Why AI in Education?

The use of education technology (edtech) in schools is becoming more mainstream. Similarly, the use of AI, a technology that enables machines to perform tasks that typically require human intelligence, is becoming more mainstream in everyday life. Bringing the two together is a natural step that can benefit students, teachers, staff, and administrators.

AI can take many shapes and forms in education. Most recently, there’s a growing interest in generative AI (GenAI) tools that can create content and complete tasks in response to naturally phrased questions. These systems can personalize content, deliver near-real-time feedback, and guide coaching and skills development.

Incorporating intelligent AI technology into schools can also help teachers, staff, and administrators by automating repetitive or time-consuming tasks, freeing time to focus on enabling student success.

By the Numbers

Recent research on AI in education conducted by multiple institutions has found:

• 65 percent of educators want to deploy AI to improve learners’ outcomes.¹
• 20 to 40 percent of current tasks could be outsourced to technology.²
• 13 hours per week of a teacher’s time could be freed up by using AI for automating tasks.²
• 48 percent of educators say AI technologies have positively impacted the student learning experience.³
• 42 percent of teachers and students say that AI creates a more equitable system.³
• 73 percent of students report AI helps them study faster, and 67 percent of students report AI helps them study more efficiently.³

Benefits of AI in Education

AI in education offers a wide range of benefits that can help maximize time and efficiency, improve school and data security, provide data-driven insights, and enable valuable tools to improve learning. Some benefits include:

• Administrative efficiency: AI can automate routine tasks, improving efficiency and freeing teachers, administrators, and staff for higher-engagement activities. For example, AI can help teachers with grading, essay scoring, and attendance taking. It can also automate personalized messaging about events and schedules or assist with resource planning.
• Data-driven insights: AI analysis of data, such as student and class test and assignment performance, can yield unique insights for teachers and administrators. This insight can be used to improve curriculum, adapt instruction for personalized learning experiences, guide skills development, identify tutoring opportunities, and present new ways to guide and manage student learning. Feedback on student progress can also inform school district guidance about content development.
• Improved operations and safety: Campus operations on a school or district scale can benefit from harnessing AI. For example, AI-powered digital systems can detect facility or technology issues and problems proactively or in near-real time. Computer vision technologies and connected sensors can improve physical security via smart doors, fall detection, and smart gate access, among other uses. These capabilities can lead to increased efficiency and a higher level of safety and security campus-wide.
• Improved cybersecurity protections: Cyber threats continue to evolve, and the education sector is a prime target. For example, in 2023 known ransomware attacks against all levels of educational institutions increased by 105 percent.⁴ AI-assisted security technologies can help education IT teams proactively augment current security solutions to protect students, faculty, data, and operations from cyberattacks.

AI in Education Use Cases

Three types of AI are generally applied in educational environments to enable use cases for students, administrators, and campuses:

1. Reporting AI uses algorithms to analyze data and automatically generate reports. The three main advantages of AI reporting are speed, accuracy, and pattern identification. In education reporting, AI can help with student attendance, grade reporting, and resource optimization.
2. Reactive AI performs simple tasks based on a large quantity of collected data. It is the simplest form of AI and does not have the ability to form memory or use past experiences to form new output. It can be used for administrative automation and student assessment.
3. Predictive AI, using statistical algorithms, can identify patterns in past events or data collected and make predictions about future events. In education, it can be used for personalized learning or to detect students at risk of dropping out.

Use Cases

Examples of how AI can be applied in education include:

• Student engagement: AI in education can support language learning to bridge potential gaps in understanding. Students can prepare for tests through personalized AI-enabled applications. They can also learn from their peers and virtual exchanges in online discussion boards and through curriculum gamification.
• Attendance taking: Administrators and office staff can use AI to help track student attendance, record known or unplanned absences, or notify parents about tardiness.
• Classroom management: AI-enabled systems can help teachers monitor student activities, especially for personalized learning plans, group labs, workshops, or hybrid learning experiences. Teachers can see student progress more easily and have more time to support emotional-cognitive learning and behavior management as needed.
• Essay scoring: Teachers can use AI systems to review students’ essays as a first pass and check for grammar, sentence structure, and plagiarism. AI can also help determine whether students accurately understood their assignments and correctly followed a writing prompt.
• Student and class comprehension: Teachers have options for automatically determining student scores on tests, depending on the test-taking method. AI-enabled systems can help instructors identify general comprehension of certain subjects based on individual and collective scores on assignments and tests. This can inform lesson planning, how materials are presented in class, the creation of personalized learning plans based on individual knowledge gaps, or even curriculum changes to improve learning performance.
• Near-real-time notes: AI systems can help students with visual or auditory impairments by recording lectures and using speech-to-text technology. If students have trouble focusing in class because they’re busy trying to take notes, AI can create a transcript synced with an audio recording so students can go back and listen to or read what a teacher said at a specific moment. This also frees teacher time from providing lesson recaps and notes.
• Communication: It takes an ecosystem to support student education. Connecting parents, teachers, and administrators more efficiently can help improve the learning experience. From event scheduling to concerns reporting to recognition for student achievement and presentations, AI-enabled messaging and videoconferencing capabilities can facilitate access for communication among all stakeholders.
• Intelligent campus: AI systems can help monitor campus environments and provide valuable insights for administrators, visitors, and staff. For example, AI can collect student metrics for both on-site and digital class attendance. It can also be used to monitor pedestrian and traffic flow for usage patterns, identify potential on-campus safety hazards, and aid with smart parking, wayfinding, and crowd management. AI-enabled robots can be used in various ways to help with maintenance and facility management.

Challenges of AI in Education

As with the adoption of any technology, understanding how, when, and where to use AI in education must be a priority for today’s visionary educators and administrators.

As a foundation for AI in education, there must be a commitment to using responsible AI for transparency, accountability, inclusivity, and governance to support societal trust, critical thinking, and deep reasoning. Even so, there are scenarios that need to be considered for all AI initiatives in schools:

• Student misuse: The risk of students cheating raises ethical issues and undermines their ability to learn the necessary content and skills. Additionally, students may swap or forget their devices or password credentials, which can be a security risk.
• Bias in algorithms: AI systems learn from the data they are trained on. If this data contains biases like gender, ethnicity, and socio-economic segment, the AI system can learn and perpetuate those biases.
• Equitable access: Not all students have access to AI tools and the internet, with a risk that the digital gap may widen if access is not enabled for all.
• Decreased student engagement: There is a risk that students who spend more time with AI tools may engage less with educators and other students.
• Teacher burnout: The teacher device is the most used tool in the modern classroom for instruction, administrative tasks, and communication. At the same time, teacher burnout is leading to increased turnover and staff shortages. Providing AI-enhanced tools can help improve teacher satisfaction.
• Systems implementation: Upgrading existing infrastructure and devices for today’s technologies and future-proofing to be ready for tomorrow’s educational needs requires an investment of time and resources, including training personnel on how to use AI effectively.

Most of these risks are not new but should be considered through the responsible use of AI.

The Future of AI in Education

The nature of jobs is transforming significantly. By 2027, an estimated 83 million job roles globally—like bank tellers, postal service clerks, cashiers, and ticket clerks—will become obsolete as the employment landscape shifts.⁵ At the same time, projections show that about 69 million fresh opportunities will emerge in roles like AI and machine learning specialists, sustainability experts, and business intelligence analysts.⁵

Future Workplace Skills

The skills that will prepare students for that future workplace include analytical and creative thinking, resilience, flexibility, and agility. These abilities fall into categories like cognitive skills, working with people, self-efficacy, technology prowess, and management acumen. In response, education must adapt.

Students today need to be equipped to thrive with problem-solving capabilities, social-emotional competencies, the ability to collaborate effectively, and proficiency in technology design and programming. Real-world applications for this kind of knowledge include content creation (including video production), data visualization, and familiarity with working from anywhere.

Future Technology Requirements

AI-enhanced systems in education will gain momentum over the next several years, increasing the need for future-proofed devices that enable new levels of collaboration, productivity, and creativity and support the ability to run AI more efficiently and effectively. This is particularly important given the traditional four-year refresh cycle in education.

Security will also continue to be a top priority. Educational institutions must develop a security strategy that can withstand the challenges of a complex security landscape, protecting user and data privacy on student, teacher, and staff devices and networked infrastructure.

Educational institutions can take advantage of AI’s benefits today. Taking steps to incorporate AI now will set a foundation for more easily capturing emerging possibilities and use cases in the future.