娇色导航

Artificial Intelligence (AI) is revolutionising the way enterprises innovate products, address customer needs, and boost productivity. This transformation is enhancing their competitiveness not only on a global scale but also specifically in the Middle East, Türkiye, and Africa (META) region. In 2025, 40% of the core IT budget among the world’s 2,000 largest firms is expected to be spent on AI initiatives, driving a double-digit rise in product and process innovation rates.

The META commitment to AI

However, to fully harness the potential of AI and achieve scalable value realisation, enterprises must build robust foundational capabilities while systematically navigating the risks and complexities of organisation-wide AI implementation.

Encouragingly, approximately 60% of organisations in the META region have already prioritised AI investments as a means of transforming their businesses (IDC EMEA Digital Executive Sentiment Survey 2024). Additionally, more than 80% of the organisations have been either investing in Generative AI (GenAI), doing proof of concepts, or exploring potential GenAI use cases (Source: IDC Data and AI Survey, 2024).

This promising trend is propelled by key factors such as enhancing and expanding customer experiences, accelerating the introduction of digital products and services, and driving research and development for faster product design and innovation.

The framework for becoming AI-ready

Nevertheless, understanding and addressing AI-related challenges are pivotal for success, especially as GenAI is increasingly infused into various business processes and applications. These challenges encompass a range of issues, including security and privacy concerns, a shortage of skills and expertise, the cost of deploying and managing AI solutions, data quality issues, model bias, ethical considerations, and infrastructure readiness.

Crucially, many organisations lack a structured, enterprise-wide AI strategy, which is fundamental to succeeding in their AI journey. To proactively overcome these obstacles and achieve AI readiness, enterprises should adopt an AI Readiness Framework.

This framework identifies key foundational elements for success, both before embarking on the AI journey and throughout its enablement, ensuring measurable business impact. The framework’s essential pillars are outlined below.

• Key activities: Establishing a comprehensive, organisation-wide strategy, implementing a responsible AI policy with governance mechanisms, designing modern data architectures, and empowering employees through training.
• Core technologies: Gaining a thorough understanding of available data and the capabilities of core AI technologies.
• Infrastructure and platforms: Deploying cloud-native digital infrastructure for compute-intensive AI workloads and enabling data and AI platforms for AI lifecycle management.
• Trust and oversight: Implementing a robust trust and oversight programme to address transparency, bias, regulatory compliance, governance, and ethical considerations in AI.
• Use cases: Prioritising use cases with measurable outcomes and ensuring continuous value delivery across their lifecycles.

The rapid pace of technological advancement demands close attention, particularly to the emergence of AI agents, which represent significant innovations across industries. These digital assistants that work reactively and cooperatively with humans to provide productivity and efficiency gains, along with AI advisors that offer enhanced insights and recommendations to organisations, have quickly become must-haves in modern software.

AI agents independently perceive, evaluate, and act upon data to help organisations move toward more integrated and autonomous work practices. Since the beginning of 2024, technology suppliers and buyers have started exploring and investing in AI agents. IDC predicts that by 2027, 40% of the world’s largest 2,000 companies’ knowledge work will be transformed as agentic workflows reshape task delivery and performance, leading to a doubling in productivity. Although adopting such emerging technologies presents challenges, organisations prepared to seize such opportunities will enjoy a substantial competitive advantage in achieving their goals.

Success in the AI journey also hinges on cultivating a robust partner ecosystem. Partnerships driven by ecosystem collaboration are crucial to successful AI initiatives, as they combine diverse expertise and resources from both technology and non-technology sectors. Technology partners supply critical infrastructure, tools, and support, empowering organisations to implement advanced AI solutions effectively.

Additionally, organisations seeking to become data- and AI-driven will require technology service providers that serve as trusted partners, with comprehensive knowledge of both business and technology requirements, to guide them through this transformative journey. Meanwhile, non-technology partners—such as industry stakeholders, academic institutions, and policymakers—foster innovation through collaborative opportunities.

To gain insights into how organisations can initiate and advance their AI journey, download e& enterprise’s Infobrief titled ““