Artificial intelligence has come of age, moving from a domain of technological novelty to a defining force reshaping global economic, social and industrial systems. Moreover, its ability to process vast amounts of data, streamline processes and provide insights on a scale unimaginable a decade ago has made it imperative for the overall functioning of governments, businesses and academic institutions. In this regard, AI also holds out the promise of efficiency, innovation and economic development, but lurking behind the promise is a question both urgent and deep that pertains to us adopting AI, but who else will adopt AI? 

The answer is not straightforward, but one that entails a complex interplay of the development of labor, structural inequality, environmental necessity and unique alterations in human cognition and agency. The world population has risen steadily over the last ten years, from approximately 7.8 billion in 2020 to a projected 8.2 billion in 2025, as proposed by the UN. Although a higher population ideally means a greater labor force and bigger markets, it also simultaneously stresses employment systems. The AI burst adds to the problem by increasingly automating repetitive manual and even mental tasks. While nations grapple with accommodating increasing populations, they also have to contend with the structural displacement that comes with the speed of AI penetration. 

Work creation has lagged behind such population pressures. The International Labour Organization (ILO) originally projected the development of 60 million new jobs by 2025, but reduced the number to 53 million when the growth of the economy slowed down, as quoted by Challenger, Gray & Christmas. Therefore, a vast majority of these new roles involve high-level technical and AI ability, leaving the conventional workforce increasingly at risk. Consequently, this intensified disconnection adds more pressure to the urgency of getting by on the basis of reskilling and forward-looking workforce planning. Without progressive policies, AI can further exacerbate the global divide between high-skill and low-skill labor markets.

Beyond the bottom line: the collateral impact of automation

On a different note, AI business deployment levels have sped up. Over 25% of large firms had already implemented AI in their operations by 2019, as indicated by the Organization for Economic Cooperation and Development (OECD), given that AI is more operationally efficient, cheaper and more often makes strategic choices. Yet this speed comes at significant human expenses. Analytics, decision-making and creative work are under threat. Overemphasizing efficiency at the expense of greater social costs can lead to incremental erosion of human agency in decision-making and innovation.

Furthermore, job dismissals have already been hit by trade barriers, geopolitics, sanctions and intellectual property conflicts, which are compounded by restructuring due to AI. Over 206,000 employees were discharged by 221 American technology companies in 2025 alone, as estimated by Challenger, Gray & Christmas. These are structural, not cyclical, dismissals, as the labor could be lost for good or require skills that the existing labor pool lacks. Subsequently, this creates traditional destabilizing forces for traditional social safety nets and labor institutions that policymakers will find difficult to deal with.

Furthermore, the environmental impact of AI is typically underestimated. In addition to energy usage, AI needs custom hardware composed of scarce minerals like neodymium, dysprosium and tantalum. The extraction of the minerals has environmental impacts and geopolitical dependencies. The data centers used to house AI systems account for vast amounts of water usage for cooling and plenty of power to process, according to the UN Environment Program (UNEP). Fueled by fossil fuels, these operations have high levels of carbon emissions. Places with this sort of infrastructure are subject to local water deprivation and resource shortage, proof that the social benefits of AI have undetected ecological and social effects.

The cognitive erosion: reclaiming human autonomy

Aside from economic and environmental considerations, AI insidiously menaces human thought and culture. With AI interfaces and alert systems overwhelming human experience, attention is splintered, diminishing creativity, civic engagement and the capacity for long-term strategic contemplation. AI excels at capturing explicit knowledge but cannot fully grasp context-dependent know-how, risking the erosion of institutional memory and local problem-solving capabilities. Automating interpersonal decision-making and AI-mediated communication can diminish empathy, negotiation skills and emotional resilience — qualities essential for healthy workplaces and social cohesion. 

Moreover, AI’s reliance on historical data for optimization may unintentionally constrain innovation, favoring safe and predictable trajectories over bold, unconventional ideas. The psychological reliance on AI for professional, personal and ethical decision-making also risks destabilizing autonomous human thought. Business investment in AI keeps expanding. As per a McKinsey and Company Report, 92% of business executives are planning to increase AI spending, with over half expecting a 10% hike from existing levels. The force of transformation that AI represents is gigantic, but not necessarily for all. Whether AI will raise human potential or speed up inequality will be determined by governance, regulation, upskilling and inclusive deployment strategies. 

As we begin this new era, caution needs to catch up to optimism. Societies may become unwittingly dependent on AI networks owned and controlled by a few large firms, generating systemically produced vulnerabilities. AI-rich environments everywhere can distract attention in the crowd, undermining imagination, long-term thinking and civic participation. Human intuition of context-dependent and experiential knowledge can be contemplated as being pushed aside, and optimization by algorithms can pressure innovation along predetermined lines, deterring out-of-the-box solutions.

The final experiment: shaping our machine-driven destiny

On the whole, dependence on AI for making strategic, individual and moral decisions may quietly erode independent thought. Unobtrusive external costs — such as mining of rare metals, water-cooled operation and energy-intensive usage — add to the multifaceted, interdependent nature of AI deployment footprint. A sense of these problems ensures that AI is benefiting human beings and not becoming stuck in inequality, environmental pressure or psychological reliance.

Moreover, AI is no longer a device; it’s a force remaking the destiny of economies, societies and even the human brain. The question now is no longer whether we can control AI, but whether human beings will be the masters of their own destiny and not just passive actors in a machine-dominated world. Optimism about AI needs to be paired with foresight, ethical sensitivity and robust governance.

Therefore, in order to realize its full revolutionary potential, human societies will have to develop not only technological know-how but also public wisdom, cultivating a human-AI partnership that is attuned to local conditions and capable of responding to diverse social and environmental exigencies. Not only are we developing AI, but AI is also developing us. It is a different kind of experiment, and one whose outcome is less predictable and more fateful than ever.

[Ainesh Dey edited this piece]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.