library(readxl)
library(plotly)
library(tidyverse)
library(htmlwidgets)Just a few years ago, most university students had never used generative AI. Today, tools such as ChatGPT are helping students explain difficult concepts, summarise readings, generate ideas and prepare assignments. What started as a new technology has quickly become part of everyday university life.
While AI offers many benefits, it also raises an important question: are all students benefiting equally, or is a new educational divide beginning to emerge? This visual story explores how students are using AI, why they rely on it, what concerns they still have and what these changes could mean for the future of higher education. Rather than asking whether AI belongs in universities, the story examines how students and institutions can learn to use it responsibly.
chart1 <- read_excel("C:/Users/Rujuta/Downloads/chart1.xlsx")
chart2 <- read_excel("C:/Users/Rujuta/Downloads/chart2.xlsx")
chart3 <- read_excel("C:/Users/Rujuta/Downloads/chart3_real.xlsx")
chart4 <- read_excel("C:/Users/Rujuta/Downloads/chart4_real.xlsx")
chart5 <- read_excel("C:/Users/Rujuta/Downloads/chart5_real.xlsx")p1 <- plot_ly(
chart1,
x = ~Year,
y = ~AI_Usage,
type = "scatter",
mode = "lines+markers",
text = ~paste("Year:", Year, "<br>Students using AI:", AI_Usage, "%"),
hoverinfo = "text"
) %>%
layout(
title = "AI adoption among students has become near universal",
xaxis = list(title = "Year"),
yaxis = list(title = "Students using AI (%)", range = c(0, 100))
)
p1AI adoption among university students has increased rapidly. HEPI’s student surveys show that the proportion of students using AI rose from 66% in 2024 to 92% in 2025 and 95% in 2026. This suggests that AI has moved beyond being a novelty and has become a mainstream part of student life. The speed of this growth creates a challenge for universities: students are already using AI, so institutions need to focus on guidance, literacy and responsible use rather than treating AI as an optional or future issue. Knowing that AI use has increased rapidly is only part of the story. The next question is how students are actually using these tools in their studies.
p2 <- plot_ly(
chart2,
x = ~Percentage,
y = ~reorder(Activity, Percentage),
type = "bar",
orientation = "h",
text = ~paste(Percentage, "%"),
textposition = "auto",
hovertext = ~paste(Activity, "<br>Percentage:", Percentage, "%"),
hoverinfo = "text"
) %>%
layout(
title = "Students use AI for different assessment tasks",
xaxis = list(title = "Percentage of students (%)", range = c(0, 100)),
yaxis = list(title = "")
)
p2Students are not using AI in only one way. The 2025 HEPI survey shows that students commonly use generative AI to explain concepts, summarise articles, suggest research ideas and structure their thoughts. These uses indicate that AI is being integrated into the learning process, not just used at the final stage of assessment. This matters because it shows AI can act as a study assistant, but it also raises questions about how much of the learning process is still being completed independently by students. Understanding how students use AI naturally leads to another question: why do they rely on it so heavily?
p3 <- plot_ly(
chart3,
x = ~Percentage,
y = ~reorder(`Reason for Using AI`, Percentage),
type = "bar",
orientation = "h",
text = ~paste(Percentage, "%"),
textposition = "auto",
hovertext = ~paste(`Reason for Using AI`, "<br>Percentage:", Percentage, "%"),
hoverinfo = "text"
) %>%
layout(
title = "The main attraction of AI is efficiency and support",
xaxis = list(title = "Percentage of students (%)", range = c(0, 100)),
yaxis = list(title = "")
)
p3The strongest reasons students use AI are practical. Many students use AI because it saves time, improves the quality of their work and provides instant support. This helps explain why adoption has grown so quickly. AI can provide help outside traditional study hours and can make support feel more personalised. However, this also creates a productivity paradox: the same features that make AI useful may also make students more dependent on it, especially when they are under pressure. Although AI provides many benefits, it is not without risks. Students themselves recognise several important concerns.
p4 <- plot_ly(
chart4,
x = ~Percentage,
y = ~reorder(Concern, Percentage),
type = "bar",
orientation = "h",
text = ~paste(Percentage, "%"),
textposition = "auto",
hovertext = ~paste(Concern, "<br>Percentage:", Percentage, "%"),
hoverinfo = "text"
) %>%
layout(
title = "Students remain concerned about misconduct, accuracy and fairness",
xaxis = list(title = "Percentage of students (%)", range = c(0, 100)),
yaxis = list(title = "")
)
p4Students are enthusiastic about AI, but they are not unconcerned. The 2025 HEPI survey shows that students are most discouraged by the risk of being accused of cheating and by the possibility of false results or hallucinations. Bias, institutional rules, data privacy and fairness also shape student behaviour. These concerns show that AI use is not simply a technology issue. It is also an academic integrity, trust and equity issue. Clearer guidance from universities is therefore essential. Looking beyond current university life, the final chart considers how AI skills may shape future careers and employability.
p5 <- plot_ly(
chart5,
x = ~Percentage,
y = ~reorder(`AI Future Readiness Indicator`, Percentage),
type = "bar",
orientation = "h",
text = ~paste(Percentage, "%"),
textposition = "auto",
hovertext = ~paste(`AI Future Readiness Indicator`, "<br>Percentage:", Percentage, "%"),
hoverinfo = "text"
) %>%
layout(
title = "Students value AI skills, but support has not fully caught up",
xaxis = list(title = "Percentage of students (%)", range = c(0, 100)),
yaxis = list(title = "")
)
p5The future divide is not only about whether students can access AI tools. It is also about whether they are supported to use those tools effectively. The 2026 HEPI survey shows that most students believe AI skills are essential to thrive, but fewer feel that teaching staff are helping them develop these skills for future careers. This gap suggests that universities need to embed AI literacy more clearly into teaching, assessment and career preparation.
One message stands out from this visual story: AI is no longer a future technology for university students—it is already part of everyday learning. Students are using it to save time, understand difficult concepts and improve the quality of their work, but they also recognise concerns around accuracy, fairness and academic integrity.
The real challenge is therefore not deciding whether AI should exist in higher education. Students have already embraced it. Instead, universities need to help students develop the skills to use AI critically, ethically and responsibly. Without this support, differences in AI literacy could create new educational inequalities.
Ultimately, the future of higher education will depend less on access to AI and more on the ability to use it wisely. Students who can evaluate AI outputs, question its limitations and integrate it into their own thinking are likely to be better prepared for an increasingly AI-driven workforce.
Freeman, J. (2025). Student generative AI survey 2025. Higher Education Policy Institute.
Stephenson, R., & Armstrong, C. (2026). Student generative AI survey 2026. Higher Education Policy Institute.
World Economic Forum. (2025). The future of jobs report 2025. World Economic Forum.
This visual story was created using RStudio, R Markdown, Plotly and the readxl package. Generative AI was used to assist with brainstorming, editing and troubleshooting code. All data analysis and interpretation were based on publicly available sources.The data values used in the charts were taken from the HEPI Student Generative AI Survey 2025 and HEPI Student Generative AI Survey 2026 reports.