Creating visual presentations to effectively communicate information from experimentation, research, or data collection is vital to presenting findings. However, this process can be overlooked in the latter half of their research process. The founder of Gamma, Grant Lee, experienced this firsthand: “When you think about the traditional sort of presentation tools like slides, you’re often faced with this blank canvas—and the majority of us are not visual designers,” Lee said.” (J.P. Morgan, 2025). Students enrolled in university often need to create presentations, infographics, or slideshows. Instead of letting this process overwhelm them, with assistance from AI, students may now have the tools necessary to help visualize their data efficiently so they can focus on their research. To evaluate the impact these tools can have, this review will investigate the question: What steps need to be taken for GenAI to be effectively utilized to assist with visual presentation in a higher education environment? 

Although GenAI is a relatively new concept, it has already been shown to improve presentation quality. Balakrishnan cites a study. “...AI-enhanced PowerPoint presentations significantly improved student engagement and learning outcomes compared to traditional slides.” (Balakrishnan, 2024, p. 10). This shows how GenAI has already been implemented and is showing signs of improvement from the classic method of presentation creation. “....from automating content generation to personalizing learning experiences for students.” (Balakrishnan, 2024, p.10) shows an investigation into some of the aspects of GenAI that can put it above traditional PowerPoint creation processes. Plusai’s look into Gamma further supports this. “...the drag-and-drop system is quite intuitive. There are also great utilities, like if you need more graphics, there's direct access to sites like Unsplash and GIPHY inside Gamma.” (Daniel, 2025). In another instance, a study investigated how a GenAI platform called NB2 Slides can assist researchers in presenting their findings. “Almost all participants mentioned that one particular challenge of creating presentation slides is to customize for different target audiences,” (Zheng et al., 2023, p.6) suggests a common problem in creating visual presentations. This suggests that AI developers understand the difficulties of visual presentation creation “DR1: The AI system should customize output presentation slides for the different backgrounds (e.g., technical and non-technical) of the target audience.” (Zheng et al., 2023, p.7). This idea is further supported by an Elsevier article evaluating prompt engineering. “...recent studies have emphasized LLM, such as ChatGPT’s, capacity to enrich the educational experience by supporting a wide range of learning methodologies, including adaptive learning, personalized learning, and self-directed learning” (Knoth et al., 2024, p. 1-2). Grant Lee emphasizes that tools like Gamma will still grow, adding to its abilities and range of application. “Gamma continues to expand. “I’m excited on all fronts. The technology is advancing so quickly, and we’re just scratching the surface in terms of what the capabilities will be,” Lee said.” (J.P. Morgan, 2025). The idea being suggested is that not only is there a positive effect associated with the implementation of GenAI in visual presentations, but the development of these tools is focused on the experiences of real researchers and their ideas are being directly implemented as AI developers strive to improve their products. The already widespread usefulness of GenAI in educational settings is something that, if communicated correctly, could entice a wider audience to look into utilizing GenAI for their own needs as they would be able to understand the impacts it could and has had. 

A barrier to AI being used in higher education is a lack of awareness as to how these tools work. This sentiment is shared in an Elseiver article “As the future of education is expected to undergo significant transformation due to the widespread availability of powerful generative AI systems, it becomes crucial for non-experts to acquire the necessary skills, knowledge, and attitudes toward AI systems” (Knoth et al., 2024, p. 3). Schiff highlights how the policy on using AI in education is not common. “Most discussion addressing ethics and education was focused on Education for AI purposes, such as training future machine learning experts to develop ethical design skills, rather than addressing ethical implications emanating from AIED.” (Schiff, 2022) and it rarely even enters the conversation of AI policy “It finds that the use of AI in education (AIED) is largely absent from policy conversations” (Schiff, 2022). Similarly, a study by researchers at the University of Abuja found that lecturers in Nigeria were not comfortable using AI or did not know how “...lecturers were not proficient in utilizing PowerPoint slide presentation (PPT) tools…” (Olatunde-Aiyedun & Hama, 2023, p.9) and after receiving training the Nigerian lecturers felt more comfortable in creating presentations “...they tend to utilize PowerPoint Artificial Intelligent tools more effectively than before treatment.” (Olatunde-Aiyedun & Hama, 2023, p.12). This suggests the idea that AI is not being widely used to assist with presentations due to a lack of knowledge on how it is used. A trend becomes apparent as many researchers highlight an improvement in visual presentations as AI is implemented. If action were to be taken to introduce and teach the inner workings of AI tools more students or professionals would feel more comfortable using them for themselves. This is something our instruction set aims to fix by supplying college students with an overview of how a GenAI presentation tool works. Researchers have found a gap when it comes to providing the necessary education to utilize AI. Studies have shown that AI could be more prevalent if more people knew how to use it. To fill this it becomes necessary to find more ways to provide AI usage instruction 

The ethical and legal boundaries of AI are a major concern as AI becomes more prevalent. This can include data misuse or privacy violations. Some believe Facebook crossed this boundary with its use of deepfakes. “For example, in developing their ground-breaking DeepFace facial recognition technology, Facebook engineers used without explicit consent four million photographs of people…” (Tuomi, 2022), and related issues have caused some unease with the use of AI. “While, in Europe, there has been growing interest in developing teacher-oriented guidelines and regulations for the ethical development and deployment of AI…” (Tuomi, 2022). Concerns are arising over how AI is implemented and used, especially in education. Teachers also are at threat of being replaced by these tools “...recent advancements in non-invasive brain-computer interfaces and artificial intelligence are opening new possibilities to rethink the role of the teacher, or make steps towards the replacement of teachers with teacher-robots…” (Popenici & Kerr, 2017, p. 9). Though these are real fears, Popenici and Kerr highlight how research into AI understands these fears surrounding AI. “We also believe that it is important to focus further research on the new roles of teachers on new learning pathways for higher degree students.” (Popenici & Kerr, 2017, p.11) suggest that though the role of the teacher may change, it will still be important to the development of students. A paper from IEEE, the ethical concerns of AI that are also being tackled by the AI industry. “OpenAI's team has explored the potential applications of generative AI in generating misinformation and proposed strategies to counteract it.” (Baldassarre et al., 2025). This is further supported by a Plusai article highlighting how Gamma keeps the users' information secure: “Gamma uses several methods to protect users, such as HTTPS encryption, limiting access to customer info, and regular safety audits.” (Daniel, 2025). It is also important to highlight how AI is being used to identify legal issues in writing, like hate speech. “On the other hand, efforts also involve exploring how generative AI can be employed to combat hate speech.” (Baldassarre et al., 2025). Analysis of this information suggests that though the legal and ethical concerns of GenAI are present, actions are being taken to combat common issues associated with GenAI. This shows how these AI companies recognize the power and potential consequences of using AI and are actively trying to combat it. Communication of the action taken by AI developers to best protect common ethical boundaries is important so potential audiences of AI tools do not feel as though their values could be unintentionally violated through AI mistakes. 

Throughout this review the references investigated have provided critical insight into current research involving AI and education. The most current sources of information carry the most weight as they are based around the most up to date status of AI implementation and have the strongest overview of the effects of AI. This includes an article from IEEE and Elseiver. An article from J.P. Morgan is also current however it includes words from Gammas founder and J.P. Morgan is a key financial partner of Gamma which may suggest bias towards Gamma. The article from Plusai also may raise some concerns due to the fact that they have their own AI presentation software which may create bias against Gamma in favor of their own tool. Lastly, the article written by Popenici and Kerr may be limited due to it being written in 2017. While the content is excellent and it provides strong points to the intended argument of the article, it does not have the knowledge of the implementation of AI as it stands today. The remainder of the articles featured in this review are current and come from authors with extensive experience in education, AI, or similar research fields making their points and analysis trustworthy and insightful 

Based on our analysis, several important steps must occur for GenAI to be effectively utilized in higher education. First, the benefits and possibilities of using AI must be presented; not enough students know how AI may enhance their work, and this idea must be displayed and advocated for to educate students. Second, potential users must be educated on the tools. Evidence shows that simply providing education on how GenAI helps with visual presentations enables an improvement in presentation quality. The instruction set associated with our website aims to assist with this issue, and with more AI educators, GenAI could be added to more students' arsenal. Lastly, ethical concerns involving data or privacy misuse should be known and addressed. Students must be educated on the possible issues that arise while using GenAI but they must also be aware of actions being taken to mitigate these issues so audiences know AI can be trustworthy. If these paths are taken, GenAI has the potential to be widely used to transform research presentation in academics.