Expert cautions as AI emerges next essential need

 We stand at the precipice of what many are calling the fourth industrial revolution, driven not by steam, steel, or silicon alone, but by artificial intelligence. From algorithms curating our newsfeeds to large language models drafting our emails and diagnostic tools spotting early-stage cancers, AI is rapidly transitioning from a speculative technology to what pundits and CEOs alike are branding the “next essential need.” This framing is potent and dangerous. While the utility of AI is undeniable, the rhetoric of essential demands urgent caution. We must not rush to embrace AI as an indispensable utility like electricity or the internet without first establishing robust ethical, social, and structural guardrails. To view AI merely as the next consumer necessity is to misunderstand its profound agency and risk cementing its flaws into the foundations of our future. 

The argument for AI’s “essential” status is compelling on its surface. Proponents point to its transformative potential in critical sectors. In healthcare, AI can accelerate drug discovery, personalise treatment plans, and improve diagnostic accuracy, potentially saving millions of lives. In climate science, it optimises complex models for renewable energy grids and tracks deforestation in real-time. In education, it promises personalised tutoring, adapting to each student’s pace. For businesses, it is a powerful engine for efficiency, innovation, and data analysis. The economic imperative is clear: nations and corporations that lag in AI adoption risk obsolescence. This creates a powerful, fear-driven momentum to onboard AI at all costs, reinforcing the narrative of its indispensability. However, this very narrative is the heart of the problem. Labelling something an “essential need” historically triggers a societal shift toward universal, often uncritical, adoption. 

We do not ethically debate the electricity flowing to our homes; we expect it to be safe, reliable, and available. Applying this framework to AI is a categorical error.  Its “intelligence” is a reflection of the data it consumes and the objectives set by its human creators. This makes it a vector for amplification of both human genius and human prejudice. The first and most critical area for caution is embedded bias. AI systems trained on historical data inevitably codify the inequalities of the past. We have seen this in algorithmic hiring tools that disadvantage women, predictive policing that targets minority neighbourhoods, and credit scoring models that perpetuate socioeconomic disparities. If these biased systems become “essential infrastructure,” they will automate and invisibly scale discrimination, making it harder to identify and root out. Justice would become algorithmic, without a pathway to appeal. Secondly, the drive for essentially threatens to outpace our development of meaningful accountability and transparency. The most powerful AI models, particularly deep learning systems, are often “black boxes.” Even their engineers cannot always explain why a specific output was generated.

 When an AI denies a loan, recommends a medical procedure, or influences a parole decision, “the algorithm decided” is an unacceptable answer. For an essential technology, we demand reliability and recourse. Our current regulatory and technical frameworks are woefully inadequate to provide this for AI, yet the market rush continues unabated. Furthermore, the economic and social disruption caused by widespread AI adoption could be seismic. Framing AI as an essential corporate need will fuel aggressive automation far beyond factory assembly lines. Knowledge work—in law, finance, media, and administration—is squarely in its sights. The promise is increased productivity, but the human cost could be massive job displacement and increased inequality if the transition is not meticulously managed. A technology that creates societal instability while being branded “essential” is a recipe for deep conflict and a loss of public trust.

The concentration of power presents another profound danger. The development of cutting-edge AI requires immense computational resources, vast datasets, and highly specialised talent. This naturally consolidates power in the hands of a few mega-corporations and state actors. If AI becomes as essential as the internet, these entities would wield unprecedented influence over the economic, political, and informational spheres of daily life. We risk moving from a digital divide to an “intelligence divide,” where access to the best AI tools determines opportunity, creating new, almost unbridgeable, class structures. Finally, the “essential need” narrative actively stifles the most important conversation we need to have: what is AI? If you are writing a formal text, avoid using prepositions at the end of a sentence. It focuses on capability and adoption, not purpose and alignment. Should AI primarily optimise for corporate profit and state control, or for human flourishing and societal benefit? The race to integrate AI everywhere risks locking in the former by default. We must ask if we are building a world where humans are constantly optimised by AI, or one where AI is thoughtfully designed to augment human agency, creativity, and connection.

 Therefore, the caution is not against AI’s development, but against its mindless coronation as an essential commodity. The path forward requires a deliberate, society-wide effort to domesticate this powerful technology before it becomes ubiquitous. We need strong, adaptive regulation that focuses on outcomes, not just technical specifications. Legislation must mandate algorithmic impact assessments, enforce rights to explanation, and establish strict liability frameworks. We need international cooperation on standards and safety, akin to nuclear non-proliferation, to prevent a reckless race to the bottom. We must invest heavily in public understanding and literacy, demystifying AI so citizens can engage critically with its role in their lives, not just consume it passively. Crucially, we must support the development of human-centric AI—technology designed to augment and collaborate, not merely to replace and optimise.

 The emergence of artificial intelligence is a defining moment for our species. It holds a mirror to our values, our biases, and our aspirations. To view it simply as the “next essential need” is to see only the reflection of our own consumerism and technological determinism. We must look deeper. AI will not be a neutral tool we use; it will be an environment we inhabit and a partner we engage. If you are writing a formal text, avoid using prepositions at the end of a sentence. The imperative is not to install it as quickly as possible, but to shape it as wisely as we can. Our caution today is not an attempt to halt progress, but the essential foundation for ensuring that this monumental technology ultimately serves humanity, and not the other way around. The goal is not to make AI essential to our systems of efficiency, but to make wisdom essential to our systems of AI.