Employers are hiring candidates who present well in interviews and submit highly polished written work, yet in some cases find that performance falls short shortly after employment begins.
The issue is no longer whether artificial intelligence is being used in job applications, but what happens when that use obscures real ability and any gap only becomes visible after the employment relationship has started.
Recent reporting suggests there is no clear collapse in graduate hiring. Students are continuing to enter the workforce and employers are still recruiting at entry level.
At the same time, career advisors have noted that AI is increasingly being used by candidates to produce resumes, complete written assessments, and prepare for interviews. This creates the potential for a disconnect between the quality of submitted work and a candidate’s underlying experience or capability, particularly where employers rely heavily on written outputs during the recruitment process.
Recent industry commentary also indicates that the use of AI in job applications is no longer occasional but increasingly common.
Platforms such as LinkedIn have highlighted the growing use of AI tools to draft resumes, cover letters, and application responses. Career advisors and hiring professionals have, in parallel, pointed to a recurring issue in which candidates appear highly capable on paper but struggle to explain or replicate that work in interviews or practical assessments.
The legal issue that follows is not whether the use of AI is permitted. It is whether legal exposure may arise when an employee is hired on the basis of work that does not reflect their actual competence.
In the United States, this question does not require new legal frameworks. It sits within established principles relating to misrepresentation, at-will employment, negligent hiring, and employer liability.
At the point of hiring, the relevant issue is reliance. Where a candidate presents work they did not meaningfully produce, or implies a level of competence they do not possess, an employer may argue that the hiring decision was based on a misleading representation.
In practice, such situations do not commonly lead to standalone legal claims, but they can influence the legal position that follows. In particular, they may strengthen the employer’s justification for early termination and shape how any dispute is assessed if the employment relationship ends.
Many employers rely on at-will employment to manage hiring risk, allowing termination without cause, subject to legal limitations such as discrimination or retaliation. While this provides flexibility, it does not remove all exposure.
Termination decisions that are inconsistent, insufficiently documented, or applied unevenly can still give rise to claims. The use of AI in the hiring process may add complexity, particularly where employers have not clearly defined expectations around candidate outputs or acceptable use of such tools.
A more immediate issue may arise where performance does not match expectations. Employers may encounter situations in which new hires are unable to reproduce the standard of work presented during recruitment, struggle to explain their reasoning, or rely on AI in ways that conflict with internal policies. In these circumstances, employers typically move into performance management processes or consider termination.
Legal risk can develop where those processes are not handled carefully. Employers that act without clear documentation, fail to set expectations, or apply standards inconsistently may face disputes relating to fairness or policy enforcement.
The presence of AI does not alter the underlying legal framework, but it may increase the likelihood that questions arise about how hiring decisions were made and how performance issues are addressed.
The more significant exposure, however, may sit with the employer rather than the individual employee. If an underqualified hire produces defective work, contributes to financial loss, mishandles data, or is involved in regulatory breaches, liability will not necessarily rest solely with that individual. Under established principles of vicarious liability, employers may be held responsible for actions taken within the scope of employment.
In such cases, the focus may shift away from the employee’s performance and toward the employer’s systems and decision-making. Questions may arise as to whether reasonable steps were taken to assess competence before hiring, and whether appropriate supervision or controls were in place. In more serious scenarios, this could engage concepts such as negligent hiring or supervision, depending on the circumstances and applicable state law.
The underlying issue is not the use of AI itself, but the extent to which employers rely on outputs that have not been independently tested or verified before being used in a commercial or regulated context. Once work produced by an employee is relied upon externally, any gap between perceived and actual competence may carry practical and legal consequences.
This dynamic may be reinforced by broader changes in hiring practices. AI can make it easier to produce structured and persuasive written outputs, while traditional methods of assessing practical capability such as internships, extended interviews, or work-based testing, may not always be as consistent or widely available. As a result, some employers may place greater weight on presentation during recruitment than on demonstrable performance.
The consequence is a potential gap between perceived competence and actual ability. Where that gap affects business outcomes, it may become a source of legal and financial exposure.
For employers, this suggests a need to review recruitment processes, including how candidate skills are assessed and how the use of AI is addressed in hiring and internal policy. Greater emphasis may be placed on practical testing, verification of capability, and clear expectations around performance.
For graduates, the position remains unchanged in one key respect. The use of AI may assist in accessing opportunities, but it does not reduce the requirement to perform once employed. Where expectations are set at a certain level during recruitment, employers may reasonably expect that level to be met in practice.
The graduate job market has not fundamentally contracted, but the conditions under which candidates enter it continue to evolve. Where there is a mismatch between what is presented during hiring and what is delivered in practice, that issue may extend beyond recruitment and become a point of legal exposure, particularly for the organisations that rely on those hiring decisions.