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).
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:
Better client experience
Faster decision-making
Stronger governance and compliance
More time for advisory work
This is one of the clearest wins for AI legal tools.
AI can review contracts in minutes, flagging:
Missing clauses
Inconsistencies
Risk markers
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:
Bulk contract reviews
Risk flagging and clause comparison
Policy alignment checks
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:
Case law
Statutes
Regulations
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.
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:
Identifying patterns
Highlighting anomalies
Suggesting likely relevance
Surfacing operational inefficiencies
This is where “AI in legal” shifts from productivity to strategy.
Where it’s most valuable:
Litigation support
Portfolio risk analysis
Operational improvement
From drafting to negotiation to renewals, AI can streamline the contract lifecycle.
Examples include:
Generating standard documents (like NDAs)
Tracking renewal deadlines
Flagging non-standard terms during negotiation
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.
AI automates the heavy lifting in due diligence by scanning large contract sets and flagging:
Compliance risks
Unfavourable terms
Missing clauses
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.
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:
Reduced preparation time
Lower costs
Fewer missed details
Clearer narratives
This is one of the strongest “scale benefits” of legal AI tools. The bigger the dataset, the bigger the impact.
Regulation moves fast. Contracts don’t update themselves.
AI helps legal teams keep pace by:
Scanning agreements for non-compliant clauses
Highlighting areas needing remediation
Supporting redrafting with approved language templates
The result: reduced risk, faster governance, and fewer last-minute compliance fire drills.
Predictive analytics is where AI starts supporting probability based decisions.
By analysing historical case data, AI tools can help estimate:
Likely outcomes
Settlement probabilities
Risk exposure
Resourcing requirements
It’s still developing, but for legal leaders, this will become a powerful lever for better forecasting and strategic planning.
AI enables law firms to develop new revenue streams by packaging repeatable legal support into scalable services.
Examples include:
Automated contract checks
Self-serve legal “triage”
AI-powered intake and assessment tools
This is where AI shifts from efficiency → growth.
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:
Phone calls
Video meetings
Client intake conversations
Follow-ups and actions
That means your comms stack needs to support the full journey:
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
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:
AI workflows for productivity
Customer/client interaction journeys
Conversational intelligence opportunities
Governance and compliance considerations