Introduction

In an era where artificial intelligence (AI) is reshaping education and the workplace, equipping students with AI literacy from the start of their academic journey is more important than ever. Early exposure to AI tools, particularly prompt engineering, can empower students to harness technology effectively and responsibly.

The Benefits of Early AI Literacy

Personalized Learning

Adaptive technologies have transformed personalized learning by tailoring educational experiences to individual student needs, preferences, and performance. These tools dynamically adjust content delivery, pacing, and feedback based on learner data, promoting deeper engagement and improved outcomes. As Bayly-Castañeda et al. (2024) suggest that adaptive systems not only respond to learner input but also anticipate needs, creating a proactive and responsive learning environment. Walter (2024) then further adds that “AI’s role extends beyond traditional teaching methods, offering personalized learning experiences and supporting a diverse range of educational needs. It enhances educational processes, developing essential skills such as computational and critical thinking” (p. 15). This approach supports equity by accommodating diverse learning styles and fostering autonomy, especially for students who benefit from differentiated instruction. When integrated thoughtfully, adaptive technologies can empower learners to take ownership of their progress while instructors gain insights to guide targeted support.

Critical Thinking and Problem Solving

Teaching prompt engineering fosters critical thinking and problem-solving skills. According to Mollick and Mollick (2023) though, students must remain the “human in the loop” and learn to critically assess AI outputs (p. 3). This is something I stress in my classes each week as I interact with students. I know that some of them are using AI and when they use it as a replacement for their own thinking, it will often return an incorrect response. A great example of this is when I ask students to explain how they have been using one of the concepts in class this week. AI does not know what students are studying and it hallucinates and provides an answer that is inaccurate. It is a good learning experience because students begin to realize that AI cannot replace their thinking or complete their work for them. They must be the ones to review each output to make sure that what is being returned is accurate.

Future Career Readiness

The demand for AI skills in the job market is growing rapidly and early exposure to AI tools prepares students for future challenges. LinkedIn’s Workplace Learning Report (2025) identifies AI-related competencies such as prompt engineering, ethical AI use, and data literacy as among the top ten fastest-growing skills across industries. This trend suggests that students who develop AI fluency early will be better positioned to thrive in a tech-driven workforce. The World Economic Forum (2025) highlights how integrated this will be as it projects that 85 million jobs will be displaced by automation and AI, while 97 million new roles will emerge that align better with human-machine collaboration (p. 12). Ryan (2025) further emphasizes that AI literacy is the #1 skill employers are seeking in 2025, based on a survey of 1,000 hiring managers. It defines AI literacy as understanding how AI works and how to use tools like ChatGPT, Gemini, and Copilot effectively and ethically. It also discusses prompt writing as a critical skill. Students in most fields will be expected to exhibit proficiency in prompting and building agents to help them in the workplace.

Risks of Neglecting AI Education

Misuse and Overreliance

There are problems when students are not prepared to use AI. Low AI literacy can lead to ineffective prompts and poor academic outcomes. Folmeg, Feket & Koris (2024) argues that it

“is important that students learn and become aware of the limitations of ChatGPT and how to prompt well, otherwise they will receive too general texts. They must be somewhat proficient in the given topic, because the language model does not reject (sic) to answer even if it has no specific clues. It will still create a text that seems to be the best solution based on its knowledge but may be full of misleading information.” (p. 8)

 Walter (2024) also highlights that this “lack of training could lead to misuse of AI tools, as many students might not be aware of how to properly integrate these technologies into their academic work” (p.7). This is something that is common now with first year students. They will often simply put something into an AI and ask for the answer. It is not being used as a learning tool, but as a replacement for their own individual thoughts. By teaching students better prompting methods, it can encourage them to think not just about the prompt, but also the knowledge they want to gain from that exchange. When they begin to understand the benefits of a learning tool, my students have had an awakening to the possibilities of how they can not only learn about concepts in class but also gain more depth by using good prompts that explore these concepts.

Missed Opportunities

Without proper AI training, students miss out on potential benefits and face long-term academic and professional disadvantages. Cain (2024) warns that poor prompt design can lead to biased or misleading outputs. I talk about this above when I explore the “human in the loop” and I emphasize this every week as I provide a prompt for the students to explore and then discuss what they gained. I also encourage them to begin building their own prompts, asking for AI to help them when needed, and building their body of knowledge in this area. When they miss this opportunity in college, they may be less prepared for an AI integrated workplace. They also need to understand that, as Cain (2024) points out, large language models have biases and students need to be able to identify a bias as well as misleading for simply incorrect material being returned. When they use critical thinking and information literacy, they can use their prompt building skills to find more useful information while weeding out the bad.

Practical Steps for Implementation

Curriculum Design

Integrating AI literacy into first-year courses is at this point essential. Successful programs have demonstrated the value of early AI education. For instance, Walter (2024) advocates for embedding these skills early to foster critical thinking and prepare students for a tech-driven world. Walter (2024) states that “early adoption of AI literacy is crucial in preparing a generation that is not both adept at using AI as well as capable of innovating and leading in a technology-driven world (para 22). This is something that is on my wish list. Course developers have been exploring the idea now for some time and my wish is to see this in practice in the classroom. At least one part of an assignment each week should have a prompt building exercise that allows the students to explore concepts in class and also build their prompting skills. But how prepared are faculty to review and provide guidance?

Teacher Training

To answer the question above, many faculty still feel a bit ill at ease with AI and need resources and good training in order to bridge the gap in our own learning. This is not something that most faculty will have touched on as they worked on their degrees and bringing everyone forward is going to be a giant step not just for faculty but for course developers and administrators. Preparing educators to teach AI skills does seem to be the bottleneck in implementing needed changes. A global survey found that only 17% of faculty consider themselves proficient in AI (Hoffman, 2025). Many educators expressed skepticism, ethical concerns, and a lack of confidence in using AI tools effectively. According to Hoffman (2025) “Many university instructors lack the knowledge, support, and confidence to integrate AI into their teaching practices effectively” (para 1). Providing resources and support for teachers will help to ensure effective implementation, but this will rest with administration and training teams who are also grappling with the same learning curve.

Conclusion

Teaching AI prompting to first-year students is not just an educational innovation; it is a necessity. By addressing the benefits, risks, and practical steps for implementation, educators and institutions can prioritize AI literacy and prepare students for a future where technology plays a central role.

References

Bayly-Castañeda, K., Ramirez-Montoya, M.-S., & Morita-Alexander, A. (2024). Crafting personalized learning paths with AI for lifelong learning: A systematic literature review. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1424386

Cain, W. (2024) Prompting Change: Exploring Prompt Engineering in Large Language Model AI and Its Potential to Transform Education. TechTrends 68, 47-57. https://doi.org/10.1007/s11528-023-00896-0

Folmeg, M., Fekete, I., & Koris, R. (2024). Towards identifying the components of students’ AI literacy: An exploratory study based on Hungarian higher education students’ perceptions. Journal of University Teaching & Learning Practice, 21(6), 1–16. https://doi.org/10.53761/wzyrwj33

Hoffman, E. (2025, May 6). AI challenges: Alarming gaps in faculty training at universities. WINS Solutions. https://www.winssolutions.org/ai-challenges-training-gaps-universities/

LinkedIn Learning. (2025). 2025 Workplace Learning Report. LinkedIn Corporation. https://learning.linkedin.com/reports/workplace-learning-report-2025

Mollick, E., & Mollick, L. (2023). Assigning AI: Seven approaches for students, with prompts. arXiv. https://doi.org/10.48550/arXiv.2306.10052

Mzwri, K., & Turcsányi-Szabó, M. (2025). The impact of prompt engineering and a generative AI-driven tool on autonomous learning: A case study. Education Sciences, 15(2), 199. https://doi.org/10.3390/educsci15020199

Ryan, R. (2025, July 30). The No. 1 Skill Employers Want In 2025 And Most Job Seekers Don’t List It. Forbes. https://www.forbes.com/sites/robinryan/2025/07/30/the-no-1-skill-employers-want-in-2025-and-most-job-seekers-dont-list-it/

Walter, Y. (2024). Embracing the future of Artificial Intelligence in the classroom: The relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational Technology in Higher Education, 21(15). https://doi.org/10.1186/s41239-024-00448-3

World Economic Forum. (2025). The Future of Jobs Report 2025. World Economic Forum. https://www.weforum.org/reports/the-future-of-jobs-report-2025

Yu, S. (2024). Students’ prompt patterns and its effects in AI-assisted academic writing: Focusing on students’ level of AI literacy. ResearchGate. https://www.researchgate.net/publication/388377084#