Why Teams Should Care About AI?

When OpenAI’s ChatGPT hit 100 million users in two months, it showed the world what’s possible when artificial intelligence becomes accessible to everyone. By mid-2025, over 80% of Fortune 500 companies report that their legal or operations teams use generative AI tools in some way.

Modern legal teams know they can’t afford to ignore AI’s role in contract lifecycle management (CLM), routine drafting, document review, or internal collaboration. But too often, teams get stuck between hype and hesitation. What will generative AI actually do for legal professionals? And where does it still fall short?

This guide explains, in clear terms, what AI does well, where it struggles, and how to use it wisely — backed by 2025 benchmarks and real examples.

The State of Generative AI in 2025

Generative AI has moved far beyond chatbots alone. Today’s top tools power summaries, contract redlining, clause recommendations, live negotiation support, multi-language drafts, and even early-stage risk scoring.

According to Gartner’s Legal and Compliance Hype Cycle 2025, contract review remains the number one real-world use case for AI in legal departments. A recent Law.com survey found that 62% of in-house legal teams now use AI to handle at least first-pass document review and internal approvals.

What Generative AI Can Do for Legal Teams

Summarize Complex Documents
Generative AI’s single biggest strength is processing large blocks of repetitive text. Legal teams use it to produce instant summaries of leases, NDAs, MSAs, procurement contracts, and more — saving hours of human reading time.

Example: A BoloSign user uploads a 50-page supplier agreement. In seconds, AI highlights key payment terms, renewal dates, notice periods, and potential risks.

Draft First-Pass Contracts
AI can draft standard agreements using your own clause library. This means faster NDAs, faster standard vendor agreements, and fewer delays waiting for legal to send initial drafts.

Review and Redline Automatically
LLMs can compare new contracts to your approved playbooks, flag unusual terms, and suggest edits. In a 2024 IACCM report, 7 out of 10 legal teams said that AI-driven redlining has cut first-round review times by 50% or more.

Surface Insights from Old Contracts
Modern AI isn’t just about new documents. It can process thousands of existing agreements to spot trends — from average renewal timelines to clauses that routinely cause disputes.

Example: One global company used AI to find out that 15% of its contracts were auto-renewing at higher-than-expected rates — savings hidden in plain sight.

Automate Routine Requests
Many in-house legal teams spend time fielding simple questions: “Where’s that NDA template?” or “Is this clause compliant?” AI can handle these repetitive first-line answers using your policies.

Brainstorm Clauses and Negotiation Points
Need alternative phrasing for an unusual risk clause? Generative AI can produce multiple clause versions, fallback language, or argument points to help you prepare for negotiation.

What’s Next: AI Agents for Legal Teams

In 2025, the next evolution of generative AI is AI agents. Unlike chatbots that answer questions, AI agents can break tasks into smaller steps, run those steps autonomously, and refine outputs on their own.

Real-World Example:
A legal team can assign different AI agents to:

• Monitor incoming vendor proposals and run first-pass reviews.
• Flag non-standard clauses for human lawyers.
• Track renewal milestones and send proactive alerts.
• Generate summary decks for the GC and board.

This multi-agent approach is already in pilot in some Fortune 500 legal teams. BoloSign’s AI tools handle elements of this flow today — clause checks, milestone tracking, and redlining — all in a single CLM system.

New Use Cases Emerging in 2025

Generative AI is moving deeper into legal tasks that once depended entirely on human teams. Early adopters are now using AI in these advanced ways:

Smarter Clause Libraries
AI doesn’t just store your approved clauses — it learns your preferred wording, fallback positions, and how you negotiate. This means every new draft pulls language that matches your brand voice and risk tolerance automatically, saving time on back-and-forth edits.

Example: Legal ops teams train AI on five years of signed contracts so standard MSAs always reflect your real-world terms.

Automated Risk Scoring
Modern AI tools can highlight risky clauses instantly by comparing them against your internal playbooks. Instead of reading line by line, lawyers get a clear risk rating so they know where to focus their review effort.

Example: If a vendor tries to insert uncapped liability, AI flags it and suggests the fallback your team uses most.

Multi-Language First Drafts
Global companies spend huge time localizing contracts. AI can now produce first drafts in multiple languages while preserving legal meaning — so local counsel can fine-tune instead of starting from scratch.

Example: A master service agreement is auto-generated in English, German, and Japanese in minutes, not days.

Real-Time Audit Trails
Every AI action — what was edited, flagged, or suggested — is now logged automatically. This creates a clear digital paper trail for compliance checks, internal reviews, or regulator audits.

Why it matters: Many new AI regulations require clear evidence of how decisions were made. An AI-enabled CLM with built-in logging makes this easy to prove.

What Generative AI Won’t Replace

For all the power of LLMs, there are areas where humans stay essential and will for the foreseeable future.

Complex Legal Strategy
AI can’t replace the judgment calls that come from years of practice. Decisions about whether to settle or fight, how to handle delicate negotiations, or when to bend vs. hold firm on risk — that’s human domain.

Client Relationships and Trust
Law is relationship-based. Human nuance, empathy, reading tone, and building trust can’t be outsourced to a model.

Local Legal Context
AI can surface the letter of the law — but interpreting it for a specific jurisdiction, culture, or fast-changing regulatory environment requires local human insight.

Edge Cases
Generative AI learns from patterns in data. When your scenario is too unusual — like a once-in-a-decade regulatory change — it won’t find enough examples to advise well.

Risk and Confidentiality
Finally, AI can introduce new risks. Free chatbots aren’t built for secure contract data. A misused prompt can leak confidential IP, as Samsung famously discovered in 2023. That’s why secure, enterprise-grade AI with strong user permissions is a must.

Common Pitfalls to Avoid

Blind Trust — Generative AI is powerful but not infallible. Large language models can confidently generate errors, outdated references, or misleading summaries. Always have qualified legal eyes review outputs before signing or sending.

Unclear Prompts — Vague or sloppy instructions lead to generic results. Teach your team how to give AI precise, context-rich prompts (like referencing the exact contract type, jurisdiction, or fallback clause). Clear input = reliable output.

Data Security Risks — Feeding confidential contracts into free consumer chatbots is a real threat. Sensitive deal terms, IP, and client info can leak. Use enterprise-grade AI tools designed for legal, with encryption, compliance certifications, and strict user controls.

Over-Customizing Too Soon — Many teams try to automate everything at once. Start with high-volume, repeatable contracts — like NDAs and SOWs — and expand only when you see clear ROI. Complex one-off workflows can drain resources if rushed.

How to Use AI Wisely

Start with Clear Wins — Identify contracts or tasks where repetitive manual effort slows you down, like standard NDAs or routine vendor reviews. Prove success fast.

Train with Real Data — Feed your AI actual executed contracts, not generic templates, so its recommendations match your real deal language and negotiation history.

Keep Human Oversight — Use AI for draft generation, risk flagging, and summaries — but require final approvals from qualified counsel to catch nuance AI can miss.

Measure and Share Results — Track time saved, review cycle time improvements, and user adoption to show the ROI of your AI rollout. Share wins to keep teams engaged.

Stay Audit-Ready — Use AI tools that log edits, suggestions, and approvals clearly. Clean audit trails protect you if questions ever arise about who changed what and when.

Real Stories: BoloSign Customers in 2025

Case Study 1: Vendor Risk Savings
A global logistics firm used BoloSign’s AI clause extraction to review 5,000 active vendor contracts. They found 10% had hidden auto-renewals with unfavorable pricing. In one year, they renegotiated enough deals to save $1.8 million.

Case Study 2: Faster Sales NDAs
A mid-market tech company rolled out self-serve NDAs inside BoloSign. Sales teams no longer waited three days for Legal to send a template. Now, salespeople generate NDAs themselves in minutes. Legal reviews only non-standard changes.

Case Study 3: Training Junior Counsel
An enterprise legal ops team used BoloSign’s AI side-by-side with junior lawyers. AI-generated summaries helped new hires learn faster — aligning AI output with senior counsel feedback improved both training and review consistency.

What’s Next for AI in Legal

The next wave of AI in legal will be about moving from standalone tools to deeply integrated, trusted systems that combine speed with accountability. By 2026, expect three clear shifts to reshape how in-house legal and operations teams use AI every day.

Tighter Integrations Across Systems

Today, many teams use AI in silos — a chatbot here, a redlining plugin there. That’s changing fast. The most effective legal tech stacks will have AI embedded directly inside core tools like your Contract Lifecycle Management (CLM) system, CRM, document management, and eSignature workflows.

Example: Instead of manually moving draft contracts from an AI writing tool to a CLM and then pushing them to an eSignature app, future-ready platforms like BoloSign will handle this entire flow inside one secure environment — from first draft to negotiation to signature — with AI suggestions and risk checks at every step.

Stronger Governance and AI Regulations

As AI matures, governments and industry bodies are stepping up oversight. In the EU, the AI Act is already setting new transparency and accountability rules for high-risk use cases, which includes parts of legal work. In the US, state-level data privacy laws increasingly expect clear audit trails for how AI-generated recommendations are created and used.

This means legal teams must choose tools that offer explainable AI — so you know why a clause was flagged or what data the model used. Clear logs, user permissions, and version tracking will be must-haves, not nice-to-haves.

Smarter AI Agents, Not Just Chatbots

We’re already seeing a shift from static “ask a question, get an answer” chatbots to AI agents that handle complex legal tasks autonomously — within guardrails you control.

For example, a smart contract agent might:

• Draft a new vendor agreement using your template library.
• Compare the counterparty’s edits to your playbooks.
• Flag risky clauses and auto-suggest alternatives.
• Notify the right reviewers, gather approvals, and route the final version for signature.
• Log every action for audit readiness.

These multi-step flows are becoming possible thanks to new developments in agentic AI, where an agent plans, executes, and learns from each task without constant human input — but always leaves final approval to your legal experts.

Forward-looking teams will combine AI-driven task automation with clear human oversight, so you unlock speed without losing control.

The BoloSign Approach

At BoloSign, our AI-first CLM is built to deliver real value, safely. We combine secure contract workflows, AI-powered summaries and clause checks, and native eSignatures — all in one place. You stay in control. Your team works faster and smarter. And your Legal stays the final decision-maker.

Key Takeaways

Generative AI frees teams from repetitive tasks, it doesn’t replace strategic judgment.
When used well, AI can cut cycle times by 30–50% for standard contracts.
Keep humans in the loop for final decisions and complex strategy.
Always use secure, enterprise-grade AI tools for legal workflows.
Start small, measure ROI, and expand as your team builds confidence.

FAQs

How secure is generative AI for legal work?
Consumer AI chatbots aren’t designed for confidential legal data. Always use an enterprise-grade AI with encryption, SOC 2 or ISO 27001 certification, and audit trails to control access and protect sensitive contracts.

Can AI draft entire contracts?
AI can handle standard agreements like NDAs or basic vendor contracts well. For complex deals, AI supports first drafts and risk checks, but final strategy, negotiation, and approval should stay with your legal experts.

Will AI replace junior lawyers?
No. AI automates repetitive tasks so junior lawyers spend more time on real legal work, research, and learning from senior counsel. It’s a support tool — not a substitute for people growing their legal skills.

How much time does it really save?
On average, legal teams using AI for routine drafts and reviews see first-pass turnaround drop by 30–50%. The more standardized your templates and workflows are, the bigger the time savings.

Where should we start?
Start with simple, repeatable contracts: NDAs, SOWs, or renewals. Use AI for summaries, clause checks, or auto-redlines. Prove the value fast — then expand to more workflows as your team gets comfortable.

Ready to Make AI Practical?

Generative AI is here to stay. Used wisely, it’s one of the best ways to unlock your legal team’s time and protect your business from hidden risk.

See how BoloSign’s AI-powered CLM makes your contracts faster, smarter, and more secure — without losing human judgment where it matters.

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