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AI in Higher Education and Employement

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Artificial intelligence (AI) is revolutionising higher education and employment, reshaping everything from student placement applications to academic integrity and recruitment processes. While AI enhances efficiency and expands opportunities, its increasing influence raises critical ethical, equity and governance challenges. How can universities and employers balance AI’s tools while maintaining fairness, inclusivity and human creativity? In this blog, I explore key concerns around AI in education and employment, including academic integrity, discrimination, self-regulation and digital equal opportunities.

AI’s Expanding Role in Placement Applications

AI is now integral to student placement applications. Platforms like LinkedIn and Glassdoor personalise job recommendations, while generative AI tools enhance CVs and cover letters (McCall & Allman, 2025). AI recruitment platforms even simulate interview scenarios, helping students prepare for industry-specific questions.

These images represent an abstract representation of AI. They show a robot with a human-like face holding a glowing brain-like object surrounded by interconnected a book, devices and code.

Although these advancements can enhance employability, they also present enormous challenges. Over-reliance on AI may lead to generic applications, where students fail to articulate their unique strengths, critical skills and personal experiences. Furthermore, AI job recommendations can create echo chambers, limiting students’ exposure to diverse industries and opportunities. As McCall and Allman (2025) highlight, students who depend solely on AI-generated job searches may miss valuable career paths that do not fit AI’s algorithmic predictions.

Integrity and Authenticity

A further concern with AI in student applications is the erosion of authenticity and creativity. While polished, AI-generated cover letters and resumes often lack the personal voice and self-reflection that employers value (Spehar, 2025). If students overly depend on AI tools to craft their applications, they may enter the workforce without developing essential skills such as critical thinking, problem-solving and self-awareness.

Spehar (2025) also observes that AI hiring processes introduce ethical risks, including potential biases in AI-based candidate screening. If students use AI to navigate AI recruitment, how much of the hiring process remains genuinely human? Universities must address these challenges by integrating AI ethics education into career services, ensuring students use AI as a support system rather than a substitute for personal effort.

Algorithmic Discrimination: Risks of AI Detectors in Academia

As AI tools become more prevalent in education, universities increasingly use AI detection software to verify student work. However, a problematic trend has emerged—non-native English speakers are flagged by AI detectors, leading to false accusations of academic misconduct (Mayers, 2023). AI detection tools are often trained on biased datasets, making them less reliable when evaluating writing from students with diverse linguistic and cultural backgrounds. This raises serious concerns about fairness, discrimination and the potential stigmatisation of non-native speakers (European Parliamentary Research Service, 2025).

If academic institutions rely on AI detectors without critical oversight, they risk penalising students based on assumptions rather than evidence. The challenge is deciding when AI is permissible and should be restricted. Should AI be removed from academic assessments, or should its use be standardised for all students? Without clear frameworks, the decision of “good” or “bad” AI applications remains subjective and inconsistent.

To ensure fair and inclusive AI governance in education, universities should:

  1. Reassess the validity of AI detectors, ensuring they do not disproportionately harm students from diverse linguistic and cultural backgrounds.
  2. Develop clear policies on AI use, deciding whether AI should be integrated responsibly into education.
  3. Promote AI literacy programmes, helping students understand how to use AI ethically and effectively in academic and professional settings.
  4. Adopt transparency in AI evaluations, requiring human oversight when AI detectors flag student work as potentially AI-generated.

Proactive AI Governance

As AI becomes an integral part of education and employment, organisations face a crucial decision: Should they take the initiative to establish internal AI ethical frameworks or wait for governments to enforce regulations? Many organisations including educational institutions and businesses are opting for self-regulation rather than waiting for legal mandates. This proactive approach prepares them for inevitable regulations, builds stakeholder trust, and demonstrates ethical responsibility.

However, self-regulation comes with challenges. Without clear legal frameworks, organisations risk inconsistent AI policies that may not align with future laws. Additionally, some institutions may adopt superficial ethical guidelines, leading to AI ethics-washing where organisations claim to use AI responsibly but fail to implement meaningful safeguards.

On the other hand, waiting for legislation to dictate AI governance can also be problematic. Regulatory bodies often struggle to keep up with AI’s rapid advancements, so laws may come too late to address pressing concerns such as algorithmic bias, transparency, integrity and data privacy.

A balanced approach is needed. Organisations should take early action in AI governance, focusing on transparency, fairness and inclusivity while remaining adaptable to evolving legal frameworks. International collaboration between policymakers, educators and industry leaders can help create coherent and effective AI governance models that promote innovation and ethical responsibility.

Another issue in AI career development is digital inequality. AI job search and application tools often require access to advanced software and AI literacy skills, which are not evenly distributed among students. Those from less privileged backgrounds may lack access to premium AI tools, placing them disadvantaged in an AI-dependent job market (McCall & Allman, 2025).

The Future of AI in Higher Education: A Balanced Approach

To fully prepare students for an AI workplace, universities should embrace a balanced approach that integrates AI literacy, ethics and critical thinking. AI should not replace human effort but rather be an enhancement tool that complements students’ individuality and professional growth.

As AI continues to shape higher education, the goal should not be to eliminate AI from student applications but rather to empower students to use it wisely, ethically and authentically. In doing so, universities can uphold their commitment to integrity, equity, and the development of truly independent graduates.

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