Artificial intelligence (AI) is transforming the relationship between technology, economy, society and nature. Its potential to accelerate scientific discovery, optimize energy systems, improve water management and strengthen climate resilience offers unprecedented opportunities for sustainable development. Yet the same technologies can intensify resource extraction, concentrate economic power, undermine privacy and amplify social inequalities. This contradiction raises a fundamental question: can humanity govern the technological revolution it is creating, or will technological expansion increasingly determine the direction of human civilization?

The dilemma is especially significant for the Middle East and North Africa (MENA). Countries in the region are investing in AI, digital infrastructure, smart cities and data centers, while simultaneously confronting water scarcity, food insecurity, climate vulnerability and the challenge of economic diversification. AI could help address these challenges, but it could also reinforce hydrocarbon dependency, surveillance infrastructures and technological reliance on external corporations.

The central argument of this article is that sustainable AI requires a transition from a technology-driven economy towards a moral economy of artificial intelligence. Such an economy would place technological innovation within a framework of social justice and ecological responsibility. Consequently, the challenge is not simply to accelerate AI innovation, but to ensure that technological power remains accountable to society and the natural world.

1. Beyond Technological Determinism: AI as a Socially Constructed System

A dominant narrative in contemporary technological discourse assumes that AI represents an inevitable wave of progress to which societies must adapt. This narrative reinforces technological determinism, the assumption that technological development follows an a trajectory that largely determines social and economic transformation. However, technologies are not neutral instruments; their design and application reflect choices about whose problems deserve attention, which knowledge is recognized and what purposes innovation should serve.

This perspective changes the debate about AI in MENA. Consider water management. AI can optimize desalination, predict groundwater depletion and improve agricultural irrigation. However, whether these applications prioritize equitable access, industrial consumption or ecological protection depends on the institutional arrangements and economic priorities governing their deployment. The question is therefore not whether AI is good or bad, but how societies construct and govern its purposes.

Islamic ethics offers an important normative foundation for this discussion. The concept of oneness (Tawhid) emphasizes the interconnectedness of creation, while the role of a human as a witness and a steward (Khalifah) establishes humanity’s responsibility to protect and manage natural resources. Technology should consequently be evaluated according to its contribution to the common good, rather than its computational capacity or profitability. The moral economy perspective therefore asks three fundamental questions: Who owns technological capabilities? Who benefits from the value generated by AI? Who bears the social and environmental costs? These questions are particularly important in MENA, where the concentration of digital infrastructure and investment could create new inequalities between countries, corporations, workers and communities.

An Islamic moral economy provides a distinctive ethical foundation for addressing these challenges. The principles of Adl (justice), Amanah (trust), Ihsan (excellence) and public interest suggest that economic and technological activities must serve society rather than subordinate society to the interests of capital. For MENA, the development of a moral economy of AI would mean encouraging innovation ecosystems in which commercial incentives are balanced by public accountability, ecological responsibility and inclusive access. The ultimate objective is to move from an economy that treats data, natural resources and human attention as commodities towards an economy that recognizes them as resources carrying social and ethical responsibilities.

2. The Sustainability Paradox and the Problem of Path Dependency

One of the most important contradictions of the AI revolution is the sustainability paradox. AI can improve resource efficiency while simultaneously increasing the overall demand for energy, water, minerals and computing infrastructure. The International Energy Agency’s 2025 report, Energy and AI, illustrates this dual relationship. AI can support electricity-grid optimization and energy efficiency, but the expansion of data centers also creates additional electricity demand.

For the GCC, this raises difficult questions about the environmental sustainability of large-scale digital infrastructure in hot, water-stressed environments. The paradox extends to the wider economic structure. AI can optimize oil and gas production, improve extraction efficiency and extend the life of existing hydrocarbon infrastructure. However, these applications may reinforce the very economic dependencies that energy diversification strategies seek to overcome.

This is where path dependency becomes critical where historical investments, institutional structures and increasing returns can lock societies into established technological and economic trajectories. MENA’s hydrocarbon-based development models have generated infrastructure, expertise, investment patterns and institutional interests that may constrain alternative pathways.

AI can therefore become either an instrument of structural transformation or a mechanism for reproducing existing economic dependencies. The Islamic concept of balance (Mizan) provides an alternative criterion for evaluating technological progress. The Qur’an emphasizes balance in creation (55:7–9), while the concept of overconsumption (Israf) challenges excessive resource consumption. From this perspective, environmental sustainability cannot be reduced to technological efficiency; it must also involve ecological balance, responsible consumption and intergenerational justice. The objective would be to use AI to escape unsustainable development trajectories rather than make them more efficient.

The expansion of AI also raises fundamental questions about the relationship between technological power and human freedom. Surveillance capitalism explains how digital platforms extract behavioral data and transform human experiences into commercial assets. AI significantly expands this capacity through predictive analytics, automated decision-making and behavioral influence. This creates a contradiction: technologies presented as instruments of empowerment can also become instruments of control. The challenge is to ensure that AI strengthens human capabilities without turning citizens into objects of continuous monitoring, classification and commercial extraction.

3. From Technological Progress to Moral Responsibility

It is argued that AI and synthetic biology combine characteristics that make containment particularly difficult due to increasing capabilities, falling costs, widespread accessibility, and broad applicability. The resulting dilemma is that governments, businesses and societies have powerful incentives to develop these technologies even when their risks are not fully understood. Containment, in this context, should not be understood as an attempt to stop scientific progress. It is an effort to establish institutional, technical and political mechanisms that keep technological capabilities within acceptable boundaries. It is critical to develop norms and standards to ensure technical safeguards and governance arrangements. Containment should therefore involve not only asking what AI systems can do, but also what they should be permitted to do, who should decide and in whose interests.

On another hand, strategic foresight provides a way to explore how different governance choices may shape the future of AI and sustainability. The Sustainability Paradox scenario describes a future in which technological efficiency improves while ecological pressures continue to intensify. Post-Truth Division scenario describes a future in which misinformation, social fragmentation and declining trust undermine collective action.

Generative AI may intensify political polarization and weaken the shared knowledge necessary for addressing climate change and other sustainability challenges. Fortress Multipolarity scenario presents a more fragmented future, characterized by geopolitical competition, resource insecurity, and surveillance. In this scenario, technological power becomes closely connected to security and control. Global Awakening scenario offers a more hopeful alternative, in which technological capabilities support ecological regeneration, social solidarity and collective responsibility. These scenarios present alternative possibilities that help policymakers examine the consequences of current choices.

Bottom Line

These arguments suggest that the future of AI should be governed through a new development paradigm that integrates technological innovation, moral economy, and ecological sustainability.  A sustainable AI future requires markets to remain embedded in social values, technological innovation to serve the common good and economic development to respect ecological limits. In sum, the future of AI should not be measured by how much power humanity can extract from technology, but by how wisely humanity can govern that power.