AI for Legal Ops: The 2025 Guide to Implementation

The reality of AI adoption in legal departments
AI applications that deliver real value for legal teams
Implementation strategies that maximize AI success
Common AI pitfalls and how to avoid them
The future of AI in legal departments
Case study: Concord's Agreement Intelligence in action
Practical next steps for your legal team
Conclusion: A balanced approach to legal AI
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The reality of AI adoption in legal departments

AI for legal teams represents a significant opportunity to transform workflows, but implementation remains a challenge for many organizations. According to Thomson Reuters’ Future of Professionals Report, legal professionals cite handling large volumes of data more effectively as a key area where AI can help deliver greater value, with 59% of respondents highlighting this specific capability.

The challenge for legal teams isn’t a lack of options—it’s identifying which AI contract management tools solve real problems without creating new ones. Let’s explore what’s working, what isn’t, and how to implement the most effective AI solutions for your legal department.

AI applications that deliver real value for legal teams

1. Contract analysis and management

Contract analysis consistently ranks as the most valuable AI application for legal teams. According to Thomson Reuters, 59% of legal professionals cite handling large volumes of legal data more effectively as a key area where AI can deliver greater value.

Modern Agreement Intelligence platforms like Concord’s use AI for contracts to automatically extract key terms, streamlining processes that once took hours into tasks that take seconds. This approach transforms static contracts into dynamic, data-rich assets that inform business decisions.

What works:

Automated metadata extraction (dates, payment terms, renewal clauses)
Risk identification in contract language
Obligation tracking and deadline management
Centralized contract repositories with intelligent search

What doesn’t:

Complete contract drafting from scratch without human oversight
Fully automated contract negotiation
One-size-fits-all implementation without customization

Michael Cuschieri, Group Head of Legal at LeoVegas, experienced this transformation firsthand: “Our old process involved diving into folders, opening documents one by one, and sifting through clauses. Now, it’s a matter of clicks. This efficiency has completely reshaped how we handle compliance.”

2. Legal research and due diligence

AI-powered legal research tools have dramatically improved in reliability and usefulness. Systems that combine natural language processing with comprehensive legal databases can significantly reduce research time while improving thoroughness.

What works:

Case law and precedent identification
Regulatory compliance monitoring with contract compliance management software
Multi-jurisdictional legal research
M&A due diligence assistance

What doesn’t:

Completely replacing attorney judgment on legal interpretations
Operating without human verification of sources
Research without clear parameters and guidance

A recent study published in the National Law Review found that while AI legal research tools demonstrated impressive capabilities in identifying relevant precedents, they still required attorney oversight to ensure proper application to specific cases.

3. Document review and e-discovery

Document review represents another area where legal contract AI delivers measurable value. Modern systems can sort through millions of documents to identify relevant information based on specific criteria.

What works:

Automated document categorization and tagging
Privilege identification and redaction
Pattern recognition across large document sets
Predictive coding for e-discovery

What doesn’t:

Unsupervised document production
Handling of highly nuanced or context-dependent reviews
Complete elimination of human review

Implementation strategies that maximize AI success

Implementing AI effectively requires more than just purchasing software. Here are practical strategies to maximize the return on your AI investments:

1. Start with specific, high-value problems

The most successful AI implementations begin with clearly defined problems that have measurable outcomes. According to Juro’s AI for legal teams blog, focusing on what can be automated right now and targeting high-volume work that is taxing but not complex is a solid approach for legal teams.

Action tip: Identify one specific, time-consuming process—like contract renewal tracking or NDA reviews—and implement contract automation software specifically for that task. Measure the time saved and use that as a foundation for broader adoption.

2. Focus on augmentation, not replacement

AI works best when it enhances legal professionals’ capabilities rather than attempting to replace their judgment. Think of AI as a sophisticated research assistant, not a substitute attorney.

Action tip: Implement systems where AI handles the initial data gathering and analysis, but final decisions remain with legal professionals. This “human-in-the-loop” approach balances efficiency with necessary oversight.

3. Invest in proper training and integration

Many AI implementations fail not because of technology limitations, but due to inadequate training and integration. Legal professionals need to understand not just how to use AI tools but when and why to use them.

Action tip: Create role-specific training that shows each team member how AI solves their specific pain points. For example, show contract specialists how legal contract management software can help them identify risky clauses, while showing litigators how it can help prepare for case reviews.

Common AI pitfalls and how to avoid them

1. Overreliance on AI without verification

The most dangerous AI pitfall is treating AI outputs as definitive without verification. While AI can dramatically accelerate work, it still requires human oversight to ensure accuracy.

Solution: Implement structured verification processes where AI suggestions undergo appropriate human review before being finalized.

A study featured in ArentFox Schiff’s AI blog highlighted that verification processes not only prevent errors but also help train the AI system to improve over time through feedback loops.

2. Implementing AI without clear metrics

Many legal departments implement AI without defining clear success metrics, making it impossible to evaluate ROI objectively.

Solution: Establish baseline metrics before implementation, then track improvements. Relevant metrics include:

Metric	Description	Target Improvement
Contract review time	Average time to complete contract reviews	40-60% reduction
Research efficiency	Time spent on legal research tasks	30-50% reduction
Risk identification	Percentage of risks identified in contracts	20-40% improvement
Compliance incidents	Number of missed compliance deadlines	50-70% reduction

3. Neglecting data quality and organization

AI systems are only as good as the data they’re built on. Disorganized or incomplete data will lead to poor AI performance regardless of the underlying technology.

Solution: Begin with a data audit and organization initiative before implementing AI. Clean, structured data dramatically improves AI effectiveness.

The future of AI in legal departments

Looking ahead to 2025 and beyond, several trends are shaping how AI will continue to transform legal operations:

1. The rise of agentic AI

According to NetDocuments’ 2025 Legal Tech Trends report, agentic AI represents the next frontier. These systems can act more autonomously, effectively adding a new legal assistant to your team. Early adopters will gain a significant advantage by implementing these tools that require less constant supervision.

2. Integration with existing workflows

The most successful AI tools won’t exist as standalone applications but will seamlessly integrate into existing legal workflows. This approach means technology serves as a natural extension of how legal professionals already work rather than requiring them to adapt to new processes.

3. Enhanced multi-modal capabilities

Future AI systems will work effectively across text, images, and audio, allowing for more comprehensive legal analysis. This development is particularly relevant for evidence review, where AI can analyze multiple data types simultaneously.

Case study: Concord’s Agreement Intelligence in action

To illustrate these principles in practice, let’s examine how one organization transformed their contract management with artificial intelligence.

LeoVegas, a global leader in online gaming, operates in multiple jurisdictions with complex regulatory requirements. Their legal team was overwhelmed by the manual work required to review contracts for compliance across different regions.

After implementing Concord’s Agreement Intelligence, LeoVegas automated key processes including:

Extracting essential information like jurisdictional requirements
Categorizing contracts with custom tags for easy retrieval
Setting up automated alerts for upcoming deadlines

The results were dramatic: contract reviews became 400% faster, giving the legal team more time to focus on strategy. What once took weeks could now be accomplished in hours.

Practical next steps for your legal team

Ready to improve your legal team’s AI implementation? Here are three actionable steps to take today:

1. Conduct an AI readiness assessment

Evaluate your current processes, data organization, and most pressing pain points. Identify specific areas where AI could deliver the greatest value based on your team’s unique challenges.

2. Start small with a targeted pilot

Choose one high-impact use case—like contract analysis or legal research—and implement a focused pilot project. Set clear success metrics and evaluate results after 90 days.

3. Build an AI skills development plan

Create a structured training program to build your team’s AI literacy. This should include both technical skills (how to use AI tools) and critical thinking skills (how to evaluate AI outputs).

FAQs about AI for legal teams

What’s the realistic time investment required for implementing AI in legal departments?

Implementation timelines vary based on scope, but effective AI projects typically require:

2-4 weeks for initial assessment and planning
1-2 weeks for platform setup and configuration
2-3 weeks for initial training and pilot testing

Modern platforms like Concord can be implemented much faster than legacy systems, with some teams getting started in as little as 24 hours versus 6+ months for conventional platforms.

How can we address confidentiality concerns with AI tools?

Addressing confidentiality concerns requires:

Using enterprise-grade AI solutions with strong security protocols
Implementing role-based access controls
Restricting sensitive data from being processed by external AI systems
Considering on-premises or private cloud AI deployments for highly sensitive matters

What skills should legal teams develop to work effectively with AI?

The most valuable skills for AI-enabled legal teams include:

Basic data literacy and analysis
Critical evaluation of AI outputs
Process design and optimization
Collaborative problem-solving with technology teams

How do we measure the ROI of our AI implementation?

Effective ROI measurement combines quantitative and qualitative metrics:

Time savings on routine tasks
Error reduction rates
Cost savings from reduced outside counsel
Improved compliance outcomes
Team satisfaction and reduced burnout

To get a clear understanding of your potential ROI, many vendors offer detailed pricing information and ROI calculators. Check out Concord’s pricing details to learn more about how their solution scales with your needs.

Conclusion: A balanced approach to legal AI

The key to successful automated contract summary software implementation in legal departments isn’t finding a silver bullet solution—it’s developing a balanced approach that combines the right tools with thoughtful implementation.

The most successful legal teams are neither AI skeptics nor enthusiasts—they’re pragmatists who understand both the capabilities and limitations of current AI technology. They focus on specific problems where AI can deliver measurable value, implement solutions with proper oversight and training, and continuously evaluate and refine their approach.

By adopting this balanced perspective, your legal team can harness AI’s potential while avoiding its pitfalls, ultimately delivering better, faster, and more cost-effective legal services to your organization.

Ready to see these principles in action? Request a demo of Concord’s AI-powered contract management platform today.

AI for Legal Ops: The 2025 Guide to Implementation

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The reality of AI adoption in legal departments