Beyond the Hype: Building a Sustainable AI Future

Ammon

a day ago

The promise of artificial intelligence is no longer a distant vision; it is a present reality delivering tangible value. A powerful case in point unfolded in a hospital, where an AI system, analyzing an X-ray with unparalleled precision, diagnosed a hidden malignant tumor and provided a proactive treatment plan. This single act not only saved a life but serves as a clear demonstration of AI's power to redefine operational paradigms and elevate critical services. For Jordan, this isn't merely a technological event—it's a catalyst for national growth, demanding a new, professional approach to harness its full potential.
Despite a global race to invest in AI, with over 88% of executives planning to increase their budgets, there's a significant paradox: less than 1% of organizations worldwide have actually achieved AI maturity. This isn't for a lack of money or interest. Instead, the problem stems from a fundamental misunderstanding of what AI success requires. Gartner warns that over 40% of AI projects are at risk of being canceled by 2027, not due to technical limitations, but because of poor execution, a lack of clear goals, high operational costs, and a shortage of skilled talent. This means that without a holistic and strategic approach, AI can quickly become a financial and organizational burden instead of a powerful opportunity. The path to maturity is not about buying technology; it's about building an integrated system that transforms the entire organization.
To move beyond the experimental phase and achieve real, sustainable impact, organizations must commit to a comprehensive roadmap based on six interconnected pillars. This journey begins with an Integrated Strategic Vision. This means embedding AI into the very fabric of your business, not as a separate IT project, but as an indispensable engine driving the company's core strategy.
This vision must then be tied to Comprehensive Value Measurement, which goes beyond traditional productivity metrics. Its value must be measured across three critical levels: commercial (e.g., increased revenue), technical (e.g., system resilience), and, most importantly, behavioral. This last part is often overlooked, but it is vital. If employees resist using a new AI tool out of fear or mistrust, the project, no matter how technically brilliant, will fail. Measuring and managing this human response is the key to successful adoption.
Building on that foundation, a Collaborative Structure is essential. AI cannot thrive in organizational silos. Success requires "fusion teams" that bring together technical experts, business leaders, and data analysts. A Center of Excellence (CoE) is an ideal model for this, acting as a central hub for best practices, shared knowledge, and governance, preventing duplicated efforts and ensuring alignment with the company's broader goals. Furthermore, an organization cannot fully leverage AI if its people don't understand it.
AI Literacy is a vital pillar, providing training not just for data scientists but for everyone, from executives who need to understand strategic implications to front-line staff who need to use the tools effectively and ethically. This widespread understanding builds trust and accelerates adoption.
The final pillars address the critical needs of trust and infrastructure. Proactive Governance is a necessity to protect against issues like bias, data privacy violations, and lack of transparency. Organizations must build ethical frameworks from the ground up, implementing policies that ensure fairness, accountability, and compliance with evolving regulations. This is particularly important for Jordanian companies that operate globally or handle sensitive data. This governance must be supported by an Advanced Data Infrastructure. Data is the fuel for AI, but not all data is created equal. The infrastructure must support "AI-ready data"—data that is not only clean but also contextual and representative of real-world scenarios. This requires investing in the right tools and platforms, as well as establishing strong data governance and metadata management to ensure data pipelines are reliable and efficient.
By embracing these six pillars, Jordan can use AI to achieve a transformative economic shift. AI can boost the national income by: Improving Productivity, as automating repetitive tasks in both public and private sectors could increase employee productivity by 20% or more, allowing staff to focus on higher-value work. Moreover, Jordan can position itself as a regional leader by Developing New Industries in AI-driven sectors like "Green AI" for environmental sustainability or "AI in Health" for advanced medical services. Finally, a mature and well-governed AI ecosystem will be a major draw for Attracting Foreign Investment, creating new jobs and boosting economic growth.
Ultimately, AI is no longer a technical option; it has become an economic and developmental necessity. It requires both the public and private sectors in Jordan to shift from an experimental project approach to building sustainable, integrated systems. The pressing question is: Is Jordan ready to lead this transformation, or will we remain passive observers in the global digital economy?