When will we have AGI?

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1. 1

   Forecasting Transformative AI: An Expert Survey

   arXiv (Cornell University) (Gruetzemacher et al.)Published Jan 24, 2019Checked Oct 10, 2026

   “A survey was administered to attendees of three AI conferences during the summer of 2018 (ICML, IJCAI and the HLAI conference). The survey included questions for estimating AI capabilities over the next decade, questions for forecasting five scenarios of transformative AI and questions concerning the impact of computational resources in AI research. Respondents indicated a median of 21.5% of human tasks (i.e., all tasks that humans are currently paid to do) can be feasibly automated now, and that this figure would rise to 40% in 5 years and 60% in 10 years. Median forecasts indicated a 50% probability of AI systems being capable of automating 90% of current human tasks in 25 years and 99% of current human tasks in 50 years. The conference of attendance was found to have a statistically significant impact on all forecasts, with attendees of HLAI providing more optimistic timelines with less uncertainty. These findings suggest that AI experts expect major advances in AI technology to continue over the next decade to a degree that will likely have profound transformative impacts on society.”

2. 2

   Europe and the Geopolitics of AGI: The Need for a Preparedness Plan

   arXiv (Cornell University) (Negele et al.)Published May 13, 2026Checked Oct 10, 2026

   “Drawing on empirical trends in AI capabilities, expert forecasting surveys, and policy analysis, we find that a plausible window for AGI emergence falls between 2030 and 2040, or potentially earlier, though substantial uncertainty remains. Our analysis of the geopolitical implications suggests that AGI could fundamentally alter the global distribution of economic and military power, intensify interstate competition, and strain existing governance frameworks. Assessing Europe's current positioning, we identify critical gaps: limited strategic awareness of frontier AI progress, structural weaknesses in compute infrastructure and talent retention, low rates of industrial AI adoption, and fragmented policy responses at both EU and Member State levels that do not match the potential scale of disruption.These findings point to a need for a coordinated European preparedness agenda. We outline policy options centred on building institutional capacity for AGI situational awareness, strengthening Europe's position in the AI value chain, and developing frameworks for international stability in an era of increasingly capable AI systems.”

3. 3

   Review of Artificial General Intelligence (AGI): Implications for the U.S. Workforce and Economic Stability

   International Journal of Innovations in Science Engineering and Management. (Joshi)Published Jun 19, 2025Checked Oct 10, 2026

   “This paper further provides a comprehensive review of the predicted and potential impacts of AGI on the global job market. We analyze key themes including job displacement risks, emerging employment paradigms, and policy considerations in preparation for AGI integration. Drawing upon recent literature, we explore various facets, including job displacement, the emergence of new roles, economic implications such as wage dynamics, and the critical need for workforce adaptation through reskilling and upskilling initiatives. Furthermore, we delve into the societal and ethical considerations surrounding AGI's development and deployment, including concerns about preparedness, timelines for its arrival, and the imperative for responsible governance. By synthesizing diverse perspectives, this review aims to offer a holistic understanding of how AGI could reshape employment landscapes, urging proactive measures from policymakers, educators, and individuals to navigate this evolving future. The synthesis reveals divergent expert perspectives on both AGI timelines and socioeconomic consequences, highlighting critical gaps in workforce preparedness.”

4. 4

   The race for an artificial general intelligence: implications for public policy

   AI & Society (Naudé & Dimitri)Published Apr 22, 2019Checked Oct 10, 2026

   “It is established that, in a winner-takes-all race, where players must invest in R&D, only the most competitive teams will participate. Thus, given the difficulty of AGI, the number of competing teams is unlikely ever to be very large. It is also established that the intention of teams competing in an AGI race, as well as the possibility of an intermediate outcome (prize), is important. The possibility of an intermediate prize will raise the probability of finding the dominant AGI application and, hence, will make public control more urgent. It is recommended that the danger of an unfriendly AGI can be reduced by taxing AI and using public procurement. This would reduce the pay-off of contestants, raise the amount of R&D needed to compete, and coordinate and incentivize co-operation. This will help to alleviate the control and political problems in AI. Future research is needed to elaborate the design of systems of public procurement of AI innovation and for appropriately adjusting the legal frameworks underpinning high-tech innovation, in particular dealing with patenting by AI.”

5. 5

   Pathways to AGI

   arXiv (Cornell University) (Fletcher & Khan)Published May 7, 2026Checked Oct 10, 2026

   “This conditioning of any view regarding AGI does lead the discussion in specific directions and to certain conclusions regarding the future. However, adopting this perspective enables the work to offer some final recommendations. We set out to ask the following questions, 1. What are the critical pathways that produced the current dominant generative AI tools (capabilities, product forms, adoption patterns)? 2. Which decision points acted as leverage nodes (small changes that had large downstream effects), and which dead ends reveal alternative possibilities that did not become dominant? 3. How do pathways differ across three foundational-model trajectories such as the frontier proprietary models, open-weight models or specific domain and sovereign models? 4. Which alternative projects branched from key leverage nodes, what is their current state, and why did some succeed, stall, fail or become absorbed? 5. Based on this analysis, what socio-technical development programmes could plausibly move toward AGI-adjacent capability while meeting requirements for transparency, moderation, wellbeing and sustainable business models?”

6. 6

   The Forthcoming AGI Revolution: Its Impact on Society and Firms

   Preprints.org (Makridakis & Michailides)Published Aug 6, 2025Checked Oct 10, 2026

   “This paper examines the transformative impact of Artificial General Intelligence (AGI), poised to redefine society and organizations by surpassing narrow AI's capabilities. Drawing on historical technological revolutions, we analyze AGI’s potential to enhance problem-solving, address global challenges like climate change and healthcare disparities, and reshape labor, governance, and human purpose. Through a human-AI collaborative approach, we present four scenarios—ranging from utopian synergy to existential risks—to assess AGI’s societal and economic implications. Key considerations include cognitive automation, ethical governance, and equitable access. We propose actionable recommendations for governments, firms, and educational institutions, emphasizing reskilling, international cooperation, and ethical frameworks to ensure AGI fosters inclusive prosperity while mitigating risks like job displacement and inequality.”