A contract is uploaded or pasted into the interface. ChatGPT is asked to highlight risks, explain clauses or provide recommendations.
The motivation behind this is understandable:
The practical appeal is clear, but the legal reliability is not—especially given that large language models still hallucinate and remain opaque regarding the sources of their answers.
This raises a central question:
This guide explains:
ChatGPT can explain and rephrase complex text.
But contract review is not a linguistic task—it is a legal task involving structure, risk assessment and internal consistency.
To better understand the practical limitations, it helps to look at the core weaknesses.
ChatGPT does not work with a defined model of how a contract must be structured.
It does not know which components are mandatory, such as:
Unusual wording or non-standard formatting can be overlooked.
Its analysis results from statistical patterns, not legal structural logic.
👉 Legal structure review ≠ statistical text analysis.
Beyond the missing structure, generative AI lacks any legal evaluation framework.
It has no legally curated playbook.
It lacks:
ChatGPT generates generic descriptions based on training patterns.
It does not know what a complete or high-quality clause must contain—and cannot apply any quality standards.
Another major limitation: ChatGPT cannot evaluate the severity of findings.
Legal risk assessment depends on:
A language model knows none of these.
Therefore, ChatGPT cannot:
It may describe potential issues, but cannot judge how relevant they are.
A critical limitation:
ChatGPT cannot determine whether something is missing in a contract.
It can only analyse the text it sees.
It cannot identify:
Generative AI works descriptively—not evaluatively.
It can say what is present, but not what must be present.
Another structural issue: ChatGPT’s results cannot be reliably traced.
It cannot explain why something is risky.
It provides:
Its answers stem from statistical probabilities, not legal logic.
The output often sounds plausible—but cannot be verified.
A further critical aspect involves the handling of confidential data.
When contracts are uploaded or pasted into generic AI tools, the following typically happens:
Even when providers promise not to train on user data, key questions remain:
For confidential contracts—customer data, employee information, IP-related content or strategic agreements—this means:
Real loss of control and limited transparency.
Specialised Legal AI tools like Legartis address this directly:
Contract data is processed in controlled environments, with CH/EU hosting, contractual safeguards and no use for model training.
These methodological weaknesses are reflected clearly in a direct comparison.
In short:
➡️ Generative AI writes and explains.
➡️ Legal AI reviews.
Despite the limitations, ChatGPT can be a valuable helper for tasks such as:
Not suitable for:
For genuine contract review, organisations increasingly rely on specialised Legal AI systems, because they:
With Legartis, you can:
Discover a smarter way to review NDAs — free with Legartis.
ChatGPT is a powerful language model and useful for drafting or understanding contract language.
But reliable contract review requires more than linguistic ability:
It demands:
Generative AI cannot provide these. Legal AI like Legartis closes this gap. It combines legal expertise with technological precision—enabling structured, reproducible and secure contract review.