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The numbers tell the story. According to Forrester, only 10 – 15 % of AI pilots successfully transition to long-term production. McKinsey reports that while AI adoption is now widespread, only around one-third of organisations have begun scaling AI across the enterprise. In other words, businesses are proving that AI works, but they are struggling to make it work at scale.

The challenge is rarely the AI model itself.

Jeevan Thankappan Managing Editor

Instead, CIOs are discovering that legacy infrastructure, fragmented data, disconnected applications and operational complexity are becoming the biggest barriers to enterprise AI. Many businesses have accumulated years of technical debt, making it difficult to integrate AI into existing workflows or provide models with the trusted, high-quality data they require. AI may be intelligent, but without modern digital foundations, it cannot deliver meaningful business outcomes.

This is happening at a time when expectations have never been higher. An IBM study projects that AI spending will increase from just under 15 % of IT budgets in 2025 to almost 25 % by 2027, representing a 71 % increase in just two years. Boards are no longer asking whether organisations should invest in AI. They are asking what business value those investments are delivering.

The first wave of enterprise AI focused largely on low-hanging fruits. Customer service chatbots, content generation and productivity assistants provided quick wins and demonstrated the technology’ s potential. But the next phase is far more demanding. Organisations must embed AI into core business processes, supply chains, finance, cybersecurity and operations if they are to generate transformational value.

This shift places enormous pressure on CIOs and CTOs. They are increasingly caught between rapidly evolving AI capabilities and the realities of enterprise technology environments. The gap between what AI can achieve and what organisations can actually deploy remains significant. At the same time, the rise of Shadow AI, in which employees adopt unsanctioned AI tools outside IT governance, is creating new risks to security, compliance and data protection.

The winners in the AI era will not necessarily be those with the most advanced models. They will be the organisations that modernise their infrastructure, build robust data pipelines and integrate AI seamlessly into business workflows. The next chapter of enterprise AI is no longer about proving the technology. It is about building the foundation that allows it to scale www. intelligentcio. com

INTELLIGENT CIO MIDDLE EAST

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