FEATURE
" The traditional boundaries between technology providers are dissolving, yet many organisations still manage relationships with separate connectivity vendors, cloud providers, cybersecurity firms, and AI specialists," he said.
He argued that enterprises increasingly need integrated ecosystems, unified platforms and clearer accountability.
Soliman Ayman, Agentic AI & Enterprise Transformation Leader, MEA at DXC Technology, identified technical debt as another significant obstacle.
Ageing systems, fragmented data and limited interoperability can prevent intelligent agents from operating reliably across enterprise environments.
However, he believes some Middle East organisations have an advantage because they have invested in newer digital infrastructure, potentially reducing the complexity of integrating AI into existing systems.
DXC ' s approach includes centralised enterprise AI platforms that provide reusable environments for developing, testing and governing applications. This reduces the need for individual departments to repeatedly build their own integration, security and governance capabilities.
Amjed similarly advocates shared AI architectures that connect data, applications, identities and business processes while allowing individual functions to innovate.
The objective is to establish common foundations without creating centralised bottlenecks that slow experimentation.
Data readiness becomes the foundation
If enterprise integration is one major challenge, data readiness is another.
AI systems depend on the availability of accurate, relevant and accessible information. Yet many organisations continue to operate fragmented data environments built around individual applications and business functions.
These limitations become particularly visible when AI applications require information from multiple enterprise systems. Buzzalina said data quality and accessibility are essential prerequisites for meaningful AI deployment.
" AI is only as effective as the information it can access and learn from. If data is incomplete, inconsistent, or disconnected across systems, the quality of insights and recommendations will be limited," he said.
The problem is particularly relevant in manufacturing, distribution and supply chain environments, where operational information often resides across multiple platforms.
Without consistent data definitions and visibility, enterprises struggle to establish a reliable foundation for intelligent decision-making.
Pienovi believes the problem is rarely a shortage of information. Instead, enterprises have accumulated cloud, data and AI technologies through separate investments that were never designed to function as a unified environment.
This creates operational fragmentation that becomes increasingly difficult to manage as AI applications expand.
The solution, he argued, involves treating cloud, data and AI as interconnected capabilities supported by common governance and auditable processes.
Amjed also emphasised the importance of making enterprise information more trusted, discoverable and interoperable.
He believes organisations do not necessarily need to centralise all their information in one location. Federated architectures, metadata management, clear ownership, data lineage and policy-based access can provide the foundations for AI deployment across distributed environments.
For generative AI, these capabilities improve the relevance and reliability of responses. For agentic AI, they become essential to determining whether an automated action is appropriate and safe.
Al-Anqari highlighted the growing importance of real-time information, particularly for applications involving edge computing and connected devices.
Salam ' s edge computing architecture enables information to be processed closer to where it is generated, reducing latency and supporting faster decision-making. Combined with IoT and digital capabilities, this can help enterprises translate operational data into actionable insights.
Arturo Buzzalina, Chief Product and Innovation Officer at Epicor
Soliman Ayman, Agentic AI & Enterprise Transformation Leader, MEA at DXC Technology
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