How can AI Make Contract Management Smarter?

Introduction

Introduction

This session focuses on exploring how Artificial Intelligence (AI) can make contract management more efficient and effective. The presentation, led by Adrian Von with insights from their CTO, delves into the potential of AI in enhancing NEC contract management.

Exploring the Role of AI in Contract Management

ChatGPT: Icebreakers and Jokes

The team experimented with ChatGPT to generate some NEC-specific jokes, showcasing its ability to understand and create relevant content.

Understanding ChatGPT

Many industry professionals have experimented with ChatGPT alongside NEC ESS. Despite its imperfections, it often provides surprisingly accurate responses. For instance, ChatGPT can write multiple-choice questions, articles, and answer NEC-related queries with a decent success rate.

The Potential of AI

AI holds the potential to manage and interpret vast amounts of contract data, providing insights and automating routine tasks. However, the complexity of NEC contracts and the challenges of integrating AI with such specialized knowledge cannot be understated.

The Complex World of Construction Contracts

Managing construction contracts involves handling numerous variables, such as subcontractors, notice types, workflows, a massive amount of data, and multi-tiered relationships within projects. The sheer volume of data poses a challenge but also an opportunity for AI to step in.

Practical Examples and Business Case

Using practical examples, the presentation illustrates the potential marginal gains AI could bring. For instance, identifying and interpreting trends from millions of early warnings can lead to significant savings.

Simple Tasks and AI Integration

What AI is Good At

AI excels at repetitive, simplistic tasks and can be trained to handle specific business cases. For example, correctly classifying and tagging communications is still a challenge that AI could help overcome.

Translating NEC Jargon

A significant challenge is that AI services need to truly understand NEC contracts. Using examples and testing, the presentation illustrates how AI could potentially differentiate good, bad, and ugly early warnings.

Implementing AI in Layers

Building a Foundation

The approach involves building an algorithm-based foundation that segments users and their tasks dynamically, accompanied by a simplified NEC dictionary.

Practical AI Applications

Through dynamic segmentation, NEC coaching, and mentoring within the application, the system nudges users to follow best practices. This becomes the guide for implementing AI.

Advanced AI Applications

Anomaly Detection

AI can detect anomalies in contract data, identifying irregularities and offering insights into unexpected trends.

Text Classification and Semantic Analysis

The ability to classify text based on context and sentiment can assist in early prediction of contract issues and improve handling.

Search and Analysis

Like a Google search within the application, AI allows users to query data in natural language, providing quick and insightful answers.

Addressing the Challenges and Limitations

Training AI Models

Implementing AI requires training models specific to the data and use cases in contract management.

Data Privacy and Sensitivity

Ensuring data protection and handling sensitive information within controlled environments remains a top priority.

Future Steps

Phased Implementation

Starting with foundational tasks and gradually moving to complex machine learning and sentiment analysis over a multi-year timeline.

Feedback and Iteration

User feedback and iterative improvements will guide the development, ensuring that AI implementations bring tangible benefits.

Examples and Experimentation

Sample Experimentation

Experiments with internal bots showcasing how AI can quickly analyze data and respond to queries, improving accuracy over time.

Conclusion

AI offers promising enhancements for contract management, simplifying data analysis and automating repetitive tasks, albeit with necessary caution around data privacy and specificity.

Keywords

• Artificial Intelligence
• Contract Management
• NEC Contracts
• ChatGPT
• Data Analysis
• Anomaly Detection
• Text Classification
• Sentiment Analysis
• Phased Implementation
• Data Privacy

FAQ

What is the main purpose of using AI in contract management?

The primary objective is to enhance efficiency by automating repetitive tasks, classifying data, and providing insights through anomaly detection and sentiment analysis.

How does ChatGPT aid in understanding NEC contracts?

ChatGPT can generate relevant content, write articles, and answer queries based on publicly available data, although it sometimes struggles with specificity and nuances.

What challenges are associated with integrating AI in contract management?

Key challenges include the complexity of NEC contracts, ensuring data protection, and accurately training AI models to understand contract-specific semantics.

How does anomaly detection work in AI?

Anomaly detection identifies irregularities and deviations in contract data, which can highlight potential issues and trends that might otherwise go unnoticed.

How is AI implemented in phases?

The phased approach starts with foundational tasks such as algorithm-based segmentation and progresses to complex machine learning and sentiment analysis over time.