AI in the Legal Sector: How Artificial Intelligence Is Transforming Legal Work Day by Day

The legal profession — historically defined by human expertise, analytical reasoning, and the nuanced interpretation of rules and facts — is facing an unprecedented technological transformation. Artificial intelligence (AI) has entered the legal sector not as a threat that replaces lawyers, but as a tool that amplifies their capabilities, eliminates repetitive tasks, and frees up time for strategy, creativity, and counsel.

According to a Goldman Sachs report, 44% of legal tasks could be automated with today’s AI. A McKinsey study estimates that 23% of lawyers’ time spent on documentary tasks can be handled by intelligent systems. The numbers speak for themselves: LegalTech — technology applied to the law — is no longer an emerging trend but a competitive necessity.

Firms such as Allen & Overy, Linklaters, Clifford Chance, and Freshfields have already integrated AI tools into their standard workflows. And in-house legal departments are not lagging behind: according to the ACC Chief Legal Officer Survey, more than 60% of CLOs globally say AI is a strategic priority for their teams.

Below, we explore the main use cases for AI in the legal environment and how they are transforming the daily work of lawyers, jurists, and compliance teams.

Automated Contract Review and Analysis

Contract review is perhaps the most mature and widespread AI use case in the legal sector. A complex contract can demand hours — or days — of meticulous reading. AI can analyse hundreds of documents in minutes, flagging critical clauses, potential risks, deviations from standard templates, or negotiation points.

Tools such as Kira Systems, ContractPodAi, Ironclad, and Luminance use large language models (LLMs) trained specifically on legal text to extract key information from contracts: signing parties, deadlines, penalties, confidentiality clauses, exclusivity provisions, and change-of-control terms.

One of the most emblematic examples is A&O Shearman (the merger of Allen & Overy and Shearman & Sterling), one of the first major firms to adopt Harvey AI — a generative AI platform built specifically for legal work — to assist lawyers with contract review, document drafting, and case analysis. The result was a significant reduction in review time, allowing lawyers to focus on negotiation and strategic counsel.

Similarly, Clifford Chance deployed AI tools to review syndicated credit agreements, achieving a 50% reduction in review time for certain transaction types.

What Does AI Analyse in a Contract?

Limitation of liability and indemnification clauses
Early termination and rescission conditions
Confidentiality and data protection obligations
Non-compete and non-solicitation covenants
Notice periods and breach penalties
Change-of-control and force majeure clauses

This analytical capability does not eliminate lawyer review — it focuses it. Instead of reading 100% of the contract, the professional concentrates on the clauses flagged as relevant or problematic by the AI.

Legal Research: From Days to Minutes

Legal research — finding case law, identifying relevant precedents, tracing the doctrinal development of an issue — is another area where AI is having a transformational impact.

The major legal databases have made the leap to generative AI. LexisNexis launched Lexis+ AI, an assistant that allows natural-language queries about legislation, case law, and doctrine, with cited and verified responses. Thomson Reuters offers CoCounsel and Westlaw AI, integrated into its platform, with similar capabilities.

The productivity impact is striking: according to Thomson Reuters data, lawyers using AI for legal research can reduce the time spent by up to 80%. A task that previously required several hours — reviewing dozens of rulings and producing a jurisprudence memo — can now be completed in minutes.

This implies not only improved efficiency but also improved quality of advice. A lawyer with fast, exhaustive access to all relevant case law can give better-grounded counsel, identify nuances that might otherwise be missed, and anticipate opposing arguments.

Concrete Advantages of AI-Assisted Research

Semantic search across millions of documents in seconds
Identification of relevant precedents by analogy, not just keyword matching
Automatic summaries of rulings with extraction of the ratio decidendi
Alerts on new case law or legislative changes in areas of interest
Analysis of the doctrinal evolution of a concept over time

Assisted Drafting and Generation of Legal Documents

Beyond review, AI also assists in creating legal documents: briefs, pleadings, agreements, standard clauses, and due diligence reports.

Platforms such as Harvey AI, CoCounsel (Thomson Reuters), or Spellbook (integrated with Microsoft Word) allow lawyers to generate first drafts from natural-language instructions, adapted to the jurisdiction, transaction type, and desired tone.

A practical example: an M&A lawyer can instruct the system to “draft a representations and warranties clause for a technology company acquisition in Spain, with a liability cap of 18 months and a materiality threshold of 1% of the purchase price.” The AI produces an initial draft that the lawyer reviews, adjusts, and refines. Total time is drastically reduced.

This does not make AI the author of the document: the lawyer remains responsible for the content, legal accuracy, and strategic judgment. But AI eliminates the “blank page” and allows work on a stronger foundation from the very first moment.

Document Types Where AI Already Adds Value

Sale, distribution, and service agreements
Civil and administrative pleadings and briefs
Legal opinions and advisory notes
Legal due diligence reports in corporate transactions
GDPR-compliant privacy policies and terms and conditions
Board minutes, powers of attorney, and corporate documents

E-Discovery and Identification of Relevant Documents in Litigation

In major litigation and international arbitration proceedings, the e-discovery phase — the collection, review, and selection of relevant documents — can involve reviewing millions of emails, contracts, internal communications, and files. Historically, this required teams of dozens of lawyers working for months, at enormous cost.

AI has radically transformed this process. Using Technology-Assisted Review (TAR), predictive coding, and classification models, platforms such as Relativity, Reveal AI, and Everlaw can:

Automatically identify potentially relevant documents
Classify them by topic, privilege, or relevance
Detect duplicates and near-duplicates
Extract key entities: people, dates, places, legal concepts

The result is immediate: reviews that previously lasted weeks are completed in days, with greater precision and at a fraction of the cost. Industry data shows that AI-assisted review can reduce e-discovery costs by up to 70%.

AI also reduces the risk of missing critical documents — one of the main risks in managing large litigation matters. A human team working against the clock can overlook relevant evidence; a well-trained system does not.

Predictive Analytics for Judicial Outcomes

One of the most advanced — and most debated — AI applications in law is predicting the outcome of judicial proceedings. Platforms such as Lex Machina (acquired by LexisNexis) and Premonition analyse millions of historical rulings to identify patterns and provide success probabilities across different types of proceedings.

What Can AI Predict?

The likelihood that a specific court will grant or deny a type of claim
Trends in courts on specific matters: intellectual property, employment, commercial law
The estimated duration of a proceeding
The relative success of different litigation strategies
The probability of out-of-court settlement based on the case profile

This information has enormous strategic value: it allows lawyers and their clients to make more informed decisions about whether to litigate or negotiate, which arguments to prioritise, and when to pursue settlement.

Lex Machina has processed more than 1 million federal cases in the United States, and some firms use it as a routine part of their pre-litigation analysis. In Europe, research projects in France and the Netherlands have demonstrated accuracy rates above 70% in predicting European Court of Human Rights rulings.

It is important to note that these tools are not designed — and must not be used — to replace the lawyer’s deep legal analysis, but to complement it with data intelligence that would otherwise be inaccessible.

Regulatory Compliance and Continuous Monitoring

In an increasingly complex regulatory environment — GDPR, NIS2 Directive, EU AI Act, AML regulations, ESG, Basel IV — continuously tracking regulatory changes is an enormous task for any legal or compliance department.

AI enables continuous regulatory monitoring: tracking publications from national gazettes, the Official Journal of the EU, the EBA, ESMA, and other relevant bodies; classifying regulatory changes by impact area; and generating alerts when provisions affecting the company’s activities are published.

Tools such as Clausematch, Corlytics, and Ascent RegTech use natural language processing (NLP) to analyse normative texts, map requirements, and automatically update internal compliance frameworks.

The direct impact: compliance teams can stay current with all relevant changes without manually reviewing hundreds of publications, and can quickly identify which internal policies, contracts, or procedures need updating.

Use Cases in Automated Compliance

AML and KYC: Automated identity verification, suspicious transaction monitoring, and regulatory reporting
Privacy: Identification of data flows requiring updates to processing records or impact assessments
ESG: Tracking sustainability regulations and generating compliance reports
International sanctions: Monitoring OFAC, UN, and EU lists and alerting on sanctioned counterparties

Virtual Assistants and Legal Client Service

Intelligent virtual assistants are also transforming the relationship between firms and their clients. Legal chatbots allow:

Immediate, 24/7 responses to frequently asked legal questions
Guidance on what type of service or practice area the client needs
Management of schedules, information requests, and new client onboarding
Real-time access to the status of active matters
Automated alerts on procedural deadlines or pending documentation

Platforms such as DoNotPay — which describes itself as “the world’s first robot lawyer” — have shown that AI can handle simple claims, traffic fine appeals, and consumer disputes with remarkable effectiveness, democratising access to basic legal advice for citizens who could not otherwise afford it.

In the corporate sector, many firms have implemented intelligent client portals where clients can access real-time matter updates, review documentation, or receive automated alerts on key milestones.

Accelerated Due Diligence in Corporate Transactions

In mergers and acquisitions, financings, and IPOs, legal due diligence involves reviewing hundreds or thousands of contracts, licences, litigation records, IP registrations, and corporate documents. In complex transactions, this can take weeks.

AI is dramatically accelerating this process. Using tools such as Harvey’s due diligence engine, Kira Systems, or Luminance, legal teams can:

Automatically ingest and classify thousands of documents uploaded to the data room
Identify relevant contractual risks: change-of-control clauses, pre-emption rights, assignment restrictions, or confidentiality commitments
Generate automatic summaries by document category
Produce an initial due diligence report in hours, not days

The benefit is twofold: the total cost of the transaction is reduced, and the closing process accelerated — a critical competitive advantage in deals where deadlines are tight and competing bidders are at the table.

Ethical Considerations and Risks That Cannot Be Ignored

The adoption of AI in the legal sector is not without significant challenges. These must be rigorously addressed before deploying any tool in a professional environment.

Hallucinations and Factual Errors

Language models can produce incorrect answers or invent non-existent legal references. In 2023, a New York lawyer was sanctioned for submitting a brief drafted with ChatGPT that cited fictitious case law. This case illustrates the need to always verify AI outputs before using them in professional contexts.

Tools designed specifically for the legal sector — such as Lexis+ AI or CoCounsel — include verification mechanisms and cited sources to mitigate this risk, but human oversight remains essential.

Confidentiality and Data Protection

Lawyers have strict ethical duties of confidentiality regarding client information. Using AI tools that process sensitive data in the cloud raises questions about where data is stored, who can access it, and whether it is used to train future models.

It is critical to choose providers with robust contractual guarantees — including GDPR-compliant data processing agreements — and that do not use client data to retrain their models without explicit consent.

Algorithmic Bias

Predictive systems trained on historical data can perpetuate existing biases in the judicial system. A model trained on past decisions may reproduce systemic inequalities if those historical data reflect unjust or discriminatory practices. This risk is especially relevant in litigation risk analysis or outcome prediction applications.

Professional Responsibility

Ultimately, responsibility for legal work lies with the lawyer, not the tool. AI is a support, not a substitute for professional judgment and ethical responsibility. Bar associations across jurisdictions are developing ethical AI use guidelines that legal professionals must know and apply.

Tangible Benefits for Firms and Legal Departments

The use cases above translate into concrete, measurable benefits:

Efficiency and Productivity

Up to 80% reduction in legal research time
Contract review up to 5 times faster than with traditional methods
E-discovery cost reductions of up to 70%
Due diligence reports in hours instead of weeks

Quality and Accuracy

Lower error rates in identifying contractual risks
Comprehensive coverage of applicable case law and regulations
Consistency in applying criteria across all reviewed documents

Client Access and Service

24/7 availability for frequently asked questions
Greater transparency and proactive communication on matter status
Faster, fully digital client onboarding

Strategic Competitiveness

Ability to handle more work with the same resources
Differentiated value proposition against competitors that haven’t adopted AI
Cost reductions that allow more competitive pricing or improved margins

The Future: Augmented Lawyers, Not Replaced Ones

The narrative of the “robot replacing the lawyer” is simplistic and wrong. AI does not replace deep legal reasoning, client empathy, creativity in building arguments, or the ability to negotiate and persuade in the courtroom. What it does is eliminate low-value tasks that consume a disproportionate share of legal professionals’ time.

The profile of the lawyer of the near future — and already of the present — is the augmented lawyer: a professional who uses AI as an extension of their capabilities, who knows which questions to ask the tools, how to verify their responses, and how to integrate technological efficiency with strategic judgment and ethical responsibility.

Firms and legal departments that adopt this vision first — that invest in training, the right tools, and AI-adapted processes — will have a structural competitive advantage over those who delay the transformation.

Take the Next Step in the Digital Transformation of Your Legal Practice

At ALS Innovation, we help law firms, in-house legal departments, and LegalTech companies design and implement AI solutions tailored to their specific needs: from automating document review to integrating legal virtual assistants, enabling continuous regulatory monitoring, or accelerating due diligence processes.

Our experience combining artificial intelligence, process automation, and strategic consulting allows us to accompany legal teams at every stage of their digital transformation, with a rigorous focus on regulatory compliance, data security, and ethical responsibility in the use of AI.

Contact us and discover how to turn artificial intelligence into a real competitive advantage for your legal practice.