Contract AI: Ways to Simplify Your Workflow

You’ve heard the buzz about how AI is reshaping contract processes. Yet, you’re on the fence, wrestling with questions like: Does investing in contract AI tools pay off? Does the technology live up to the hype? And what about the risks?

Contract AI isn’t a magic wand, but it offers far more than the rigid rules of basic automation tools. It understands context, adapts to your preferences based on custom data, and improves over time through feedback. So, there’s plenty to gain.

In this article, we’ll dive into how contract AI works in practice, the risks to watch for, ways to get the most out of it, and how to choose the right tools. 

What is Contract AI?

Contract AI refers to tools that use technologies like natural language processing (NLP), large language models (LLMs), and generative AI to improve contract workflows. These tools can power a wide range of tasks like metadata extraction, clause comparison, contract summarization, and more.

Here are a few examples of how AI and contracts work together:

How Does Contract AI Benefit Your Business?

You might be wondering, using AI increases productivity, but is it worth the shift? According to World Commerce & Contracting’s (WCC) 2024 AI contract report, organizations that have introduced AI into their contract workflow have seen a 44% increase in productivity. Legal costs are down too, by up to 34%.

Unilever, for example, cut back its reliance on external counsel by using AI for standard contract work, saving both time and legal fees.

Victor André Enselmann, CEO of Modeva, a small marketing agency, shares a similar story:

“We use AI all the time when drafting contracts, whether NDAs, retainers, or partnership agreements. If it’s a standard agreement, we’ll polish it in-house and send it off. 

But for anything important or layered, we always run it past our legal advisor. That review step gives us peace of mind without burning hours on something a model can structure in minutes. Funnily enough, I was listening to Andrew Wilkinson’s podcast, billionaire and the founder of Tiny, and he described almost the exact workflow. He said the lawyers usually reply ‘looks great!’ before knowing they were created by AI”.

This shows just how far AI tools have come in generating reliable contract drafts (and assisting with other tasks). Whatever your business size, if you're not using them, you're probably spending more time and money than you should.

Some Practical Applications of Contract AI Software

Before diving into the use cases, you might be asking: why invest in contract AI tools when general-purpose AI like ChatGPT can already handle so many tasks?

The difference lies in specialization. While standalone AI models are trained on broad, general data, contract AI tools are often fine-tuned on legal documents and contracts specifically. This gives them a better grasp of legal language, clause structure, and industry nuances, making their output more relevant, reliable, and context-aware for contract-related work.

Contract review and analysis

Traditionally, contract review meant combing through documents to spot errors, risks, or missing clauses. Automations sped things up, but AI has taken it further. They can handle these tasks and suggest improvement in minutes, with more consistency and adaptability.

Many teams now use AI for first-pass contract reviews to give legal teams a head start for faster redlining. These tools scan contracts against a company’s playbook and flag clauses:

✅ Green if it meets company standards
❌ Red if it violates policy or presents risk
⚠️ Yellow if further review is needed

You can also be proactive by running your templates through AI to reduce red flags before sharing.

The 2024 WCC report states that companies using AI have seen a 35% boost in review accuracy—proof that these tools do more than just save time.

Contract review and analysis tools worth trying: SpeedLegal, Lawgeex.

Contract drafting

Rather than starting from a blank document or copying overused templates, AI tools can now generate first drafts tailored to your specific use case, whether for a one-time or recurring contract.

These tools use generative AI to generate, suggest, or improve clauses based on context, prior usage, and preset rules. That means faster drafting, fewer missed details

Even better, they learn from your edits. Over time, your standard language becomes smarter and more consistent with every use.

Drafting tools worth trying: Legalfly, Spellbook, Docupilot.

Contract summarization or briefs

Summarizing contracts used to take extra hours or required rigid, rule-based automation. Now, AI can generate both extractive summaries (pulling key points) and abstractive summaries (rewriting in simpler terms) in minutes. 

You can even customize the tone and focus depending on the audience, like tailoring summaries for the finance team. This saves time and makes complex contracts easier to digest for any audience.

Contract summarization tools to try: Surmise, Kira Systems, Evisort

Contract AI Challenges and Considerations

According to the WCC 2024 report, 76% of individuals and 36% of organizations said they’re more enthusiastic about using AI compared to 36% and 26% from the year before. This adoption shows that while AI has its flaws, they’re not dealbreakers. So, consider the points below as things to manage, not reasons to avoid it.

Accuracy and bias

AI tools have improved, but they can still miss nuances, overlook context, make things up (hallucinate), or show bias based on their training data. For instance, an AI-generated contract might default to English law or rely on Western contract norms that don’t apply globally. That’s why legal oversight is still essential, as emphasized by the founder of Modeva, who always runs important drafts past a legal advisor.

Monica Riederer, Vice President, Digital & Enterprise Operations Counsel with Northwestern Mutual, echoes this in the WCC 2024 report:

“These tools appear to be best at issue spotting and conducting an initial review, but there is clearly still a need for the subject-matter expert ‘human-in-the-loop’ to determine how to appropriately address those issues or fill the gaps in a way that is consistent with the company’s individual risk appetite.” 

Legal implication

AI in contract workflows raises more legal questions than answers right now. There are still very few laws that directly address how AI-generated contracts should be treated. This gray area raises critical questions, such as, is an AI-generated contract legally binding? Who owns the output: the user or the developer? And if the AI makes an error, who is liable?

Because no specific laws exist yet, most legal issues will fall back on established frameworks like contract law, agency principles, tort liability, and data privacy. That’s why businesses should tread carefully: review outputs thoroughly and understand the risks before fully relying on these tools.

Confidentiality and data privacy

Data is to AI what air is to humans. AI tools rely on data to deliver accurate, personalized outputs. But contracts are among the most sensitive documents businesses handle, so legal teams are understandably cautious, even with anonymized data. This creates a trade-off between confidentiality and output quality. Some even argue this reluctance could leave legal AI trailing behind other industries.

However, while custom output often depends on how much context you provide, you don’t have to compromise privacy. Reviewing the AI tool’s data storage, access, and training policies can help you strike the right balance. Further, most commercial AI tools let users retain the ownership of their output to encourage adoption.

What to Consider When Choosing AI-based Contract Tools

If you’re trying to figure out which tool is actually worth using, these five factors will help you separate the ones that make a real difference from the ones that just sound impressive on paper.

• Use case fit: Do you need help with drafting, reviewing, redlining, or summarizing? Choose a tool that specializes in the part of the contract process you care about most. While many contract AI tools claim to cover multiple use cases, they usually excel at one or two. Know what you need, then look for depth, not just breadth
• Ease of use: AI should reduce friction, not create it. Look for tools with clean interfaces, minimal setup, and a low learning curve. Even better if you can test them through free trials and demos before committing
• Customization and control: Can the tool learn from your internal clause libraries, fallback positions, or templates? The more you can fine-tune its outputs to reflect your organization’s language and risk tolerance, the more valuable it becomes
• Collaboration features: As mentioned in the challenges section, having a human in the loop is key to overseeing the process and making critical inputs. Collaboration features like in-app commenting, redlining, or tagging make that easier and more transparent
• Cost vs. value: There are plenty of free contract AI tools out there now, especially for drafting and summarizing. But free isn’t always useful. That said, you don’t need the most expensive tool either. Look at the actual return: How much time does it save? Is the output solid? Does it protect you from legal risk? And is your data secure?

Save More Time With AI + Automation: How to Draft Contracts With Docupilot AI Template Builder

Docupilot doesn’t just help you draft contracts, it helps you build smarter workflows. With the AI-powered template builder, you can create a tailored draft in seconds, then turn it into a dynamic template you can reuse as often as needed.

This means, if you generate lots of similar contracts (like non-disclosure agreements or onboarding documents), AI can draft them, autofill client data, route for approval, and send for e-signature, all with minimal manual effort. This way, you’re not just saving time on drafting, you’re also speeding up the entire contract lifecycle from creation to signature.

Here’s how: 

• Access the AI template builder: Log in to your Docupilot dashboard. Click on "Create Template" and select "Build with AI"

• Define template details: Enter a Template Name (e.g., “Freelance Service Agreement”) and a brief description of the contract’s purpose (e.g., “Contract between My Company Inc. and independent service providers for project-based work”)
• Generate AI prompts: After entering the template details, you'll be presented with auto-generated prompt suggestions. Choose a prompt that closely matches your requirements or customize it to better fit your needs
  
• Generate the template: Click "Generate" to let the AI create a structured contract template based on your input
  

• Review and customize: Once the template is generated, review it for accuracy. You can make adjustments, such as modifying text, adding merge fields, or refining formatting to align with your company's standards

• Automate the template: Once your template is ready, click Zapier or make an integration to set up automation by connecting it to your customer relationship management (CRM) system or form tool (like Google Forms or Typeform)

You can also set up approval and e-signature workflow for a more hands-off contract process through third-party integrations.

Final Thoughts: Embracing the Future of Contract AI

You don’t need to overhaul your entire process to benefit from contract AI. Start small. Pick one part of your workflow (drafting, reviewing, summarizing) and test how AI tools handle it. Let the results speak for themselves.

You’ll likely find that it’s not about replacing anyone. It’s about cutting down the busywork so your team can focus on the decisions that actually need human judgment.

And if you’re ready to see how this works in practice, Docupilot is a good place to begin. You can generate your first contract draft, turn it into a reusable template, and plug it into a workflow that runs on autopilot.

Want to try it out? Sign up for your 30-day free trial.