Legal is one of the fastest-moving industries when it comes to AI adoption and the upside is obvious: less admin, faster turnaround, and better risk control.
Yet as AI accelerates, the firms winning aren’t the ones with the most tools. They’re the ones using legal AI in the right places, with the right guardrails, to remove friction from the workflow.
Below are the 9 highest-impact ways we’re seeing AI in legal being used today (and what to prioritise first if you’re getting started).
Why AI in Legal is accelerating so fast
Legal work is full of high value activity that’s often slowed down by repeatable tasks: scanning documents, checking clauses, finding precedent, tagging data, summarising calls, organising case files.
That’s exactly where AI shines.
The opportunity isn’t replacing expertise, it’s freeing people up to use it where it matters most:
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Better client experience
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Faster decision-making
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Stronger governance and compliance
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More time for advisory work
1. Document review and analysis
This is one of the clearest wins for AI legal tools.
AI can review contracts in minutes, flagging:
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Missing clauses
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Inconsistencies
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Risk markers
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Unusual wording or deviations
Instead of spending hours working through agreements line by line, teams can use AI to surface the issues then apply legal judgement where it counts.
Where this works best:
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Bulk contract reviews
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Risk flagging and clause comparison
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Policy alignment checks
2. Legal research at speed
One of the most searched questions right now is: what is the best AI for legal research?
The honest answer: it depends on your workflows, your sources and your governance requirements, but the outcome is the same.
AI can scan large legal databases and surface relevant:
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Case law
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Statutes
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Regulations
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Previous decisions
…in seconds, improving preparation time and helping teams move faster without cutting corners.
Practical tip:
AI works best as a research accelerator, not the final authority. Use it to narrow the field, then validate sources and context.
3. Handling large volumes of legal data
Legal teams often sit on mountains of information; case notes, emails, evidence files, meeting transcripts, disclosure documents.
AI analytics can transform that into something usable by:
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Identifying patterns
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Highlighting anomalies
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Suggesting likely relevance
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Surfacing operational inefficiencies
This is where “AI in legal” shifts from productivity to strategy.
Where it’s most valuable:
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Litigation support
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Portfolio risk analysis
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Operational improvement
4. Contract lifecycle management (CLM)
From drafting to negotiation to renewals, AI can streamline the contract lifecycle.
Examples include:
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Generating standard documents (like NDAs)
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Tracking renewal deadlines
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Flagging non-standard terms during negotiation
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Identifying where approvals are stuck
It’s one of the most practical uses of an AI legal assistant, because it improves speed and reduces human error.
5. Due diligence
AI automates the heavy lifting in due diligence by scanning large contract sets and flagging:
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Compliance risks
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Unfavourable terms
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Missing clauses
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Data gaps
Instead of teams drowning in manual review, AI surfaces what matters, so you can move quickly and confidently.
Typical use case:
M&A due diligence, vendor reviews, and large portfolio contract analysis.
6. Discovery and evidence analysis
In disputes and investigations, discovery is time-consuming and costly.
AI-powered discovery tools sift through electronic records and surface the most relevant evidence faster which means:
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Reduced preparation time
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Lower costs
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Fewer missed details
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Clearer narratives
This is one of the strongest “scale benefits” of legal AI tools. The bigger the dataset, the bigger the impact.
7. Compliance and risk management
Regulation moves fast. Contracts don’t update themselves.
AI helps legal teams keep pace by:
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Scanning agreements for non-compliant clauses
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Highlighting areas needing remediation
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Supporting redrafting with approved language templates
The result: reduced risk, faster governance, and fewer last-minute compliance fire drills.
8. Compliance and risk management
Predictive analytics is where AI starts supporting probability based decisions.
By analysing historical case data, AI tools can help estimate:
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Likely outcomes
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Settlement probabilities
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Risk exposure
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Resourcing requirements
It’s still developing, but for legal leaders, this will become a powerful lever for better forecasting and strategic planning.
9. New revenue opportunities (the “next chapter”)
AI enables law firms to develop new revenue streams by packaging repeatable legal support into scalable services.
Examples include:
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Automated contract checks
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Self-serve legal “triage”
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AI-powered intake and assessment tools
This is where AI shifts from efficiency → growth.
The biggest opportunity: connect AI workflows to comms + CX
Here’s the real unlock most businesses miss:
If AI tools sit separately from communications and client interaction workflows, you only get half the benefit.
Legal teams don’t just work in documents, they work in:
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Phone calls
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Video meetings
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Client intake conversations
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Follow-ups and actions
That means your comms stack needs to support the full journey:
- capturing insights
- reducing admin
- improving response time
- maintaining trust and compliance
This is especially true for conversation intelligence, where client calls become searchable, usable insight (not lost context).
“Fortay walked us through what modern platforms can actually do, translated all the technical jargon into real business value, and completely transformed how we interact with clients.”
— Ben Hallatt, COO, Ashtons Legal
Want help finding the best-fit AI opportunities?
If you’re exploring AI in legal and want to identify the fastest, safest wins - we can help.
We’ll review your current setup and recommend practical improvements across:
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AI workflows for productivity
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Customer/client interaction journeys
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Conversational intelligence opportunities
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Governance and compliance considerations
