Abstract
This commentary discusses Robinson et al. on integrating artificial intelligence (AI) proficiency into undergraduate psychology curricula. It supports the argument that AI literacy and fluency are essential for graduate employability, a position aligning with APA and EFPA guidelines. Authors highlight opportunities such as enhanced learning, innovation and reduced digital inequities. But also discuss challenges, including academic integrity threats, reduced critical thinking, and ethical concerns. In the commentary, additional practical barriers are identified, including faculty training gaps, curriculum overload, infrastructural inequalities and rapid technological change. While integration is necessary, successful implementation requires careful planning, institutional support and ongoing adaptation to evolving educational and technological contexts
Introduction
In their paper, Robinson et al. (2026) put forward a compelling argument that artificial intelligence (AI) proficiency should be purposefully integrated in undergraduate psychology curricula, in order for psychology graduates to remain competitive and employable in contemporary labour market. The rise of AI is viewed as presenting a transformative opportunity to increase the value, relevance and marketability of the psychology bachelor’s degree. AI proficiency, in terms of both literacy and fluency, is an essential skill that must be cultivated and developed to support graduates’ future careers. The European Federation of Psychologists’ Associations (EFPA), in response to the rapid rise of technology, launched a Digitalisation Expert Reference Group in 2024, comprised of members with expertise in AI, experiential technology, communications and social media technologies. The Digitalisation Expert Reference Group argues that the rise in interaction with technology has many benefits but also presents several challenges. Six priorities have been identified as principles to underpin societal engagement with advancing technology, one of which is digital literacy and accessibility. The group notes that digital literacy for the public as well as for psychologists should be promoted, and suggests that curricula and standards should include relevant digital skills (EFPA, n.d.), a position shared by Robinson et al. (2026) in their paper.
Opportunities and Challenges in Integrating AI in Psychology Curricula
The authors begin their paper referencing the American Psychological Association's (APA) Board of Educational Affairs (BEA), which concluded that AI should be embraced by educators as a critical educational tool. They also make an important distinction between the two components of AI proficiency: AI literacy and AI fluency. Whereas AI literacy includes foundational understanding, such as how AI works, its capabilities and limitations, how to interact with AI tools ethically and recognising how AI can affect cognition and behaviour, AI fluency has to do with more advanced skills. These include using AI for innovation, data analysis and integrating it into complex tasks.
Through a thorough review of available literature, the authors point to both opportunities and challenges of deliberately incorporating AI proficiency development in undergraduate psychology curricula. Opportunities include the reduction of digital inequities, the generation of unique ideas, learning enhancement, bringing innovation to the classroom and modelling the thoughtful and ethical integration of AI into higher education. Challenges include discouragement of original thought and work an increase in dishonesty and cheating, and a negative effect on academic integrity and quality of student work. Perhaps the most feared challenge is the replacement of critical thinking, a potential danger that I also agree with. The solution to this, however, is not to ban AI (or expect students and faculty not to use AI) from universities, but rather to educate students and faculty on AI's potential and capabilities as well as its ethical and “smart” use. The focus should be on supporting the development of critical thinking and transferable skills in an AI-driven area. I fully agree with the authors’ statement that banning AI is not a sustainable long-term solution. This would be an unrealistic expectation because it ignores the reality of the rapid expansion of AI and the existence of readily available and easy to use applications for generative AI, and it also leaves students unprepared for the realities of the contemporary AI-driven competitive labour market.
Rightly so, authors postulate that professional responsibility necessitates staying current and integrating AI as a purposeful and necessary component of student education, incorporating it throughout the curriculum. To support their argument, they conclude their paper by giving examples of how AI proficiency can complement three existing APA frameworks:
APA Guidelines for the Undergraduate Psychology Major 3.0 (APA, 2023a) APA Principles for Quality Undergraduate Education in Psychology (APA, 2023b) The Skilful Psychology Student (Naufel et al., 2018)
Despite the strong case for curricular reform, we should, however, not downplay or ignore the practical challenges of such an endeavour as these can complicate the widespread implementation of an AI-integrated psychology curriculum. More specifically.
Gaps in Faculty Training and Limited Expertise
While the authors offer examples of how psychology programmes can incorporate AI proficiency development, less attention is devoted to the reality that many faculty members lack the AI knowledge necessary to teach and support the development of these competencies. A recent scoping review (Prégent et al., 2025) concluded that AI has potential to enhance learning outcomes but its successful integration requires addressing ethical, technical, and pedagogical barriers, and its responsible and effective use requires focusing on AI literacy, faculty development, and institutional policies. Training faculty is therefore imperative, and a necessary prerequisite for AI proficiency development in psychology students.
Curriculum Overload and Feasibility Constraints
Undergraduate psychology curricula are already overloaded with theoretical, methodological, and applied courses. Adding separate courses on AI proficiency would further burden the curriculum. Portocarrero Ramos et al. (2025), in their study on AI skills and the employability of university graduates, highlight the necessity for a reform of existing educational models. They found that 87% of graduates believed that AI should be a structural component of all university programmes, pointing to the reality that it has now become a social requirement that has implications concerning equity, access to employment and educational justice. It is therefore necessary to redesign programmes to incorporate the development of AI proficiency – which poses a challenge for higher education institutions, complicates accreditation procedures and requires time, consensus and resources.
Ethical and Academic Integrity Concerns
This paper acknowledges important concerns related to ethics and academic integrity. These include plagiarism, over-reliance on AI and reduction of critical thinking. Broader scholarship documents similar concerns by faculty, such as fears about ethical use, data privacy, and fairness in AI. For example, Francis et al. (2025) posit that while generative AI offers substantial benefits in terms of automation and efficiency, careful integration is needed in order to avoid discouraging authenticity in students’ work and exacerbating existing inequalities.
Furthermore, Mulaudzi and Hamilton (2025) recommend that higher education institutions train lecturers and students alike on the ethical use of AI, support transparency in AI-assisted academic work, and invest in technologies that would facilitate the above. They also postulate that institutions must revise assessment strategies so that they are more innovative to mitigate misuse and over-reliance on AI. Consequently, any discussion on AI proficiency integration in psychology curricula should consider, in addition to innovative pedagogical methodologies, assessment strategies that promote the development of critical thinking and moderate AI misuse, as well as responsible use of AI in assessment.
Inequalities in Access and Biases
Access to stable technologies, updated digital tools and secure data environments is imperative in order to accomplish a successful integration of AI in higher education curricula. Risks to equitable implementation should be taken into account, for example by higher education institutions that have fewer resources, as well as for students with limited digital access that can be disadvantaged. Francis et al. (2025) also mention potential biases in the training data that may reflect and perpetuate existing inequalities, for example the underrepresentation of contributions by scientists from historically marginalised groups.
Rapid Technological Change
AI and its capabilities evolve at a rapid pace, much faster than traditional academic programme review cycles (which take place every few years). What is implemented in one academic year in relation to AI resources or teaching and assessment methodology incorporating AI may become obsolete or irrelevant the next academic year. I came to a strong realisation when researching articles in preparation for writing this commentary. Articles published more than 2 years ago are already outdated when discussing, for instance, the capabilities of systems, or the perceptions of teachers and students on AI use. Consequently, curriculum designers face a challenge to ensure that what and how it is taught remains relevant. This is why continuous professional development, training and upskilling of faculty is essential.
Conclusion
In conclusion, Robinson et al. (2026) provide a timely and persuasive vision for integrating AI proficiency in the psychology curriculum. The authors effectively demonstrate that AI proficiency (literacy and fluency) aligns with APA's existing educational frameworks and that psychology, a discipline whose foundations lie in understanding human behaviour, ethics, and cognition, is positioned favourably in leading responsible AI integration in higher education. I am in agreement with its foundational argument: Psychology graduates need AI-related competencies to remain competitive in the labour market and thrive professionally, and psychology educators should and can lead in shaping the ethical and effective use of AI tools. At the same time, substantial practical challenges should also be considered, especially in relation to faculty training needs and readiness, infrastructure inequalities, curriculum constraints and ethical complexities. Moreover, how can we keep up to date in our teaching and assessment methods when the technology and tools are evolving more rapidly than we can follow? And when will the job market needs change almost as rapidly? All the aforementioned challenges must be considered and confronted in order to accomplish the successful integration of AI into psychology curricula in contemporary university settings and constitute psychology graduates relevant, skilful and confident in an exceedingly competitive labour market.
Footnotes
Funding
The author received no financial support for the research, authorship, and/or publication of this article.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.