AI Use Cases Across Industries

There are AI use cases across industries including law firms, distribution, manufacturing, finance, marketing, and security. They illustrate potential ways to:

Automate workflows

Enable data-driven decisions

Improve customer engagement

Operationalize predictive insights

Apply AI securely and responsibly

Demand Forecasting

Derive actionable insights from customer data


Group customers into cohorts based on common attributes and behaviors

Churn Prediction

Identify customers most at risk for attrition using ML models

Profile Enrichment

Augment records with additional data like demographics and credit information

Campaign Optimization

Boost marketing performance through real-time adjustments

Ad Bidding

Dynamically bid for best positioning based on budget and expected response


Continually try combinations of messaging, formats, channel mix to improve results


Quantify impact of each ad and marketing element on customer actions

Fraud Prevention

Mitigate fraudulent activities across campaigns and transactions

Anomaly Detection

Spot outlier patterns in real-time that could indicate fraud

Scenario Modeling

Isolate factors and data relationships most predictive of fraud

Rule Tuning

Refine fraud detection rules to improve accuracy over time

Customer Intelligence

Derive insights from customer data to personalize engagement


Group customers into cohorts based on attributes and behaviors

Propensity Modeling

Predict likelihood of loan default, investment activity etc.

Profile Enrichment

Augment records with additional data like credit history

Fraud Prevention

Mitigate fraudulent activities across payments and transactions

Transaction Pattern

Spot anomaly patterns indicating fraudulent card use

Identity Validation

Compare user details against verified ID databases


Assign risk scores to events based on potential of fraud


Continuously monitor adherence to financial regulations

Regulatory Update

Track latest regulatory and policy changes requiring attention

Control Testing

Validate existing workflows against updated compliance controls


Suggest changes to processes to address gaps

Legal Research

Ecover evidence and reveal insights

Fact Pattern Analysis

Scan case files to flag relevant facts and match them to applicable laws and precedents

Augmented Research

Proactively surface highly relevant case studies, journal articles and statutes to strengthen legal arguments

Regulatory Update

Continuously monitor changes in laws and regulations and alerts on impacts to existing research


Distill complex legal language into concise summaries and meaningful legal principles

Case Law Analytics

Uncover connections between cases by facts and outcomes to inform litigation strategy

Legal Drafting

Create, strengthen, perfect, and protect legal documents

Draft Generation

Instantly produce draft motions and briefs tailored to case details

Argument Augmentation

Get recommendations on expansions and precedents to bolster legal arguments

Quality Assurance

Ensure document quality, alignment to standards and final human review

Confidentiality Control

Apply stringent access controls to safeguard confidentiality

Risk Identification

Highlight non-standard clauses in contracts compared to databases of reference agreements

Threat Prevention

Proactively identify and mitigate complex security threats

Real-time Detection

Perform high-speed data correlation to uncover anomalies

Risk Scoring

Prioritize threats by potential business impact for accelerated response


Automate containment of attacks through coordination

Fraud Prevention

Leverage machine learning to pinpoint fraudulent activities

Behavior Modeling

Develop profiles of normal vs suspicious patterns in transactions


Assign fraud potential scores to events based on learned models

Scenario Testing

Enable isolation of factors most indicative of fraudulent intent


Continuously audit and provide visibility into security posture

Policy Violation

Flag activities or configurations violating security best practices


Suggest steps to address gaps and improve compliance


Produce audit reports certifying current compliance controls

Intelligent Inventory

Optimize inventory planning, availability and turns

Demand Forecasting

Project future inventory needs by product lines based on historical data


Automate purchase orders and transfers to prevent stockouts

Supplier Integration

Enable data sharing with strategic suppliers to coordinate planning

Automated Order Processing

Accelerate order management with 95%+ accuracy

Data Extraction

Convert order information from emails, EDI feeds into structured data


Check orders for completeness, customer credit status, product availability

Routing & Tracking

Assign warehouse tasks for fulfillment and generates customer shipment notifications

Customer Experience

Boost engagement across the customer lifecycle

Conversational Chatbot

Provides 24/7 self-service access for order status, returns, etc.

Recommender Bot

Recommends relevant products based on the individual’s purchase history

User Analytics

Identify common questions and pain points to improve content and experience

Accounts Receivable

Optimize collections through personalized engagement

Invoice Tracking

Automate tracking payments


Identify past due accounts and initiates contact for resolution

Payment Plan

Suggest customized installment plans based on customer history

The Accounts Receivable Assistant aims to streamline the collections process by.

Predictive Maintenance

Prevent unplanned downtime through data-driven insights

Sensor Analytics

Analyze equipment sensor data to predict potential failures

Maintenance Scheduling

Optimally schedule preventive maintenance during planned production halts

Technician Guidance

Provide real-time guidance to resolve equipment issues quickly

Quality Management

Drive higher quality output and minimizes defects

Visual Inspection

Leverage computer vision to automatically detect product anomalies

Root Cause Analysis

Identify process parameters triggering defects to enable corrections


Continuously tune machining settings to maintain quality specs

Production Planning

Optimize production scheduling for improved efficiency

Demand Forecasting

Combine inputs like orders, inventories, and trends to project output requirements