A recent report by Cloudera  reveals that although nearly 90 per cent of organisations are adopting AI technologies, many face challenges in building the data infrastructure and workforce skills required to maximise AI's potential.

The survey, titled The State of Enterprise AI and Modern Data Architecture, conducted across over 600 IT leaders in regions such as EMEA, the US, and APAC. It also highlights key barriers to AI adoption and explores its current applications in business. Some of the key insights from the report include:

Security and compliance risks: These risks are identified as the top obstacle to AI adoption, with 74 per cent of respondents expressing concern about these issues.

Training and skill gaps: Additionally, 38 per cent of organisations report lacking the necessary training or talent to effectively manage AI tools, while 26 per cent find the technology prohibitively expensive. These findings underscore the fact that while AI is rapidly being integrated into business operations, critical elements like data security and talent development are lagging.

Rising AI expectations: Despite the challenges, the Middle East stands out as a region embracing AI’s potential for growth. According to the report, 61 per cent of Middle Eastern executives expect AI and generative AI (GenAI) to boost productivity by over 10 per cent by 2024. The region’s move from experimental AI projects to large-scale initiatives is being driven by a tech-focused economy that aims to improve both employment and living standards.

Cloudera’s Regional Vice President for the Middle East and Turkey, Karim Azar, emphasised that AI adoption could contribute up to US $150 billion to the GCC’s GDP, underscoring the need for strong data infrastructures to support these advances.

In addition to security and talent gaps, the report also outlines some of the most popular applications of AI. Top use cases include improving customer experiences (60 per cent), enhancing operational efficiency (57 per cent), and streamlining analytics (51 per cent). For example, AI-driven customer service tools, such as chatbots and predictive analytics, are helping companies deliver faster, more intuitive support while improving security and fraud detection.

However, the report stresses that effective AI adoption hinges on having reliable data infrastructure. While 94 peer cent of respondents trust their data, over half express frustration with accessing it due to issues like conflicting data sets and lack of control across platforms. Cloudera’s Chief Strategy Officer, Abhas Ricky, notes that a robust data architecture is crucial for AI success, allowing companies to bring AI models to their data instead of the other way around. Without such an infrastructure, the transformative potential of AI may remain untapped for many organisations.