Abstract: Artificial intelligence is an emerging technology that is predicted by many experts to arrive by the end of this decade. It will be transformative, changing how humans interact with each other, and will bring various benefits and drawbacks. While these benefits and drawbacks will be monumentally changing, the timeline of widespread implementation of AI is debatable. This piece aims to provide a better understanding of the factors that will either hinder or accelerate AI development.
Problem statement: These factors need to be understood to implement effective AI governance that maximises the benefits of AI while mitigating harmful effects.
So what?: AI will be one of the most important technical evolutions in human history. Understanding which factors could hinder or accelerate its progress will better guide humanity as we approach its implementation by providing an estimate of when the AGI threshold will be crossed.
What is Artificial Intelligence?
Artificial intelligence, a system that relies on advanced algorithmic coding to simulate human cognition, seems to permeate almost every aspect of society and is a frequent topic of discussion. From military uses to medicine, technology, and finance, the race to implement AI seems poised to be the next great milestone in humanity’s progression. There are three main phases of AI: LLMs, AGI, and ASI. Current large language models (LLMs) represent a form of narrow AI. While they demonstrate impressive capabilities within specific domains, they do not meet the commonly proposed criteria for Artificial General Intelligence (AGI), which requires broad, human-level competence across a wide range of cognitive tasks. LLMs are trained on massive amounts of widely available data that relies on recognising patterns of text to accomplish tasks given to them by humans.[1] This technology is used in chatbots like ChatGPT, Claude, and Grok, which answer human prompts across a wide variety of tasks. While not AGI, this technology is widely seen as an important step toward more general AI systems. AGI will be the first AI program to achieve a milestone: meeting or exceeding human cognition across all assigned tasks.[2] This can be done by continually rewriting its computer code to learn from past experiences, demonstrating common sense and autonomy not currently found in humans. LLMs may match or exceed human cognition in some narrowly defined domains, such as games like chess or navigating a car through city traffic, but cannot currently match human capabilities across all tasks. This means it will be able to learn, adapt, reason, plan, and apply knowledge across a wide range of disciplines. While still hypothetical, there are numerous philosophical and engineering barriers to overcome to develop this technology. The final stage of AI, artificial superintelligence (ASI), will surpass AGI in every way. Significantly smarter than humans in every aspect, this technology will most likely operate in a continuous loop of self-improvement, improving at an exponential rate.[3] Although many forecasts anticipate AGI within the coming decade, and most likely it will be, understanding and predicting what factors may hinder or accelerate AI progress are vital to understanding what could be the most consequential human invention in hundreds of years.
This article does not attempt to predict a precise date for AGI. Instead, it identifies the principal drivers likely to influence the pace of development. These drivers are grouped into factors that could slow progress (governance, public resistance, infrastructure constraints) and those likely to accelerate it (market competition and geopolitical rivalry). Together, these provide a qualitative framework for assessing how the timeline may shift under different policy and technological conditions.
While LLMs have evolved from simple chatbots to more advanced models over the years, they have yet to meet the standard of AGI, as their programming does not enable them to perform all cognitive tasks as well as humans do.[4] LLMs are good at predicting which words to use in response to prompts, but cannot learn independently from humans or operate outside their predefined task range.[5] While the exact definition of AGI is still debated, as it could be either a program that matches or exceeds human intelligence across all cognitive tasks or is simply an advanced LLM that can learn by itself without human input, no one can doubt that creating a program akin to human-level intelligence will upend multiple aspects of global society. Even the timeline for implementing this technology is being debated.[6] Anthropic’s Dario Amodei claims that AGI may be here within one or two years.[7] Sam Altman thinks similarly.[8] The CEO of Google’s DeepMind, Demis Hassabis, believes we are 2 to 4 years away.[9] DeepMind’s founder and former chief scientist, Shane Legg, said there’s a 50% chance that AGI will arrive by 2028.[10] Although these forecasts originate from industry leaders with commercial incentives, they nevertheless indicate a growing consensus that AGI could emerge before the end of this decade. The U.S. government has no official timeline, as do other nations, but is keeping a close eye on developments. When the AGI threshold is universally accepted as crossed and implemented across wide-ranging aspects of society, it will be debated, but understanding the factors that hinder or accelerate this crossing is vital to tracking one of humanity’s most important advances.
AGI will be transformative once widely implemented. The changes it will have on society could be vast, and diverse across a wide range of sectors. However, proper governance is needed, and society will need to adapt in order to accommodate this emerging technology. Understanding the AGI timeline and the factors that could hinder or accelerate it will help the global community properly adjust in time. Hopefully, this will mitigate some of the negative effects of AGI, such as risks associated with the economy or the military. On the other hand, this could also help realise the positive effects of AI more effectively, such as in medicine and research. The timeline is far from certain, but understanding what could hinder or accelerate AGI development will be beneficial as we approach the AGI threshold.
Factors that will Hinder AI Development
AI, like all emerging technology, is receiving pushback across a variety of sectors.[11] This pushback, which can delay the crossing of the AI threshold, can be from national or international governance, domestic grassroots opposition, and the inability of AI to be supplied with the resources needed to operate before it can be implemented. Governance, whether by national governments, international bodies, or treaties among nations, could regulate AI precursors to the point that the implementation of AGI is delayed. Domestically, many are wary about AI replacing workers. Upwards of 300 million jobs could be automated by AI in the not-too-distant future.[12] Understandably worried, citizens have begun raising concerns about entering the job market or holding on to their jobs.[13] If AI and its subsequent impact on the economy become increasingly pertinent to voters, upward pressure on politicians could also hinder AI development. Recent polls found that a majority of US voters favoured more AI regulation.[14] This is already being seen at the local level, where communities rally against data centres, and concern rises among voters.[15] Finally, the sheer infrastructure demand of AI could cross the threshold. Data centres, which house and run AI programs, could use up more power than the entire state of New Hampshire, home to 1.4 million people.[16] Ten of these data centres are under construction in America alone. While each of these factors may be solvable in the future, policy will have to change. Until it does, the timeline for crossing the AGI threshold will remain years away.
National and International Governance
Early AI regulation varies from nation to nation. The UK currently lacks a general regulation and instead adopts a decentralised approach to enforcing the use of AI, protecting private data and other consumer protections under existing laws.[17] However, there is a growing push from the Labour Party to introduce regulations against companies developing the most powerful AI tools to ensure a safer future.[18] Across the channel, the EU is also regulating AI. Potential AI programs are regulated based on the risk they pose to users, and compliance requirements are assigned accordingly.[19] America does not have any national-level AI regulation. In early 2025, President Trump removed barriers to AI development, including the deregulation of oversight measures designed to ensure safety, reliability, and cybersecurity, to promote beneficial AI uses, after big tech companies spent $ 394 million on campaign donations during the 2024 U.S. election.[20], [21], [22] The People’s Republic of China (PRC) is removing barriers as well, but heavily censoring political content and other social aspects of AI use.[23] America and the PRC lead the world in AI development, in part because they lack national-level regulation like that of nations or blocs. While this may suggest they are not hindering AI development now, there are ongoing unofficial talks between the two nations about managing emerging military capabilities, the potential for escalation, and other existential risks associated with AI.[24] If these talks are formalised in treaties, regulations could be enforced by inspecting factories that produce the computer chips required for AI use. While this pathway is still unofficial, there is hope it may delay crossing the AGI threshold until proper governance is in place.
Domestic Pushback
While AI will have beneficial outcomes for humanity, many are unsure of whether crossing the threshold will benefit all. LLMs have already shown remarkable results in detecting cancer.[25] There are also educational benefits, such as tailoring teaching programs for personalised learning.[26] The percentage of S&P 500 companies reporting quantifiable benefits from AI increased by 11% from 2024 to 2025.[27] One study showed that “98% of CEOs believe they’d benefit immediately from AI implementation, and three-quarters already have.”[28] However, some are worried about losing their jobs, while others worry about the wealth gap growing. According to research, 29% of entry-level workers are “worried” about AI, with one in three feeling anxious about its impact on their jobs.[29] Students who will graduate from college soon have voiced opinions against AI as well, as entry-level jobs in previously stable fields such as programming, data entry, journalism, and customer support may be the first to be replaced.[30] Those with creativity-based jobs, such as those in the entertainment business, have begun taking a hardline anti-AI stance, driving workers to join unions to protect creativity and ensure AI will not take their jobs, signalling that AI will not benefit everyone, perhaps just a select minority.[31] If those in fields that could be replaced by AI push back, upward pressure on politicians could force stricter AI regulation and delay the crossing of the threshold.
Lack of Resources
Others not so directly affected have pushed back as well. Data centres, which use vast amounts of electricity and require immense amounts of water for cooling, must be designed not just for current LLMs but also for AGI. This has created localised water shortages in nearby communities while placing an increasing burden on regional energy infrastructure. Transparency issues concerning permitting also arise, with wealthy and influential big tech companies having more sway over local and state governments than individual citizens. While these concerns are mostly local, the upward pressure from average citizens may force national governments to implement regulations which delay the development of AI.
Factors that Will Accelerate AI Development
The main drivers of AI are private, for-profit companies and governments, specifically those of America and the PRC. Private companies seek to maximise their profit margins by reducing overhead costs and improving efficiency through AI. In turn, this may drive AI companies to develop AI programs for businesses. The Thomas Reuters Institute concluded that businesses that adopt LLMs earlier than others both expect and receive increases in revenue, with 70% of professionals seeing the benefits AI has on business and “almost half (49%) of respondents said they believe moving more slowly than the market would have a negative (47%) or even catastrophic (2%) impact on their organisation“.[32] On the other hand, governments, specifically those of the PRC and the U.S., the global leaders in AI, are seeking to develop AI not solely for economic gain, but to establish military superiority over one another. Many experts believe that AI could be the next superweapon, as its processing power can be harnessed to identify strategic targets or patterns in enemy decision-making.[33] Most nations, especially China and America, are racing to be the first to implement AGI in their militaries, with the first gaining a newfound advantage in capabilities that will leave other nations lagging behind.[34] While the future of emerging technology is always difficult to predict, the ability of AI to manage massive amounts of data that would overwhelm humans and make decisions almost instantaneously would give any military a major advantage in conflict.
Domestic Competition
Private companies are motivated by the need to generate profits. AI can be immensely beneficial in this sense. AGI, the type of AI that can meet or exceed human cognition in every task assigned to it, will be indistinguishable from human workers if the predicted definition comes true.[35] However, unlike humans, AGI can work 24 hours a day, including weekends and holidays, and doesn’t tire or make the mistakes humans are prone to. It can also potentially work for cheaper. This could drive up profits by reducing overhead costs, allowing companies to make more money. Private companies, such as Anthropic, xAI, OpenAI, and a host of other tech companies, are racing toward the AGI threshold. Corporate AI investment reached 252.3 billion dollars in 2024, a 44.5 per cent increase from the year before.[36] Corporations that used early AI programs reported both cost savings and revenue gains. In a capitalist society, the need for AI will drive investment and, in turn, development. The potential for AI to better analyse datasets, innovate, and automate administrative tasks will drive domestic competition in the private sector as businesses seek to outcompete one another.[37]
International Competition
Likewise, there are different, but important factors that drive AI development by governments. The military use of AI is the most important driver of international competition as reliance on private AI companies increases lethality and decreases decision-making time.[38] AI can process data collections more quickly, launch or defend against cyber-attacks faster, make faster judgement decisions, does not stress or tyre, and can better manage information networks needed to operate in complex, multi-domain environments such as the Indo-Pacific or the Middle East.[39] This incentivises militaries to incorporate AI into nearly every aspect of warfare, and for governments to procure this emerging technology to gain an advantage by working with private companies. Some believe that AI will be the next superweapon and will trigger arms races, as militarised AI will enable all forms of weapons to strike targets with little or no human input.[40]
The U.S. and the PRC, major world competitors, are already in this arms race.[41] The Pentagon recently signed eight different agreements with tech companies to implement a wide variety of early AI programs designed to improve efficiency, even in the classified workspace.[42] The Department of War also recently requested nearly $ 30 billion to purchase and maintain AI-capable supercomputers as part of its “AI Arsenal Initiative.”[43] Across the Pacific, the PRC also signed 343 AI-related contracts with its state-owned defence enterprises, but given the opaque nature of Chinese defence spending, the exact amount of investment and capabilities remains unknown.[44] Both nations seek to outdo each other to gain an advantage that will better deter unwanted aggression or win an armed conflict. Each side is likely unaware of the other’s exact capabilities and ambitions, and this fear of the unknown, compounded by the highly technical AI programs each nation is developing, is likely to drive future AI procurement, thereby accelerating development.
Counterarguments
While the AGI threshold has yet to be crossed, its arrival seems imminent.[45] OpenAI’s latest ChatGPT LLM model broke through a significant barrier in pattern recognition, a large step toward AGI.[46] However, the timeframe is still up for debate. Private companies, motivated by profits, have an incentive to cross the threshold before other companies, which could lead to false claims of having developed the first AGI program. The same can be said of governments, which are frequently found to lie about their military capabilities. AGI could also already be here, but hidden in a secret government laboratory while undergoing testing. It could also emerge from an individual, working alone without connections to big tech or loyalty to any government. Furthermore, AGI also may never be invented. Some technologists argue that consciousness is a uniquely biological process and cognition can never be replicated inside a computer.[47] The physical, technological, and societal obstacles to be overcome are complex, intertwined, and difficult to foresee or predict. Current LLMs may also reach a technological plateau, where innovation stalls, preventing the developments needed to progress toward AGI.[48] This complicates the forecasting of the exact moment when the threshold is crossed. The exact definition of AI is also debated.[49] Just because an advanced computer program can win a game of chess against a grandmaster or pass a law exam does not mean that AGI is comparable to or better than humans at every task. The term ‘AI’ is often used interchangeably with LLMs, even though they represent narrow AI rather than AGI.
Conclusion
Like any other massively transformative technology, AI will be very disruptive. It will have immense benefits in the fields of medicine, business, the military, and science. It will also cause society to change in unexpected ways, and not always for the better. Increased automation may lead to the mass employment of highly skilled and educated workers whose entire career fields have been eliminated. Its military applications almost ensure a new era of superpower status for whichever country implements it first, with the risks of uncontrollable escalation or accidental war that follow.[50] Wargaming research done at King’s College London showed that GPT-5.2, Claude Sonnet 4, and Gemini 3 Flash showed that LLMs “readily threatened nuclear strikes, with 95% of games witnessing “nuclear signalling” from the models, and often crossed the “nuclear threshold” to actually drop bombs, with 76% of games reaching “strategic nuclear threats”.“[51] These real threats also need to be addressed.
AI is also unique in that it may come from either the private or public sector and cannot be easily reverse-engineered like other technologies. This, combined with its wide-ranging applications, will mean that whoever invents it will have a massive head start over future competitors. The incentive to be the first to cross the AGI finish line is massive, in both profits and capabilities.
Once the AI threshold is crossed, change will happen quickly, perhaps faster than society can adapt. As AGI programs develop, they will become increasingly adept at all tasks. Understanding the factors that will hinder or accelerate AI adoption will help ensure there is enough time for proper governance and for society to adjust accordingly. Unregulated AI may lead to better, more widespread AI programs, but a lack of proper governance may result in societal unrest, uncontrollable military escalation, or even existential risks to humanity if AI programs are misused. There is still enough time to properly regulate AI, but governments must act quickly before the threshold is crossed.
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