AI Driven Contract Review and Risk Assessment Workflow

AI-Powered Contract Review and Risk Assessment

1. Initiation Phase

1.1 Contract Submission

All construction contracts are submitted to the AI-powered system for initial review. This can be done through a secure online portal.

1.2 Data Extraction

Utilize AI-driven tools such as Kira Systems or Luminance to extract key clauses, terms, and conditions from the submitted contracts. These tools employ natural language processing (NLP) to identify relevant information quickly.

2. Review Phase

2.1 Automated Risk Assessment

Implement AI algorithms to assess potential risks associated with contract clauses. Tools like LawGeex can automate the comparison of contract terms against predefined standards and benchmarks.

2.2 Anomaly Detection

Use AI to detect anomalies or unusual clauses that deviate from typical construction contracts. This can be facilitated by products such as ROSS Intelligence, which leverages AI to provide insights and identify potential red flags.

3. Analysis Phase

3.1 Risk Scoring

Assign a risk score to each contract based on the identified risks. This can be accomplished using machine learning models that analyze historical data to predict outcomes.

3.2 Recommendations Generation

Generate recommendations for mitigating identified risks. AI tools such as Clara Analytics can provide tailored advice based on the contract analysis.

4. Review Phase

4.1 Human Oversight

Incorporate human legal experts to review AI-generated insights and recommendations. This ensures a comprehensive understanding of the contract’s implications.

4.2 Final Approval

Once the review is complete, the contract can be finalized for execution. Use electronic signature platforms like DocuSign to facilitate the signing process.

5. Monitoring Phase

5.1 Post-Execution Analysis

After contract execution, monitor compliance and performance using AI tools. Platforms like ContractPodAI can track contract obligations and alert stakeholders of any breaches or issues.

5.2 Continuous Improvement

Utilize feedback from the monitoring phase to refine AI models and improve contract review processes. This creates a feedback loop for ongoing enhancement of the AI-driven tools.