The Dangers of Using AI For Employment Agreements
I’ve been seeing a growing pattern over the past year.
Business owners are under continuous pressure to move quickly and control costs. When hiring a new employee, it can be tempting to ask an AI platform to generate an employment agreement or offer letter in a matter of seconds rather than spending time and money obtaining legal guidance.
On the surface, the result often looks impressive. The document is organized, uses legal terminology, and appears comprehensive. To a business owner who does not routinely review employment agreements, it may seem indistinguishable from something prepared by an attorney. Even to business owners who do, circumstances arise that are different than those they have seen in the past.
The problem is that employment contracts are not simply collections of legal clauses. They are strategic documents designed to allocate risk, preserve flexibility, protect business interests, and comply with applicable law. A contract can appear polished while still creating significant legal exposure.
Why AI Gets Contracts Wrong
AI is trained to predict language, not evaluate legal risk. It does not interview the employer, understand the business model, evaluate state-specific laws, or identify the competing goals that must be balanced in an employment relationship. As a result, it often produces contracts that sound legally sophisticated but fail to accomplish the employer's actual objectives. And, as a lot of business owners in growing numbers are realizing too late, the challenges with these AI-generated contracts usually tend not to reveal themselves until the relationship ends.
A handful of clients have come to me over the past few months after these types of “contracts” have already done their damage. Here are a few real-world scenarios I’ve had to step in and address after the fact.
Real-World Scenarios
Example 1: The “At-Will” Agreement That Was Never At-Will
One client hired a key employee using an AI-drafted employment agreement. They believed they had an at-will relationship with the employee, as they always had with prior staff.
However, the contract included detailed termination language stating the employee could only be terminated for “cause,” defined broadly as performance issues, failure to meet expectations, or misconduct. When the relationship ended during a business restructuring, the employee relied heavily on that language and alleged wrongful termination and breach of contract.
I was asked to review the agreement after the dispute escalated. Unfortunately for the employer, this contract unintentionally gave job security to this employee; the “for cause” language effectively displaced the at-will presumption that is inherent in most employment relationships.
What went wrong? AI combined standard employment concepts without recognizing that adding a detailed termination standard often overrides at-will status in practice. Although the employer's goal was flexibility, the contract actually accomplished the opposite. A carefully drafted agreement would have preserved the at-will relationship while still addressing performance expectations and termination procedures.
Example 2: The Noncompete That Created More Risk Than Protection
Another client came to me after using an AI-generated employment contract that included a sweeping noncompete clause. It barred the employee from working in the same industry anywhere in the United States for two years after separation.
To the business owner, this looked protective and reasonable. In reality, however, it was almost certainly unenforceable under modern restrictive covenant standards and state-specific limitations. More importantly, when the employee left and the employer attempted to enforce other parts of the agreement (including confidentiality obligations), opposing counsel used the overbroad noncompete as part of a broader argument that the entire agreement reflected overreach and poor drafting judgment.
Ultimately, I was asked to restructure their agreements going forward to separate enforceable confidentiality protections from overly aggressive restrictive covenants.
What went wrong? Depending on the prompts, AI tends to generate “maximum restriction” language without regard to enforceability or credibility in practice, which can cause significant harm to a business owner in litigation or negotiations upon an employee’s departure.
Example 3: Contractor Language That Created Wage Exposure
In another matter, a client engaged a worker as an independent contractor using an AI-generated agreement. The contract labeled the individual as a contractor, paid a flat monthly fee, and stated they were exempt from overtime.
After the relationship ended, the worker filed a wage claim arguing they had been misclassified and were entitled to overtime and penalties.
When I reviewed the arrangement, the contract language was not aligned with how the relationship actually functioned day-to-day. The agreement had created a narrative that didn’t match the legal classification analysis under wage and hour standards. Although there was no way to turn back the clock and handle things the right way for this particularly “contractor,” we ultimately managed future exposure by restructuring their onboarding practices to ensure future contractor relationships were properly documented and operationally appropriate.
What went wrong? AI can draft labels, but it cannot apply the legal multi-factor tests that determine employee vs. contractor status. The contract attempted to define the relationship through terminology rather than substance. However, worker classification is determined by the realities of the working arrangement, not by the label placed in the agreement.
The Core Issue: AI Drafts Language But Doesn’t Allocate or Mitigate Risk
The common thread in these situations is not that the contracts were “badly written.” They covered all of the topics that the employers asked for in their prompts.
The problem was structural:
Inconsistent clauses that unintentionally changed legal meaning
Overbroad protections that undermined enforceability
Misalignment between contract language and actual working relationships
Failure to account for state-specific employment law
No integration of risk strategy across provisions
Employment agreements are not just documents to “have in place.” They are frameworks that determine what happens when things don’t go as planned.
AI can be helpful for brainstorming or drafting starting points. However, employment contracts require more than just drafting or templates—they require judgment about enforceability, structure, and how terms interact in real life disputes.
To Ask Yourself
Before relying on an AI-generated employment agreement, I encourage you to ask yourself:
Does this agreement comply with the laws of the state where my employee works?
Does it preserve at-will employment if that is my intent?
Are restrictive covenants likely to be enforceable?
Does the contract accurately reflect the actual working relationship?
Have I considered how the agreement will be interpreted if the relationship ends poorly?
Take Away
AI can be a useful tool; I use it in my own practice. But there is a significant difference between generating contract language and evaluating whether that language advances a business owner's goals while reducing legal risk.
Employment agreements are often signed at the beginning of a working relationship and forgotten until a dispute arises. By that point, it is too late to fix drafting decisions that could have been addressed from the outset.
Taking the time to review contracts, policies, and employment practices before problems arise is almost always less expensive than addressing disputes after the fact.
