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AI Use Cases
A collection of over 250 uses for artificial intelligence
A continually updated list exploring how different types of AI are used across various industries and AI disciplines,including generative AI use cases, banking AI use cases, AI use cases in healthcare, AI use cases in government, AI use cases in insurance, and more
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AI Use Cases using ML
Crop monitoring and yield prediction
Leading to better crop yields through the use of AI
Soil health monitoring
Soil particulate and composition can be analysed by ML models to provide recommendations for soil improvement
Optimise crops based on soil profile
AI can suggest which crops would be optimal for the analysed soil composition and particulate
Predicting market demand
Satellite imagery and weather data can predict which crops will have done better and therefore market demand
Pesticide optimisation
Reduce the amount of pesticide needed based on data analysis, crop type, soil type etc
Livestock prediction
Tracking numbers of animals and using past breeding habits to extrapolate future livestock numbers
Vehicle health monitoring, breakdown prediction and Predictive maintenance
Suggest decisions like irrigation schedules, pesticide applications, and harvesting times based on real-time data and learned patterns from past seasons.
Driver behaviour analysis and feedback
Provide feedback on observed user driving habits based on collected data. AI driving too close to vehicle in front, not indicating.
Route optimisation
Provide feedback on observed user driving habits based on collected data. AI driving too close to vehicle in front, not indicating.
Identifying plagiarism
Plagiarism can automatically be detected with varying degrees of confidence
Forecast demand
Predict future energy demand based on historical consumption patterns, weather forecasts, and economic indicators, helping utilities optimize resource allocation and grid stability.
Predicts renewable energy output from wind and solar
Predict future energy demand based on historical consumption patterns, weather forecasts, and economic indicators, helping utilities optimize resource allocation and grid stability.
Fault detection in solar panels
Anomaly detection algorithms identify faults and performance issues in solar panel arrays, maximizing energy yield and reducing maintenance costs
Energy consumption optimisation in buildings
Analyse building occupancy patterns, weather data, and energy usage to optimize HVAC and lighting systems for energy efficiency without compromising comfort.
Personalised experiences
Tailors user interactions by analysing preferences, enhancing engagement through customized content suggestions.
Personal or genre music playlist creation
Curates personalized playlists by analysing user preferences and music characteristics, offering tailored listening experiences.
Wildfire prediction
Predict wildfire likelihood based on historic wildfires and predicted temperatures etc
Flooding prediction
Predict flooding from previous flooding records and predicted rainfall
Drought prediction
Predict droughts from previous droughts, seasonal patterns and scheduled weather patterns
Monitoring air and water quality
Monitoring air and water quality using sensors and monitoring systems
Spot suspicious or anomalous transactions
Identify transactions that differ from expected normal activity
Loan decisions
AI can help determine the risk level of loans based on a number of factors
Stock trade algorithms
Stock trade models can be created based on the results of previous trades. The model can even continuously updated and refined.
Investment opportunity analysis
AI can identify investment opportunities in an ever changing financial landscape
Credit scoring
Automated credit scoring can be done by AI taking into account a number of factors
Predicting player churn based on their historical gaming behaviour
Utilizes machine learning to forecast the likelihood of players leaving based on their past gaming patterns and behaviour.
Personalizing offers and bonuses based on player preferences and spending patterns
Tailors promotional offers and bonuses to individual players by analysing their preferences and spending habits.
Fraud detection by identifying unusual betting patterns
Employs machine learning to detect fraudulent activities by identifying irregular betting behaviours.
Forecasting optimal staffing levels for different times and areas of the casino
Utilizes machine learning to predict the ideal staffing levels across various areas and timeframes within the casino.
Customizing marketing campaigns to target high-value players
Adapts marketing strategies to focus on high-value players by analysing their behaviours and preferences.
Identifying VIP players upon arrival for personalized greetings and services
Utilizes machine learning to recognize VIP players upon arrival, enabling personalized greetings and services.
Suggesting games based on player preferences and past gaming history
Suggests games tailored to player preferences and past gaming history, enhancing the gaming experience.
Rewarding players with loyalty points based on their gaming activity
Rewards players with loyalty points based on their gaming activity, encouraging continued engagement.
Suggesting alternative gaming options during peak times to reduce wait times
Offers alternative gaming options during peak times to minimize wait times and optimize player satisfaction.
Diagnosis from patient data
Identifying patterns in patient-reported symptoms to aid in early disease detection
Blood panel analysis
AI analyses blood panel results to identify abnormalities and assist in diagnosing various conditions.
How genes impact health
analysing genetic data to understand how gene variations affect health and susceptibility to diseases.
Genetic marker identification and consideration
Identifying genetic markers to tailor treatments based on individual genetic profiles and reduce side effects.
Drug discovery
Using AI to expedite the drug discovery process by analysing potential drug candidates and predicting their efficacy.
Patient risk prediction
Identifying high-risk patients for specific diseases based on questionnaire data and medical history
Outbreak detection
Using AI to detect and predict outbreaks of infectious diseases by analysing trends in patient data.
Disease infection prediction
Predicting the likelihood of disease infections in populations based on historical data and trends.
Patient insights
Gaining insights into patient health trends and risk factors through comprehensive data analysis.
Recommending relevant clinical trials or research studies based on patient profiles
AI suggests clinical trials or research studies relevant to individual patient profiles, aiding in personalized treatment.
Patient resource prediction
Optimizing healthcare resource allocation by forecasting future patient needs using ML models
Readmission risk prediction
Predicting patient risk of hospital readmission based on ML analysis of questionnaire data
Detecting physical abuse or neglect
Identifying signs of physical abuse or neglect through visual inspection of patient images and past history
Patient scheduling
Optimizing patient scheduling and appointment booking based on clinic availability and patient preferences.
Candidate application and profile analysis
This involves using AI to analyse candidate applications and profiles to identify the best matches for job openings. It enhances the recruitment process by quickly assessing skills, experience, and fit for the company culture.
Performance analysis
AI is used to evaluate employee performance by analysing various metrics and feedback. This helps in identifying top performers, areas for improvement, and making informed decisions on promotions and training needs.
Identify churn risk
Using AI, HR can predict which employees are at risk of leaving the company. By analysing factors such as engagement, satisfaction, and performance, proactive measures can be taken to improve retention.
Categorisation
AI categorizes and organizes large volumes of HR data, making it easier to retrieve and analyse information. This supports better decision-making and efficient HR management.
Employee satisfaction survey analysis
AI analyses responses from employee satisfaction surveys to gauge overall sentiment and identify key areas of concern. This provides insights into employee morale and helps guide improvements in workplace culture.
Workforce planning
AI assists in workforce planning by predicting future staffing needs and optimizing resource allocation. It helps HR to align workforce strategies with business goals and adapt to changing demands.
Insurance policy approval and decline
Streamline the process of approving or declining insurance policies. Use AI to assess risk factors and make quick, accurate decisions.
Insurance premium calculation
Calculate insurance premiums based on various risk factors and customer data. Utilize AI to ensure fair and competitive pricing.
Identify cyber threats and mitigation
Optimize patient scheduling and appointment booking based on clinic availability and patient preferences.
Dynamic cloud resource scaling
Automatically adjust cloud resources based on real-time demand. Use AI to predict and scale resources efficiently.
Predictive policing
AI algorithms for predictive policing to allocate resources more effectively and deter crime
Biometric identification and recognition
Implements AI-powered biometric systems for accurate identification and recognition of individuals, aiding in criminal investigations and border security.
Crime Pattern Analysis
analyses historical crime data using AI algorithms to identify patterns and trends, assisting law enforcement agencies in targeting crime hotspots and allocating resources effectively.
Sentencing Recommendation Systems
Utilizes AI to analyse case data and provide sentencing recommendations to judges, promoting consistency and fairness in the judicial process.
Fraud Detection and Financial Crime Prevention
Implements AI-based systems to detect and prevent financial crimes such as fraud and money laundering by analysing transactional data and identifying suspicious patterns.
Predictive analytics
AI can analyse historical case data to predict the likely outcomes of legal disputes, helping lawyers to strategize and make more informed decisions
Route optimisation for delivery vehicles
AI algorithms analyse real-time traffic data to optimize delivery routes, minimizing travel time and fuel consumption
Predictive maintenance for fleet management
AI algorithms analyse real-time traffic data to optimize delivery routes, minimizing travel time and fuel consumption
Warehouse layout optimisation
AI can simulate different warehouse layouts to maximize storage capacity, streamline operations, and minimize pick-and-pack times
Loading and packing optimisation
AI algorithms can determine the most efficient way to load shipping containers, minimizing wasted space and reducing shipping costs.
Predictive ETAs for shipments
ML models predict estimated time of arrivals (ETAs) for shipments based on historical data and real-time factors like weather and traffic conditions.
Predictive supply chain risk management
ML models analyse various risk factors, such as geopolitical events or natural disasters, to identify potential disruptions and implement proactive mitigation strategies.
Visual defect detection
Identify visual defects in products using AI. Utilize machine learning to ensure high-quality production standards.
Production optimisation
Enhance production efficiency by analysing historical data. Use AI to streamline processes and reduce waste.
Failure prediction
Predict equipment failures before they occur. Use AI to analyse historical data and prevent downtime.
Supply chain management
Optimize supply chain operations using AI. analyse data to suggest the best times for shipping and stocking.
Bottleneck identification
Identify production bottlenecks with AI analysis. Use machine learning to improve workflow and increase efficiency.
Quality control
Ensure product quality through AI-driven inspections. Use machine learning to maintain consistent quality standards.
Email campaign optimization
Optimize email campaigns for better engagement. Use AI to analyse data and suggest improvements for higher open and click rates.
Market analysis and trend prediction
AI can analyse market data, consumer behaviour, and social media trends to predict future market needs and guide product development strategies.
Homelessness prediction
Predicting homelessness risk factors to prevent displacement and provide early intervention
Social service demand prediction
Predicting demand for social services based on demographic and economic indicators
Optimising public service resource allocation
Optimizing resource allocation for public services based on ML-driven demand forecasting
Predicting demand for welfare assistance
analysing historical data to identify trends and patterns in welfare assistance applications
Child welfare prediction
Predicting child welfare outcomes to allocate resources for preventative interventions
Optimising public transport routes
Optimizing public transportation routes and schedules based on ML analysis of usage patterns
Public service fraud detection
Detect people defrauding the state, for example benefit fraud
Energy efficiency assessment
From analysing property features and energy consumption data
Optimise staffing levels
Adjust staffing levels to match customer demand. Use AI to ensure optimal employee allocation for better service.
Inventory management optimisation and forecasting
Optimize inventory levels and forecast demand accurately. Employ AI to reduce stockouts and overstock situations.
Dynamic price setting
Adjust prices in real-time based on market conditions and demand. Use AI to optimize pricing for maximum profitability.
Recommending products
Suggest products to customers based on their preferences and behaviour. Use AI to enhance the shopping experience with personalized recommendations.
Personalised offers
Create tailored offers for individual customers. Use AI to analyse shopping patterns and deliver customized promotions.
Product identification and tracking
Identify and track products throughout the supply chain. Use AI to enhance inventory accuracy and reduce losses.
Material discovery
AI aids in discovering new materials with desired properties by analysing large datasets.
Particle physics simulations
AI simulates particle interactions to help researchers understand fundamental physical processes.
Seismic data interpretation
AI interprets seismic data to predict earthquakes and understand geological structures.
Team or player performance analysis
Utilizes AI to monitor and analyse athlete performance metrics such as speed, agility, and endurance, providing personalized training plans for improvement.
Injury prediction and prevention
Utilizes AI to analyse player biomechanics and historical data to predict and prevent injuries, optimizing training regimes and reducing downtime.
Game strategy optimization
Applies AI algorithms to analyse opponent tactics and game situations in real-time, providing insights to coaches for optimal strategy adjustments.
Athlete performance enhancement
Utilizes AI to monitor and analyse athlete performance metrics such as speed, agility, and endurance, providing personalized training plans for improvement.
Fan engagement and experience
Implements AI-driven personalized fan engagement strategies through targeted content delivery, interactive experiences, and customized merchandise recommendations.
Referee decision support
Utilizes AI-powered systems to assist referees in making accurate decisions by analysing game events and providing real-time feedback on contentious calls.
Talent scouting and recruitment
Applies AI algorithms to analyse player performance data and scouting reports to identify talented prospects and optimize recruitment strategies.
Real-time match analysis and commentary
Utilizes AI to generate real-time match analysis and commentary by analysing game events, player statistics, and historical data.
Equipment design and innovation
Utilizes AI-based simulations and analysis to design and innovate sports equipment such as footwear, apparel, and gear for enhanced performance and safety.
Network performance optimisation
Applies machine learning to optimize network performance and reliability for enhanced telecommunications services.
Predictive maintenance for network infrastructure
Predicts maintenance needs and identifies potential issues in network infrastructure before they cause service disruptions.
Automated network configuration and optimization
Utilizes AI algorithms to automate the configuration and optimization of network settings for improved performance and efficiency.
Network Security Threat Detection
Utilizes AI techniques to detect and mitigate cybersecurity threats in telecommunications networks, safeguarding against attacks and breaches.
Dynamic pricing and service bundling
Applies AI algorithms to analyse customer behaviour and market trends, enabling dynamic pricing strategies and personalized service bundles.
Route optimisation
Utilizes machine learning to optimize the most efficient paths for transportation routes.
Estimating arrival times
Predicts arrival times using machine learning techniques for capacity planning.
Traffic management
AI-based systems for real-time traffic monitoring and congestion management.
Demand forecasting
Predicts future transportation demand using AI algorithms for better resource allocation.
Autonomous vehicles
Utilizes AI technologies to enable self-driving vehicles for safer and more efficient transportation.
Predictive maintenance
AI-driven systems for predicting maintenance needs in transportation infrastructure and vehicles, reducing downtime.
Fleet management
Optimizes fleet operations and scheduling using AI algorithms to enhance efficiency and reduce costs.
Dynamic pricing
Adapts pricing strategies in real-time based on demand and supply insights derived from AI analysis.
Emissions reduction
Applies AI techniques to optimize fuel consumption and reduce emissions in transportation systems.
Safety enhancement
Utilizes AI for real-time analysis of driving behaviour and road conditions to enhance safety measures in transportation.
Predictive maintenance of tourism facilities
Forecast maintenance needs of facilities to prevent issues. Use AI to ensure optimal operation and reduce downtime.
Tourist behaviour analysis
analyse tourist behaviour to optimize services and offerings. Use AI to gather insights and tailor experiences.
Species counting
Accurately count wildlife populations using AI. Utilize machine learning to process data from images and videos.
Species identification
Identify different species in various habitats using AI. Employ machine learning to analyse visual data and classify species.
Endangered species detection and tracking
Detect and track endangered species to aid conservation efforts. Use AI to monitor movements and ensure their protection.
Habitat mapping
Create detailed maps of wildlife habitats using AI. Employ machine learning to analyse satellite images and geographical data.
Animal behaviour analysis
analyse animal behaviour patterns using AI. Use machine learning to study movement, feeding, and social interactions.
Poaching prevention
Detect and prevent poaching activities with AI. Utilize machine learning to analyse patterns and identify potential threats.
Wildlife health monitoring
Monitor the health of wildlife populations using AI. Use machine learning to detect signs of disease and malnutrition.
Environmental impact assessment
Assess the impact of environmental changes on wildlife. Use AI to analyse data and predict future effects.
Migration pattern analysis
Study migration patterns of wildlife using AI. Employ machine learning to track and predict migratory routes.