Can AI Review Contracts Too?

How AI Transform Repetitive Legal Review

I recently had lunch with a team leader who has spent many years in game publishing. As we discussed AI in the industry, I asked where he typically uses generative AI. He replied:

“These days, I review a lot of contracts using generative AI. It’s made things so much easier.”

That one sentence inspired the topic of today’s post.

If you work in game business, you’ve likely faced repetitive tasks like reviewing publishing contracts, outsourcing agreements, NDAs, MOUs, or licensing terms.

These documents often contain dense legal language. Even after multiple reads, there’s always the worry that you might miss something important. You need to catch key points before sending them to legal— yet the process is tedious, and the risk of oversight is real. Some clauses are ambiguous. Others seem familiar but feel just different enough to raise concern.

Now, with the help of generative AI, reviewing legal documents can become significantly.

ℹ️ Can AI Really Draft Legal Complaints?

Yes. As of 2025, generative AI is already being widely used in the legal field.

AI can understand legal documents, summarize them, and even draft complaint documents.

One leading Korean law firm, “Daeryun,” introduced an AI-based system that automatically generates complaints, appeals, and legal responses. The process works as follows:

(1) The user enters a brief description of the case

(2) The AI interprets the details and extracts key legal elements

(3) It generates a draft in the appropriate legal format

(4) Relevant case precedents are automatically included

Below is an example of how the system produces both a draft document and related legal references.

Of course, a legal expert still needs to review the final version. However, AI significantly reduces the effort required to prepare the initial draft and helps clarify the meaning of complex legal content.

ℹ️ What About Game Contracts?

In the game industry, contracts are a routine part of the job. From publishing deals and outsourcing agreements to IP licensing and NDAs, these documents often include key business terms that require careful review.

Generative AI can make this process significantly more efficient. Here’s how it works in practice:

▶ Step 1: Upload the Contract → AI Automatically Detects Structure

Start by uploading the contract as a PDF or pasting in the text.

The AI recognizes the contract type (such as publishing, NDA, or outsourcing) and automatically highlights key sections like revenue sharing, termination clauses, and contract duration.

This step uses document preprocessing combined with LLM-based classification.

▶ Step 2: Summarize Key Clauses → Ask Questions Freely

The AI summarizes legal language into plain, easy-to-understand text.

You can ask direct questions like “What’s the payment schedule?” or “Who retains the IP rights?”

The AI pinpoints and explains the relevant clauses. This uses prompt engineering along with clause summarization models.

▶ Step 3: Detect Risky or Missing Clauses

The AI compares your contract to standard templates and flags potentially risky or missing terms.

Examples include unclear IP ownership, overly high termination penalties, or missing settlement terms.

This step combines LLM-based interpretation with automated benchmarking against standard agreements.

▶ Step 4: Compare with Previous Contracts

One of the most common questions during a review is: “What’s different from the last version?”

AI performs a side-by-side comparison using sentence similarity and diff highlighting. It clearly shows which clauses changed and what those changes might imply.

▶ Step 5: Retrieve Similar Cases

You can also ask, “How have other companies handled IP ownership in similar contracts?”

Using a RAG approach, the AI can pull similar past contracts or relevant case precedents for reference.

While this workflow involves multiple underlying technologies, this post focuses on the key elements needed to understand how legal AI supports contract review.

In addition to LLMs and RAG, two other important components are prompt engineering and NLP.

ℹ️ Why Is Prompt Engineering So Important When using generative AI?

To use AI effectively, how you ask matters. That’s the core of prompt engineering.

Prompt engineering is the practice of crafting instructions that guide large language models to generate accurate and relevant outputs. Think of a prompt as a precise direction— “Think this way. Answer like this.”

A well-structured prompt typically includes four components:

Instruction – What you want the AI to do (e.g., summarize, compare)

Context – Background or assumptions the AI should consider

Input data – The source text or question (e.g., contract text or a specific question)

Output format – The desired response type (e.g., bullet points, a summary, or a table)

Here’s a simple example:

“Explain the revenue share, termination clause, and IP ownership in this contract.”

This is a clear and focused request - enough for structural review.

Want to go further? Add a role assignment to help the AI take on a more expert mindset:

“You are a lawyer with 20 years of experience in the game industry. Review this publishing contract, compare it with standard industry practices, and highlight any potentially risky clauses — especially related to revenue sharing, termination, and IP ownership.”

Role-based prompts help the AI respond like a domain expert, which is especially useful when nuanced or contextual judgment is needed.

ℹ️ Why Is NLP So Important in Legal AI?

NLP is the core technology that enables AI to understand and analyze human language, crucial when interpreting legal documents.

Contracts involve not just complex sentence structures, but also implied meaning, responsibility, and legal intent. NLP allows AI to go beyond surface-level text to understand relationships between clauses, risk indicators, ownership & obligation and Legal context & tone.

Whether it’s clause interpretation, precedent matching, or flagging potential risks, NLP acts as the “thinking engine” behind legal AI.

ℹ️A Real-World Example…

♻️ Final Thoughts…

Thanks to the advancement of AI tools, game business professionals, including planners, PMs, live ops lead, and marketers, can now conduct an initial review of contracts faster and with more clarity.

But it’s important to remember: AI is an assistant tool, not a legal advisor.

While AI can help draft, summarize, and highlight key issues, the final judgment and legal responsibility must always rest with a qualified legal expert.

Some clauses may carry legal ambiguity, and AI may misinterpret the nuance. In most jurisdictions, including Korea, AI is not permitted to offer binding legal advice or act in the place of licensed attorneys.

So, think of AI as a supporting assistant—one that helps you work faster and make more informed decisions, but not one that replaces legal review.

⏩ Coming Up Next

Once the contract is signed, what comes next? Internal testing and QA.

In the next post, we’ll explore how AI can help streamline internal testing workflows and pre-launch review processes—all from the perspective of game business operations.

※ Disclaimer: This content reflects the author’s personal views and includes only publicly available examples. It does not represent the official position of any company mentioned