Access AAAI Presidential Panel Report on the Future of AI Research Here
The AAAI 2025 presidential panel on the future of AI research aims to help all AI stakeholders navigate the recent significant transformations in AI capabilities, as well as AI research methodologies, environments, and communities. It includes 17 chapters, each covering one topic related to AI research, and sketching its history, current trends and open challenges. The study has been conducted by 25 AI researchers and supported by 15 additional contributors and 475 respondents to a community survey.
Letter from the AAAI President:
As AI capabilities evolve rapidly, AI research is also undergoing a fast and significant transformation along many dimensions, including its topics, its methods, the research community, and the working environment. Topics such as AI reasoning and agentic AI have been studied for decades but now have an expanded scope in light of current AI capabilities and limitations. AI ethics and safety, AI for social good, and sustainable AI have become central themes in all major AI conferences. Moreover, research on AI algorithms and software systems is becoming increasingly tied to substantial amounts of dedicated AI hardware, notably GPUs, which leads to AI architecture co-creation, in a way that is more prominent now than over the last 3 decades. Related to this shift, more and more AI researchers work in corporate environments, where the necessary hardware and other resources are more easily available, compared to academia, questioning the roles of academic AI research, student retention, and faculty recruiting. The pervasive use of AI in our daily lives and its impact on people, society, and the environment makes AI a socio-technical field of study, thus highlighting the need for AI researchers to work with experts from other disciplines, such as psychologists, sociologists, philosophers, and economists. The growing focus on emergent AI behaviors rather than on designed and validated properties of AI systems renders principled empirical evaluation more important than ever. Hence the need arises for well-designed benchmarks, test methodologies, and sound processes to infer conclusions from the results of computational experiments. The exponentially increasing quantity of AI research publications and the speed of AI innovation are testing the resilience of the peer-review system, with the immediate release of papers without peer-review evaluation having become widely accepted across many areas of AI research. Legacy and social media increasingly cover AI research advancements, often with contradictory statements that confuse the readers and blur the line between reality and perception of AI capabilities. All this is happening in a geo-political environment, in which companies and countries compete fiercely and globally to lead the AI race. This rivalry may impact access to research results and infrastructure as well as global governance efforts, underscoring the need for international cooperation in AI research and innovation.
In this overwhelming multi-dimensional and very dynamic scenario, it is important to be able to clearly identify the trajectory of AI research in a structured way. Such an effort can define the current trends and the research challenges still ahead of us to make AI more capable and reliable, so we can safely use it in mundane but also, most importantly, in high-stake scenarios.
This study aims to do this by including 17 topics related to AI research, covering most of the transformations mentioned above. Each chapter of the study is devoted to one of these topics, sketching its history, current trends and open challenges.
To conduct this study, I selected a very diverse group of 24 experienced AI researchers, who generously accepted my invitation and devoted a significant amount of time to this effort. We all worked together between summer 2024 and spring 2025 to structure the study, define the main topics, discuss the content, comment and contribute to the various chapters. Additionally, some chapters engaged also with additional contributors who brought their expertise on a specific topic. The work was done mostly online, with monthly calls with all panel members plus additional calls for the team working on each chapter, with also in a full-day in-person meeting, held in January 2025.
However, we also wanted to include the opinion of the entire AAAI community, so we launched an extensive survey on the topics of the study, which engaged 475 respondents, of which about 20% were students. Among the respondents, academia was given as the main affiliation (67%), followed by corporate research environment (19%). Geographically, the most represented areas are North America (53%), Asia (20%), and Europe (19%) . While the vast majority of the respondents listed AI as one of their primary fields of study, there were also mentions of other fields, such as neuroscience, medicine, biology, sociology, philosophy, political science, and economics. This multi-field involvement was also reflected in an interest in multi-disciplinary research from 95% of the respondents.
Each chapter of this report includes a brief summary of the responses to questions related to the respective topic.
The work around the entire study has been generously supported and made possible by the amazing work of Meredith Ellison, AAAI Executive Director, and the AAAI office staff, who also prepared and delivered the survey.
I hope that this report will be useful to the whole AI research community. However, the report has been intentionally written in a non-technical way, to reach out to other audiences, including experts of other disciplines, policy makers, funding agencies, the media, and the general public. We all need to work together to advance AI in a responsible way, to make sure that technological progress supports the progress of humanity and is aligned to human values.
Francesca Rossi, AAAI President 2022-2025
Media Coverage of the Report
Nature Article: How AI can achieve human-level intelligence: researchers call for change in tack
Futurism Article: Majority of AI Researchers Say Tech Industry Is Pouring Billions Into a Dead End
New Scientist Article: AI scientists are sceptical that modern models will lead to AGI
CNET Article: Gen AI’s Accuracy Problems Aren’t Going Away Anytime Soon, Researchers Say
Gizmodo Article: AI Experts Say We’re on the Wrong Path to Achieving Human-Like AI
We Value Your Feedback
We invite any feedback about this report. If you’d like to share your thoughts, please use the form below.