How Contract Cheating and AI Ghostwriting Threaten Academic Integrity

Academic integrity has depended on one fundamental principle: students should submit work that genuinely reflects their own understanding, learning and effort. While traditional forms of misconduct such as plagiarism remain a concern, the rapid adoption of AI tools has introduced new challenges for educators and universities.

Among the most significant are contract cheating and AI ghostwriting. Both result in students submitting work that is not entirely their own, they differ in how the work is produced and the challenges they present for institutions.

Understanding these practices is essential for developing policies that promote responsible AI use, encourage student ownership, and preserve the value of academic qualifications.

What is contract cheating?

Contract cheating occurs when a student asks another person to complete academic work on their behalf. This may involve paying commercial essay-writing services, hiring freelancers, asking friends or family members to write assignments, or outsourcing projects through online platforms.

Unlike plagiarism, where copied material may be identifiable, contract cheating often results in original content written specifically for the student. Because the work is unique, traditional plagiarism detection tools may not identify it.

Example:

A student hires an online service to complete a research paper and submits it under their own name without contributing to the research or writing process.

What is AI ghostwriting?

AI ghostwriting refers to the use of AI tools to create few segments or entire assignment that is then submitted further to educators.

Students may ask AI systems to draft essays, solve case studies, summarize research, humanize it or answer assignment questions with little or no meaningful revision.

Unlike responsible AI-assisted writing, where students actively develop, review, and refine their work, AI ghostwriting replaces much of the student’s intellectual contribution.

Example:

A student enters the assignment prompt into an AI tool, copies the generated essay with minimal edits, and submits it without verifying facts or acknowledging AI assistance.

Contract cheating vs. AI ghostwriting

Although both practices raise academic integrity concerns, they differ in several important ways.

Both practices reduce opportunities for genuine learning and make it difficult for educators to accurately assess student understanding.

Why are these practices increasing?

Several factors contribute to the growth of contract cheating and AI ghostwriting.

Increased accessibility

Essay-writing services and AI tools are easier to access than ever before. Students can obtain completed assignments within minutes or commission custom work through online platforms.

Academic pressure

Deadlines, workload, and performance expectations can lead students to seek shortcuts when they feel overwhelmed.

Unclear institutional guidance

As AI technologies evolve, students may be uncertain about acceptable and unacceptable uses of AI. Without clear policies, some may unintentionally cross academic integrity boundaries.

Lack of confidence

Students who struggle with writing, language proficiency, or research skills may view outsourcing or AI-generated content as a solution instead of seeking academic support.

How contract cheating and AI ghostwriting affect academic integrity

The impact extends beyond individual assignments.

They undermine authentic assessment

Assessments are designed to measure student learning. When work is completed by someone or something else, educators cannot accurately evaluate knowledge or skills.

They limit skill development

Research, critical thinking, problem-solving, and communication skills develop through active participation. Outsourcing academic work reduces opportunities to build these essential competencies.

They weaken trust

Academic integrity relies on trust between students, educators, and institutions. When authorship is uncertain, confidence in assessment outcomes and qualifications may be affected.

They create fairness concerns

Students who complete their work honestly may be disadvantaged when others receive similar grades despite contributing significantly less effort.

Looking beyond the final submission

Traditionally, institutions have focused on reviewing completed assignments. However, AI-assisted work has highlighted the importance of understanding how an assignment was developed not just its final form.

The writing process often provides valuable context that a finished document cannot.

Examples of useful process signals include:

• A consistent record of drafting and revisions
• Evidence of student engagement throughout the writing process
• Gradual development of ideas and arguments
• Meaningful revisions following feedback
• The ability to explain sources, decisions, and reasoning behind the submitted work

These signals should not be viewed as proof of misconduct. Instead, they provide additional context that helps educators make informed academic integrity decisions.

Solutions such as DocuMark provide visibility into writing history, revisions, and student engagement throughout the assignment process, enabling institutions to understand how work evolves rather than relying solely on the final submission.

Preventing contract cheating and AI ghostwriting

Addressing these challenges requires a balanced approach that combines policy, education, and transparency.

Institutions can strengthen academic integrity by:

• Establishing clear policies for responsible AI use
• Teaching students when and how AI can be used appropriately
• Designing assessments that encourage original thinking and reflection
• Supporting students with writing and research resources
• Encouraging transparency about AI assistance where appropriate

Rather than focusing only on identifying misconduct, institutions can create learning environments that reduce the motivation to outsource academic work.

Supporting evidence-based academic integrity

As AI becomes a regular part of education, academic integrity practices must evolve alongside it. Reviewing only the final submission may not always provide enough context to understand authorship or student engagement.

By considering the writing journey alongside the completed assignment, educators can have more informed conversations about learning, responsibility, and appropriate AI use.

DocuMark supports this process-focused approach by providing insights into writing development, revision history, and evidence of student engagement. These insights help institutions evaluate academic work more holistically while recognizing that educator judgment remains central to every academic integrity decision.

Conclusion

Contract cheating and AI ghostwriting present different challenges, but both can weaken the connection between assessment and authentic learning. As educational technologies continue to evolve, institutions need approaches that emphasize transparency, responsible AI use, and evidence of student learning.

Rather than relying solely on the finished assignment, understanding how academic work develops enables educators to intervene earlier, support students more effectively, and promote a stronger culture of academic integrity.

With DocuMark, institutions can complement existing academic integrity practices by gaining greater visibility into the writing process, helping educators focus on meaningful evidence while fostering trust, accountability, and student ownership in an AI-assisted learning environment.