Only 28% AI Infra Projects Deliver ROI

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🇬🇧Read original on The Register - AI/ML

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💡Gartner: 28% AI infra success rate—prioritize ITSM for ROI wins

⚡ 30-Second TL;DR

What Changed

Only 28% of AI infrastructure use cases fully pay off with ROI.

Why It Matters

Low success rate underscores need for strategic selection of AI infra projects, prioritizing high-ROI areas like ITSM to avoid wasted investments.

What To Do Next

Assess current AI infra projects for ITSM alignment to maximize ROI potential.

Who should care:Enterprise & Security Teams

🧠 Deep Insight

AI-generated analysis for this event.

🔑 Enhanced Key Takeaways

•The high failure rate is largely attributed to 'technical debt' and the complexity of integrating AI models into legacy IT infrastructure, which often requires significant data pipeline re-engineering.
•Gartner's analysis highlights that organizations focusing on 'AI-augmented IT operations' (AIOps) see higher success rates because these projects leverage existing structured data sets rather than attempting to build new infrastructure from scratch.
•A significant portion of the 72% of projects failing to deliver ROI are stalled by 'pilot purgatory,' where proof-of-concepts fail to scale due to prohibitive inference costs and lack of clear business-value alignment.

🔮 Future ImplicationsAI analysis grounded in cited sources

IT budgets will shift from 'AI experimentation' to 'AI consolidation'.

Organizations will prioritize funding for proven AIOps and ITSM use cases over speculative infrastructure projects to satisfy shareholder demands for tangible ROI.

Vendor lock-in will become a primary risk factor for AI infrastructure failure.

The complexity of proprietary AI stacks makes it difficult for enterprises to pivot or optimize costs, leading to long-term financial drag on projects that fail to meet performance benchmarks.

🇬🇧Read original article on The Register - AI/ML

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