party risk and cost exposure.
- Use of commercial AI lifecycle management and governance platforms surged from 14% in 2025 to nearly 50% of respondents in 2026, signaling growing recognition that automation and embedded governance are required to keep pace with AI velocity.
“When dozens of teams build AI independently—each with different tools, processes, and controls—organizations end up with fragmented portfolios that make it difficult to monitor, trust, and show return on AI investments,” Trier continued.
Industrializing AI Delivery
The report concludes that enterprise AI has entered a new phase. Rapid experimentation, once considered the defining competitive advantage, is no longer sufficient. Organizations that succeed are shifting from decentralized experimentation to industrialized AI delivery, embedding governance directly into workflows and operating AI as a managed portfolio.
“Last year, the question was, ‘How fast can we deploy AI?’” Trier added. “This year, the questions are, ‘Which AI investments are delivering value? How do we move fast enough to sustain a competitive advantage? And how do we scale our AI delivery processes to maximize the value?’ The next phase of enterprise AI will be defined by who can deliver AI at industrial scale—rapidly, reliably, responsibly… and profitably.”
The full 2026 AI Governance Benchmark Report: The AI Portfolio Explosion is available at: https://na2.hubs.ly/H03pYJ30
About ModelOp
ModelOp is the leading AI lifecycle management and governance platform, purpose-built for enterprises. ModelOp’s platform provides a centralized AI system of record, automation from intake to retirement, and enforceable policies—helping enterprises bring ML, GenAI, Agentic AI, and vendor AI solutions into production 10X faster. ModelOp is used by the most complex and regulated institutions in the world—including major banks, insurers, regulatory bodies, healthcare organizations, pharmaceutical firms, and global CPG companies. Follow ModelOp on LinkedIn.
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