20 Useful Applications of AI & Machine Learning in Your Business Processes

A 2017 study from Pew Research found that more than 70% of the U.S. is scared that robots are going to take over our lives. And, while we can’t perfectly predict the emergence of a Skynet singularity, we can say with some certainty that technology is set to take over the repetitive, dehumanizing elements of our jobs instead of putting us out of work.

Artificial intelligence (AI) is a strategic priority for 84% of businesses, and in some cases has been used to improve sales team efficiency by over 50%. Even I’ve used AI in the past to generate hundreds of relevant hashtags for social media posts at the click of a button.

It was once the stuff of utopian science fiction and huge enterprises, but now practically anyone can take advantage.

For this post, we will dive into 20 different applications of AI in the real world:

Jump to them by clicking the links below if you want to skip the explanation of what AI and machine learning is:

  • Applications of AI in healthcare
  • Applications of AI in finance
  • Applications of AI in human resources
  • Applications of AI in retail
  • Applications of AI in agriculture
  • Applications of AI in security
  • Applications of AI in energy
  • Applications of AI in education
  • Applications of AI in gaming
  • Applications of AI in social media
  • Applications of AI in marketing
  • Applications of AI in manufacturing
  • Applications of AI in transportation
  • Applications of AI in travel
  • Applications of AI in customer service
  • Applications of AI in law
  • Applications of AI in entertainment
  • Applications of AI in automobiles
  • Applications of AI in government
  • Applications of AI in e-commerce

If you want a bit of background on AI and machine learning, read on before getting stuck in with the use cases.

AI and machine learning: a simple explanation

What is artificial intelligence?

Systems that use AI are able to carry out tasks that are characteristic of human intelligence.


AI enables the kind of decision-making that wouldn’t be possible with the simpler “if this, then that” models most software uses. This includes tasks like:

  • Identifying emotion in text or speech
  • Tagging and classifying documents
  • Understanding emails and replying like a human
  • Writing product descriptions or other formulaic copy
  • Summarizing key points from long text
  • Picking objects out of images
  • Writing unit tests for software
  • Planning projects
  • Beating the world’s top Go player

The AI industry is exploding in size. Many companies ranging from tiny startups to global giants are realizing the benefits of handing difficult or repetitive work over to machines.

While incumbents like IBM and Microsoft are developing AI for the enterprise sector, there are also thousands of startups developing everything from customer support bots to APIs capable of generating hashtags for social media.


A decade ago, the technology was hardly mature enough to be of any practical use. Now, just about anyone can hook up a free AI application to their existing tools and get to work.

One area of AI that’s seen a disproportionately high rate of adoption in recent years is machine learning.

What is machine learning?

Machine learning is an application of artificial intelligence that allows software to learn, model, and make predictions based on the data it is given.

My colleague Ben Mulholland has written an awesome article on machine learning that you can check out for a deep exploration.

As cloud computing becomes more affordable and processing power reaches unforeseen heights, the restrictions that previously made machine learning impossible have fallen away.

Machine learning enables applications to behave in new ways without being freshly programmed. Machine learning applications are programmed with the ability to improve their own code and make optimal decisions based on vast data sets. This includes functions like:

  • Projecting sales figures based on historical data and market conditions
  • Identifying and protecting against suspicious network activity
  • Learning to drive vehicles
  • Improving the efficiency of manufacturing processes by identifying waste
  • Predicting the popularity of content
  • Screening and grading job applicants
  • Making relevant content recommendations, like YouTube and Netflix

It might sound like the domain of experimental teams at big firms like Google. And, while Google has led the way for a number of years, the power of machine learning is available to businesses of any size.


In this article, we’ll look at 20 AI and machine learning applications and use cases to automate work, streamline your business, and put an army of virtual robots to work for you.

Applications of AI in healthcare

Artificial intelligence in the healthcare industry has numerous applications that can improve patient care, diagnoses, and overall efficiency in the industry. For example:

Medical imaging analysis

AI algorithms can quickly and accurately analyze X-rays, MRIs, and CT scans to aid in the detection of abnormalities and diseases.

Personalize treatment plans

Based on individual patient data, AI can develop treatment plans, leading to better and more targeted care. It can also be utilized for drug discovery and development, helping to identify potential new medications and optimize existing ones.

Healthcare management

AI can assist in improving operational efficiency within the healthcare industry by automating administrative tasks, and managing healthcare supply chains.

Predict patient outcomes

Furthermore, artificial intelligence can be used for predictive analytics to identify at-risk patients and prevent potential health complications.

Applications of AI in finance

AI in finance has revolutionized the way financial institutions operate, providing numerous applications that enhance efficiency, accuracy, and decision-making. Some key applications of AI in finance include:

Fraud detection and prevention

AI algorithms and deep learning can analyze large volumes of transactions and identify patterns or anomalies that may indicate fraudulent activity, thus helping to prevent potential losses. These are sometimes called fraud filters.

Customer service and support

AI-powered chatbots and virtual assistants can provide 24/7 customer support, assist in account management, and offer personalized financial advice to customers.

Risk assessment and management

AI can assess and predict market trends, assess credit risk, and optimize investment portfolio management by analyzing vast amounts of data for more accurate decision-making and financial advice.

Algorithmic trading

AI-based systems can analyze market data in real-time and execute trades at high speeds, thereby helping to optimize trading strategies and minimize risks.

Personalized financial recommendations

AI can analyze human behavior and customer spending habits, investment preferences, and financial goals to provide tailored recommendations for savings, investments, and retirement planning.

Applications of AI in human resources

AI has numerous applications in human resources (HR), including:

Recruitment and candidate screening

AI can automate the initial screening of resumes and applications, saving time and effort for HR professionals. It can analyze candidate’s qualifications, experience, and skills to identify the best-fit candidates for a position.

Talent management and workforce planning

Intelligent systems can help identify and analyze skills gaps within an organization, as well as predict turnover and identify high-potential employees for development opportunities.

Employee engagement and retention

Artificial intelligence can analyze employee feedback and sentiment through surveys, performance reviews, and other sources to identify trends and patterns that can help improve engagement and retention strategies.

HR analytics and decision-making

AI can process large volumes of data to provide insights for strategic workforce planning, succession planning, and performance management.

HR operations and administrative tasks

AI can automate routine HR tasks such as payroll, benefits administration, and scheduling, freeing up HR professionals to focus on more strategic initiatives.

Applications of AI in retail

AI is being increasingly used in the retail industry to enhance customer experience, streamline operations and improve decision making.

Personalized customer recommendations

Made possible through deep learning algorithms, they analyze customer data and behavior to suggest products that are most relevant to each customer. This not only improves customer satisfaction but also increases the likelihood of sales.

Demand forecasting

AI analyzes historical sales data, market trends, and other relevant factors to predict future demand for products. This allows retailers to optimize inventory levels and reduce excess stock or stockouts.

Inventory management

This helps retailers to better manage their stock levels, reduce waste and optimize supply chain operations and is achieved through AI algorithms that continuously analyze sales data and other relevant factors to make real-time inventory management decisions.


AI-powered chatbots can interact with customers, answer queries, and assist with purchases, providing personalized and efficient customer service.

Applications of AI agriculture

AI has various applications in agriculture, revolutionizing the industry with smart and efficient solutions.

Precision farming

AI assists in analyzing data from sensors, drones, and satellites, enabling farmers to make informed decisions about irrigation, fertilization, and pesticide use. This leads to better resource utilization and higher crop yields.

Pest and disease management

AI can identify pests and diseases in crops through image recognition and suggest appropriate intervention strategies, reducing the reliance on harmful pesticides and chemicals.

Crop monitoring

AI-powered systems monitor crop health by analyzing images of leaves and plant growth, detecting deficiencies and diseases at an early stage.

Predictive analytics

Machine learning algorithms can predict weather patterns, market demand, and crop prices, empowering farmers to optimize planting and harvesting schedules and make strategic business decisions.

Supply chain management

AI optimizes the transportation and logistics of agricultural products, reducing wastage and ensuring timely delivery to the market.

Autonomous machinery

AI-driven robots and drones can perform tasks such as seeding, harvesting, and spraying with minimal human intervention, increasing efficiency and reducing labor costs.

Applications of AI in security

AI has numerous applications in security, ranging from threat detection to biometric authentication.

Threat detection

Using deep learning techniques, AI algorithms can analyze vast amounts of data to identify patterns and anomalies that may indicate a security threat. This can include detecting unusual network traffic, identifying potential cyber attacks, and flagging suspicious behavior.

Biometric authentication

AI-powered biometric systems can accurately identify individuals based on their unique biological characteristics, such as fingerprints, facial features, and voice patterns. These systems are increasingly being used in access control and identity verification applications.

Video surveillance and monitoring

AI-powered video analytics can automatically detect and alert security personnel to potential threats, such as unauthorized access or suspicious activities.

Applications of AI in energy

AI is being leveraged in various applications within the energy sector to optimize operations, improve efficiency, and reduce costs. Let’s dive into these further:

Energy management

AI is used to optimize energy consumption by analyzing patterns and predicting demand, thus enabling better management of energy resources and reducing wastage.

Power grid optimization

AI algorithms help in optimizing the power grid operations, predicting equipment failures, and identifying potential issues, ultimately leading to more reliable and efficient energy distribution.

Renewable energy integration

AI is utilized to forecast renewable energy production, such as solar and wind, helping in the integration and management of fluctuating energy sources into the grid.

Energy storage solutions

Artificial intelligence is being used to optimize energy storage solutions by enhancing the efficiency of battery systems and predicting energy demand to ensure a stable energy supply.

Smart energy systems

Artificial intelligence applications are applied to develop smart energy systems that can monitor, control, and optimize energy usage in homes, buildings, and industrial facilities.

Applications of AI in education

AI in education has wide-reaching applications that are transforming the way students learn and educators teach.

Personalized learning

Using AI algorithms can help identify the unique learning needs of each student and create tailored educational experiences. Intelligent tutoring systems can provide individualized assistance to students, adapting to their pace and style of learning. This allows for more effective and efficient learning experiences.

Automating grading and assessment

Automations assists in reducing the burden on educators and providing faster and more consistent feedback to students. Additionally, AI can help in automating administrative tasks, freeing up educators’ time to focus on teaching and mentoring students.

Creating more immersive and interactive learning experiences

This can be done through virtual reality simulations and educational games. It can also help in providing real-time language translation and transcription for students with diverse linguistic backgrounds.

Applications of AI gaming

Artificial intelligence technology is revolutionizing the gaming industry by enhancing player experience and improving game design. Some applications of AI in gaming include:

Non-player characters (NPCs)

AI is used to create more sophisticated and realistic NPCs that can learn and adapt to player behavior by understanding human language, providing a more immersive gaming experience.

Procedural content generation

AI-based systems can be used to generate game content such as levels, maps, and quests, making games more dynamic and replayable.

Player behavior analysis

AI can analyze player behavior to provide personalized gaming experiences and recommendations, as well as to detect cheating and prevent fraud.

Dynamic difficulty adjustment

AI can dynamically adjust the difficulty of the game based on the player’s skill level, ensuring a challenging but not frustrating gaming experience.

Predictive analytics

AI can analyze player data to predict player preferences and behaviors, allowing game developers to tailor their games to their target audience, and improving the gaming industry overall.

Applications of AI social media

AI has various applications in social media, including:

Content recommendation and personalization

AI algorithms analyze user data to personalize content and recommend relevant posts, articles, and products based on users’ interests and behavior.

Customer service and chatbots

Many social media platforms use AI-powered chatbots to provide real-time customer support, answer frequently asked questions, and engage with users through automated messaging.

Sentiment analysis

AI can analyze user-generated content and comments to gauge public opinion and sentiment, helping businesses and brands understand the public perception of their products and services.

Image and video recognition

AI-powered tools can automatically tag, categorize, and describe visual content, making it easier for users to search and discover relevant images and videos.

Ad targeting and optimization

AI algorithms help social media platforms optimize ad targeting by analyzing user data and behavior to deliver more relevant and personalized advertisements.

Social listening and trend prediction

AI tools can monitor social media conversations to identify emerging trends, predict consumer behavior, and provide valuable insights for marketing and business strategy.

Applications of AI marketing

AI has greatly impacted the field of marketing with various applications, including:

Customer segmentation and targeting

Using neural networks, AI can analyze large datasets to identify patterns and preferences, allowing marketers to understand their audience more effectively and create personalized campaigns.

Predictive analytics

AI can forecast future trends and consumer behavior based on historical data. This helps marketers make more informed decisions about their strategies and investments.

Content creation

Artificial intelligence software has the ability to generate personalized and relevant content for different audience segments. From videos to written content to audios, AI is a massive help in these areas, especially for small businesses.

Lead scoring and nurturing

AI software enables marketers to prioritize and cultivate high-quality leads. These applications of AI in marketing have revolutionized the way businesses connect with customers and drive growth.

Applications of AI manufacturing

AI has various applications in manufacturing that are revolutionizing the traditional methods and streamlining the processes.

Predictive maintenance

AI can analyze machine data to predict when equipment is likely to fail, allowing for timely maintenance to prevent costly breakdowns.

Quality control

Artificial intelligence can automatically detect defects in products and ensure only high-quality products make it to market.

Supply chain management

It can optimize inventory levels, reduce lead times, and improve overall efficiency.

Enhanced safety

AI-powered systems can identify and prevent potential hazards in the manufacturing environment.

Applications of AI transportation

AI is changing the transportation industry forever and has a wide range of applications.

Autonomous vehicle technology

AI is used to enable self-driving cars, trucks, and drones. These autonomous vehicles use AI algorithms to perceive their environment, make real-time decisions, and navigate safely without human intervention.

Traffic management and optimization

It can analyze real-time traffic data to predict and alleviate congestion, reduce travel times, and improve overall traffic flow.

Predictive maintenance

AI is used to monitor the condition of vehicles and infrastructure, detect potential issues before they occur, and schedule maintenance to prevent breakdowns and minimize downtime.

In the railway industry, AI is utilized for predictive maintenance, route optimization, and scheduling to increase efficiency and safety.

Applications of AI in travel

AI offers various applications that enhance customer experience and streamline processes within the travel industry, such as:

Personalized recommendations

This applies to accommodations, activities, and dining based on customer preferences and past behavior. This enhances the travel experience by providing tailored suggestions.

Chatbots and virtual assistants

These provide instant customer service and support, such as booking confirmations, itinerary changes, and travel recommendations, improving customer satisfaction and efficiency in addressing customer inquiries.

Predictive analytics

Within the travel industry, this is used to forecast demand, pricing, and trends, which enables travel companies to make data-driven decisions and optimize their offerings.

Facial recognition technology

This is most often used in airports, which enhances security and expedites the check-in process for travelers.

Language translation and interpretation tools

With things like voice assistants and speech recognition, AI makes it easier for travelers to communicate in foreign countries.

Applications of AI in customer service

Some of the applications of AI in customer service include:


AI-powered chatbots can handle customer queries and provide instant responses 24/7, improving the efficiency of customer service operations.

Personalized recommendations

AI can analyze customer data to personalize product or service recommendations, leading to improved customer satisfaction and increased sales.

Natural language processing

Artificial intelligence can understand and analyze customer inquiries and feedback, allowing companies to gain insights into customer preferences and sentiments.

Self-service systems

AI enables the development of self-service customer service systems, allowing customers to find information and solve problems on their own, reducing the workload on human customer service agents.

Predictive analytics

AI can predict customer behavior and preferences, empowering companies to proactively address customer needs and provide a more personalized experience.

Applications of AI in law

AI applications in law are wide-ranging and can include:

Legal research and analysis

AI-powered platforms can quickly scan and analyze large volumes of legal documents, statutes, case law, and regulations to provide relevant information and insights to lawyers and judges.

Contract analysis and review

AI can be used to review and analyze contracts, identify potential risks or issues, and ensure compliance with legal requirements.

Predictive analytics

AI algorithms can be used to predict case outcomes, sentencing decisions, and litigation strategies based on historical data and patterns.

Due diligence

AI can assist in due diligence processes by analyzing and summarizing large amounts of information, such as corporate records, financial statements, and regulatory filings.

Legal chatbots

AI-powered chatbots can provide legal information, guidance, and support to clients, answer routine legal questions, and assist with form completion and document preparation.

Applications of AI in entertainment

AI in entertainment has forever changed the way content is created, distributed, and consumed. Some of the applications of AI in entertainment include:

Personalized recommendations

Streaming platforms like Netflix and Spotify use AI algorithms to analyze user data and provide personalized content recommendations based on a user’s preferences and viewing/listening history.

Content creation

AI is being used to produce music, art, and even write scripts for movies and TV shows. For example, AI can generate music compositions or create visual effects for movies.

Virtual reality (VR) and augmented reality (AR)

AI is used to enhance VR and AR experiences by creating more immersive environments and interactive elements.

Customer interaction

AI-powered chatbots are used by entertainment companies to provide customer support, answer queries, and engage with consumers on social media platforms.

Applications of AI automobiles

AI has various applications in the automotive industry, revolutionizing the way vehicles operate and enhancing overall safety and efficiency.

Autonomous driving

Using AI, self-driving cars can navigate and make decisions on the road without human intervention. This not only improves safety but also reduces congestion and fuel consumption.

Predictive maintenance

AI algorithms analyze vehicle data to predict potential mechanical issues before they occur, allowing for proactive maintenance and reducing downtime.

Enhanced the driving experiences

Through features like adaptive cruise control, lane departure warnings, and automatic parking assistance, AI makes driving easier and safer. Additionally, AI is used in vehicle design and manufacturing processes, leading to more fuel-efficient and reliable vehicles.

Applications of AI in government

AI has numerous applications in government, including:

Predictive analytics

Using AI to analyze vast amounts of data to predict trends and patterns, which can help government agencies make informed decisions and policies.

Sentiment analysis

Monitoring and analyzing public sentiment on social media and other platforms to understand public opinion on government policies and initiatives.

Fraud detection

AI can be used to detect and prevent fraudulent activities in government programs such as social security, tax, and healthcare.

Chatbots for citizen services

Government agencies can use AI-powered chatbots to provide automated responses to citizen inquiries and provide basic services, thereby saving time and resources.

Security and surveillance

AI can improve security and surveillance by analyzing data from cameras and sensors to detect potential threats and criminal activities.

Natural language processing

Government agencies can use AI for language translation, document analysis, and speech recognition to improve communication and accessibility for all citizens.

Applications of AI in e-commerce

AI is transforming the way e-commerce operates, providing numerous benefits and applications to enhance the overall customer experience, streamline operations, and drive sales. Some of the key applications of AI in e-commerce include:

Personalized recommendations

AI algorithms analyze customer browsing and purchasing behavior to provide personalized product recommendations, enhancing the customer shopping experience and increasing sales.

Chatbots and virtual assistants

AI-powered chatbots and virtual assistants provide customer support, answer queries, and assist in product search, leading to improved customer satisfaction and reduced response times.

Inventory management

Artificial intelligence algorithms can forecast demand, optimize inventory levels, and automatically reorder products, reducing stockouts and overstock situations.

Price optimization

AI tools can analyze competitive pricing, demand patterns, and customer behavior to optimize pricing strategies for maximum profitability.

Fraud detection

AI-powered systems can detect and prevent fraudulent activities, such as payment fraud and identity theft, safeguarding e-commerce operations and protecting customer data.

Visual search

Artificial intelligence enables visual search capabilities, allowing customers to search for products using images, making the shopping experience more intuitive and convenient.

Have you incorporated AI or machine learning into your business processes? If so, I’d love to hear from you. Let me know in the comments. Who knows — you might get featured in an upcoming article.

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