Generative AI in Legal Work: Frequently Asked Questions

Generative AI (GenAI) is one of the most talked-about technologies in legal today. From accelerating contract review to streamlining due diligence, GenAI has the potential to revolutionize how legal teams work. But like any powerful tool, it’s important to understand how it works, where its limitations lie, and how to apply it responsibly.

In this article, we answer the 10 most important questions about Generative AI—what it is, what it does, and how Robin AI ensures legal professionals can use it effectively, securely, and with confidence.

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1. What is Generative AI?

Generative AI is a type of artificial intelligence designed to produce content—whether that’s text, code, images, or data—based on patterns it learns from large amounts of training data. In legal workflows, this typically means generating summaries, extracting key contract terms, answering questions based on contract contents, and drafting legal text.

At its core, Generative AI processes natural language and transforms unstructured information into structured insights. For legal professionals, it helps accelerate tasks that are often repetitive and time-consuming, such as reviewing contracts or producing reports.

At Robin AI, we use Generative AI to streamline complex contract analysis while ensuring human professionals stay in control of decision-making.

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2. What Can Generative AI Do in Legal Workflows?

Generative AI offers legal teams several advantages by accelerating routine tasks and enhancing efficiency. Some of its most common uses include:

• Analyzing large volumes of contracts to identify and extract key clauses, obligations, and risks.
• Summarizing documents to give legal professionals a clear, concise understanding of complex agreements.
• Extracting specific data points, such as payment terms, governing law, termination rights, and liability caps.
• Producing draft clauses or language to support document drafting or negotiation prep.
• Standardizing reviews across teams by ensuring consistent approaches to contract analysis.

At Robin AI, our products are built on the principle that AI is there to support—not replace—legal professionals. We call this approach "human-in-the-loop". We ensure AI-driven reports and outputs are accurate, controllable, and designed to enable human experts to make informed decisions.

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3. What Are the Limitations of Generative AI?

Despite its power, Generative AI has limitations legal professionals need to understand:

• It lacks context awareness beyond the document it's analyzing. It doesn’t understand the commercial realities of your deal or relationships.
• It can only provide answers based on the data it’s given, not the broader strategic objectives of your business.
• It depends on well-defined instructions—poorly phrased questions can lead to unclear or incomplete answers.
• Human oversight is essential. AI can summarize, extract, and structure data, but it cannot make legal judgments or strategic decisions.

At Robin AI, we address these limitations through our Human-in-the-Loop (HITL) approach. While our Generative AI accelerates tasks like contract analysis and drafting, we ensure that human experts remain central to the process.

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4. How Accurate Is Generative AI?

Generative AI is highly effective at processing large volumes of legal data and delivering consistent results, but it’s important to understand how accuracy works in this context. The AI doesn’t “understand” legal concepts the way a human does—it identifies patterns and extracts information based on the documents it’s given and the instructions it receives.

Accuracy depends on several factors:

• The quality and clarity of the input documents.
• How clearly the AI is guided toward what to look for.
• Human review to interpret findings and apply legal judgment.

At Robin AI, we believe the best outcomes come from pairing AI with human expertise. We follow a Human-in-the-Loop approach—AI accelerates the process by analyzing and extracting information, while legal professionals review and validate the results.

We also prioritize transparency. Every output is supported by citations that link directly to the source material, making it easy to verify information and maintain trust in the results.

Generative AI makes legal work faster and more consistent—but humans remain essential for ensuring accuracy and making strategic decisions.

This combination of control, transparency, and human expertise ensures Robin AI delivers reliable outputs you can trust

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5. How Does Generative AI Handle Uncertainty?

Many AI systems will provide an answer, even if they’re uncertain—leading to hallucinations (incorrect or fabricated information).

Robin AI takes a different approach. If the AI cannot find the requested information in the data, it will clearly indicate this—using N/A, or stating explicitly that no relevant information was found.

This transparency ensures legal professionals are aware of any gaps in the data and can make informed decisions about next steps.

In legal workflows, knowing when the AI doesn’t have an answer is just as important as knowing when it does.

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6. How Secure Is Generative AI?

Security is critical for any AI system handling sensitive legal documents. Robin AI’s approach to data privacy and security includes:

• Private Cloud Ecosystem for our clients in AWS: All processing and data storage occurs within our secure AWS instance—your data never leaves Robin AI’s infrastructure.
• ISO 27001 and SOC 2 Type II Certification: Our information security systems meet rigorous industry standards.
• Encryption: All customer data is encrypted both at rest and in transit.
• Strict Access Controls: We enforce tight access policies, regular audits, and unique production database authentication.
• Data Sovereignty and Deletion Policies: We ensure customer data is deleted upon contract termination, and we never use customer data to train external AI models.
• Regulatory Compliance: Robin AI complies with GDPR and Cyber Essentials frameworks, meeting the strictest privacy and security standards.

We also partner with Anthropic via AWS Bedrock, giving our customers a private, secure instance to leverage Anthropic's Large Language Models (LLMs), inaccessible to outside parties.

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7. How Does Generative AI Fit into Legal Workflows?

AI works best when it fits seamlessly into existing legal processes—augmenting, rather than disrupting, the way legal teams work.

Robin AI integrates Generative AI into:

• Microsoft Word, enabling lawyers to review, draft, and analyze contracts within the tools they already use.
• A secure  platform, where legal teams can analyze contracts at scale, run structured reviews, and collaborate across teams.

This seamless integration makes AI adoption more intuitive, reducing friction and helping teams focus on delivering legal value.

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8. What Are the Risks of Using Generative AI in Legal Work?

The key risks include:

• Hallucination or inaccurate outputs, especially if AI systems guess rather than acknowledge uncertainty.
• Data privacy concerns, if systems are not secure or data is processed outside protected environments.
• Over-reliance on AI, where legal professionals may bypass necessary human review.

Robin AI mitigates these risks by:

• Providing clear, verifiable outputs backed by source citations.
• Implementing best-in-class security standards to protect sensitive information.
• Emphasizing human validation and decision-making as integral parts of any AI-supported workflow.

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9. What Are Best Practices for Using Generative AI in Legal Work?

Legal teams adopting Generative AI should follow these best practices:

• Start small – Apply AI to clearly defined, repetitive tasks like clause extraction or contract summaries.
• Be specific in your instructions – Ask clear, direct questions to improve answer quality.
• Leverage solutions that bring structure – Use platforms like Robin AI Reports to organize and standardize outputs for consistent, actionable insights.
• Always review AI outputs – Utilize verification tools, such as citations, to confirm accuracy before taking action.
• Integrate AI into existing workflows – Ensure your team maintains control over legal outcomes by seamlessly incorporating AI into familiar tools and processes.

Robin AI’s platform makes it easy to implement these best practices with customizable tools and integrated workflows, empowering legal teams to work more efficiently and confidently.

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10. How Do I Get Started with Generative AI in Legal?

Adopting Generative AI starts with identifying areas where it can deliver the most value. Legal teams should begin with structured, high-volume tasks that require consistency and efficiency, such as:

• Contract Due Diligence – Reviewing large volumes of agreements to extract key terms.
• Regulatory Compliance Audits – Ensuring contracts meet evolving legal and industry requirements.
• Obligation Management – Tracking post-execution duties like payment terms and renewal notices.
• Risk Identification – Surfacing red flags in supplier agreements, NDAs, and MSAs.

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How Robin AI Helps You Get Started

Robin AI provides a full suite of AI-powered solutions to streamline legal workflows:

• Legal AI Assistant: Integrated directly into Microsoft Word, it accelerates contract review, clause extraction, and drafting while keeping lawyers in control.
• Robin AI Platform : Extracts and synthesizes data across legal documents using Reports, delivering structured insights with citations for verification.
• Contract Services: A combination of AI and legal experts to expedite contract negotiation and review.

By starting with focused, high-impact tasks and leveraging AI tools designed for legal professionals, teams can validate AI’s benefits before scaling its use across more complex workflows.

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Conclusion

Generative AI has the potential to revolutionize legal work—but only when implemented with accuracy, security, and human oversight in mind. Robin AI combines advanced AI capabilities with rigorous security standards and transparent workflows, helping legal teams move faster, reduce manual work, and maintain control over outcomes.

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