Have you ever felt like you are submerged by all of the requirements that you have when searching for the best research paper? You’re definitely not alone; there are so many pieces of literature available that it can turn what should be a relatively easy search into weeks or months of working through useless abstracts and databases. Fortunately, modern technology provides researchers, students and curious people with new ways to help them locate research papers. Using artificial intelligence (AI) to locate research papers is as practical and impactful as ever and provides solutions to managing the burden of too much information and finding exactly what you need! Think of traditional search methods as searching for a specific star in the Milky Way by just looking at it with your own eyes – mostly a lot of guesswork and a lot of searching. With a sophisticated telescope, if you had one that could point right to your star, provide you with other connected constellations, give you the names of the celestial bodies that were nearby, and show you how and when the star was discovered, that would be very different than using traditional search methods. The difference when you use AI for finding research papers is that those tools are not just keyword matching tools, but they are able to understand the context in which the words and phrases are used, their meaning, and how they relate to the various concepts and ideas. They are able to learn from your user interaction with those tools, thus refining the results of what they provide for you to align with your changing research needs. This type of intelligent finding of research papers removes the time-consuming manner in which one found research papers before to create an efficient, if not enjoyable, finding process. The ability for AI to interpret natural language is one of the most notable benefits of relying on it to search for research papers. As a result, you can no longer develop extremely intricate Boolean search strings that contain combinations of AND, OR, and NOT. Rather than performing these actions, you can now go to AI and ask it a question as though it were your enabling coworker. For example: “What are the newest studies on climate change and urban development that include a cross-discipline approach?” or “Utilize the search terms given above to discover the articles that question the design of this specific study from 2018.” AI processes this question, understands the key principles, and searches its database of research papers, which will frequently include preprints, institutional repositories, and all the databases of the major publishers, to produce a specified list of the best articles. This capability of semantic searching allows you to find articles that would not have been found through searching for the standard keywords because they used other words to describe the same concept. In addition, the research process doesn’t stop with a list of results. There are also sophisticated AI platforms that provide a recommendation engine for finding relevant academic papers. After you select one of your chosen papers, these platforms will be able to provide you with a dynamic/interactive map of the academic conversation around that paper through their ability to generate lists of papers that are either “similar” or have “cited” that particular paper. These platforms will also allow you to identify the key authors in a field, to trace the development of a theory, as well as to identify emerging trends and key works you should be aware of. The features offered by these platforms are critical to conducting your literature review, so that you will be able to have a comprehensive understanding of the body of research on a specific topic without fear of missing a significant piece of the puzzle. In essence, it’s like having a guide who knows every path in the woods as well as can predict where new paths are being established. Not only do AI tools assist with discovering researchers’ publications, they are completely changing the way in which we interact with our findings. We know that reading several technical publications that include complicated subject matter is incredibly exhaustive. AI has emerged as an excellent resource for processing these materials. For instance, many AI tools now have the ability to summarize long publications into a condensed abstract form that includes the abstract, methods, results, and conclusion. There are also AI tools that have the ability to provide a listing of any figures, tables, or datasets in a publication, thereby allowing users to compare them quickly and easily. Other tools provide an indication of the general sentiment of the research as well as identifying any gaps or deficiencies. Thus, the ability to work with all of the information that we receive has changed. Research was previously limited to spending hours determining if a specific publication warranted a comprehensive review. Now, thanks to AI technologies, we are able to review large batches of publications, thereby allowing us to utilize our time and energy to focus on those documents that we believe to be the most relevant. Therefore, the process of utilizing AI to identify research materials continues into utilizing AI to assist with understanding such research materials more quickly and effectively. Adopting this technology is certainly going to involve a thoughtful process. A major factor to consider is the “black box” problem—often we cannot understand why the system selected the papers it recommends. Scholars have to keep exercising their ability to analyze; they can use the lists produced by AI systems as the place to start for academic review as opposed to the ultimate answer. Additionally, using biases in training data or having access to paywalled material still creates major issues. Researchers should seek to use AI to help them discover research papers, acting as a supporting tool alongside human judgment and curiosity; thus we are creating collaboration between machine efficiency (scalability and speed) and human insight (depth, context and critical thinking). The world of academic research is in a period of great evolution and excitement. Gone are the days of stumbling through irrelevant search results and struggling through a clunky, cumbersome research process; these tools have changed dramatically over time and will continue to evolve and improve. As these tools become increasingly integrated and personalized, they will help democratise access to knowledge and speed up the pace of research throughout all disciplines. Therefore, when you are faced with a research challenge in the future, remember that you are not alone, there are better, smarter ways to approach the task that you are facing. When you use AI to search for research papers, you are not just conducting a search for research papers, but also participating in a very deep and interactive conversation with the entire history of all published academic work, and leveraging the insights you uncover will allow you to advance your own research agenda. It is a truly remarkable way to turn information overload into manageable knowledge.