Agentic AI for In-House Legal: What’s Now, What’s Next, and What Teams Should Know
Want more content like this? Sign up for our monthly newsletter.
In all of this hype about artificial intelligence, it’s easy to forget: AI has existed for more than fifty years. It just wasn’t called AI.
In a recent webinar, Ironclad’s Chief Technology Officer, Sunita Verma, dove into how artificial intelligence is shaping the new legal landscape. And how the rate of change has accelerated over time. Researchers have been working for years to get computers to understand the human world, starting by encoding human learning into rules that machines could parse and execute. (It’s how this message gets typed and posted on our website in the first place!)But those initial rules were static. To make a change, rules needed to be updated for the machine to exhibit new behavior. Humans determined the inputs. As machines became better at learning, they were able to process small, labeled datasets to complete tasks. But those are not generalized capabilities. If the information isn’t included in the dataset, then the computer doesn’t know what to do.
Fast-forward to today. The amount of data machines can learn from has exploded with more internet connectivity—images, texts, research, everything is available online. These massive datasets, combined with high-performance computing architecture, gives researchers significantly more data to work with. And what they’ve been able to do is create computer processing pathways that mimic the way the human brain works, allowing AI to not just process a limited set of data to complete a task, but to create.
That became the genesis for our current, generative AI moment we’re seeing now.
It’s been top of mind because the legal teams that take advantage of this moment will set themselves up for success long-term…and the teams that don’t will very quickly be left behind. In this post, we’ll take a look at the state of agentic AI, how it can help in-house legal teams transform their operations, and where AI is going next.
What generative AI looks like right now
That brings us to our current generative AI moment. When we asked legal teams for the State of AI in Legal report, 69% responded that they currently use AI tools for legal work.
Source: State of AI in Legal 2025
The rise of generic chatbots or generalized AI tools has made it much more accessible to the average team to incorporate AI into their workflow. Things like summarizing case law, drafting legal documents, doing high-level research, and tagging metadata in contracts are all common use-cases for legal teams. Right now, though, much of the commercial AI tools available are “answer generators.” Essentially, more powerful search engines that generate polished results.
This is the undergraduate level of AI.
That’s because these generic chatbots, and generative AI, have a major limitation, especially in a detail-oriented, specific field like legal. If you ask a generic chatbot about the statute of limitations for a breach of contract in California, it can certainly give you some examples or some online search results. What’s made this current AI moment so interesting is the rise of domain-tuned models, which are trained with specific, vetted datasets and instructions for certain fields. If you ask one of these the same question, you’re much more likely to get the answer you’re looking for, with clause references, case law, and precedence included in the result.
Purpose-built technology, more than your Claude, ChatGPT, or Gemini, is what’s exciting about this moment.
What agentic AI actually is (and what it’s not)
Generative AI focuses on creating content based on prompts. When you ask ChatGPT, “Give me a list of the major procurement clauses I should negotiate,” that’s generative. With generative AI, you can offload the tedious, time-consuming aspect of your work to this technology and focus on aspects that require your full attention. Things like strategy, synthesizing analysis, coming up with next steps, and proactively managing your company’s portfolio of obligations.
Source: State of AI in Legal 2025
We’ll talk more about what that looks like in a legal setting in a minute, but it can truly help you accelerate research, drafting legal documents, and improve how contracts get analyzed. Yet what many legal professionals don’t know is that generative AI is just the beginning.
Agentic AI is the future of artificial intelligence in the workplace.
It acts as an autonomous manager that can pursue multi-step goals within your organization based on how you program it. The goal with artificial intelligence is to get machines to act like humans. When you think about it, there’s a lot of processes that go on in our brain as we take action, on the conscious and subconscious level. No matter what action we take, though, there is a level of planning. There’s a level of reasoning about the steps we need to take to complete that action, whether it’s thinking about our career trajectory or how to get up from a chair.
If generative AI is an answer generator, agentic AI is the action taker. An agentic AI agent acts like a sophisticated legal assistant. It can maintain context and remember important ideas or data across multiple tasks. It uses that information to work toward a desired legal outcome.
Researchers are continuing to build more complex capabilities in these domain-tuned models. Initially, agents solved simple tasks, but now this technology can handle so much more.
How agentic AI changes in-house legal operations
The reason agentic AI can do so much more is that it has more capacity for reason. Instead of just creating, and then creating, and then creating, it’s able to take multiple steps without instruction. And for legal teams, this will dramatically assist in the end-to-end contract lifecycle management, which involves preparation of information through intake, through analysis, through renewal, and so on.
Source: State of AI in Legal 2025
Many of these activities can be accomplished by agents, giving your team breathing room from the high-volume, high-repetition tasks that wear you down over and over again. When we asked legal professionals how AI helps them now, they find that adding AI into their workflows eliminates the kind of boring-yet-stressful tasks that make it so easy to burnout.
Source: State of AI in Legal 2025
What you get with agentic AI is faster cycle times, better coordination, and fewer dropped hand-offs so you can spend more time on judgment and strategy instead of coordination. This is what we’re building with Ironclad, so companies can execute or offload these manual tasks to highly trained AI agents while staying in control.
Humans are still a crucial part of this process
As legal professionals, it’s natural to focus on the risk that AI introduces into your organization. In fact, 48% of respondents to our AI survey mentioned security risks as a barrier to AI adoption, followed by information accuracy. These are real risks with artificial intelligence, though I want to say up front: These are very manageable risks.
Why humans matter
| Risk | What happens | How to mitigate it |
| Technical risk | AI models can still hallucinate because they don’t understand the meaning of what they’re outputting | Purpose-built technology and retrieval augmented generation cuts down on this risk by grounding the model in the right data |
| Security risk | Agents have wide latitude in the systems they can access and actions they can take | Building security architecture around those agents protects data privacy. Look for vendors with zero data retention policies |
| Ethics and compliance | Who takes accountability for autonomous action by machine? Agents are also influenced by the inherent biases presented in your data. | Set a company policy for how to handle incidents like these, and use your judgment and oversight on anything AI-generated. |
However, these technology challenges are solvable by making sure that humans remain a part of these workflows. Where organizations run into trouble is thinking that AI is going to allow them to remove a large portion of their workforce.
Instead, think of AI as a human amplifier. It can’t replace the judgment, creativity, and oversight that an experienced legal professional brings to their organization. Using agentic AI empowers your team to do more strategic, interesting work—and that is what will help your organization grow in the long run.
We’re just at the beginning of what agentic AI can do for legal teams
The next natural question with generative AI is not just: Can an AI understand language, but can it actually create something new? These are called multi-modal foundation models, and that’s where the industry is going next. Imagine a future where AI can analyze a video deposition, cross-reference it with other transcripts, and fact-check those references in one step.
At Ironclad, we’re building the next wave of agentic AI for legal organizations. Want to see how it can help empower your team? Request a demo today.
Ironclad is not a law firm, and this post does not constitute or contain legal advice. To evaluate the accuracy, sufficiency, or reliability of the ideas and guidance reflected here, or the applicability of these materials to your business, you should consult with a licensed attorney.
