What Are the Main Application Areas of AI Artificial Intelligence?
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AI artificial intelligence has entered a wide range of markets. Here, we share 11 key application areas:
AI in Healthcare. The biggest bet is improving patient outcomes and reducing costs. Companies are applying machine learning to make better and faster medical diagnoses than humans. IBM Watson is one of the most well-known healthcare technologies. It understands natural language and can answer questions posed to it. The system mines patient data and other available sources to form hypotheses, which it then presents with confidence scores. Other AI applications include using online virtual health assistants and chatbots to help patients and healthcare customers find medical information, schedule appointments, understand billing processes, and complete other administrative tasks. A range of AI technologies are also being used to predict, combat, and understand pandemics like COVID-19.
AI in Business. Machine learning algorithms are being integrated into analytics and customer relationship management (CRM) platforms to uncover insights on how to better serve customers. Chatbots have been incorporated into websites to provide immediate service to customers. The rapid advancement of generative AI technologies like ChatGPT is expected to have far-reaching impacts: eliminating jobs, revolutionizing product design, and disrupting business models.
AI in Education. AI can automate grading, giving educators more time for other tasks. It can assess students and adapt to their needs, helping them learn at their own pace. AI tutors can provide additional support to students, ensuring they stay on track. This technology could also change where and how students learn, potentially even replacing some teachers. As demonstrated by ChatGPT, Bard, and other large language models, generative AI can help educators create coursework and other teaching materials, engaging students in new ways. The emergence of these tools has also forced educators to rethink student assignments and testing, as well as revise plagiarism policies.
AI in Finance. AI in personal finance applications, such as Intuit Mint or TurboTax, is disrupting financial institutions. These apps collect personal data and provide financial advice. Other programs, like IBM Watson, have been applied to the home-buying process. Today, AI software performs much of the trading on Wall Street.
AI in Law. The discovery process in law—sifting through documents—is often overwhelming for humans. Using AI to automate labor-intensive processes in the legal industry can save time and improve client service. Law firms use machine learning to describe data and predict outcomes, computer vision to classify and extract information from documents, and NLP to interpret information requests.
AI in Entertainment and Media. The entertainment industry uses AI technologies for targeted advertising, content recommendations, distribution, fraud detection, scriptwriting, and film production. Automated journalism helps newsrooms streamline workflows, reducing time, cost, and complexity. Newsrooms use AI to automate routine tasks like data entry and proofreading, research topics, and assist in headline reporting. How journalism can reliably use ChatGPT and other generative AI to produce content remains debatable.
AI in Software Coding and IT Processes. New generative AI tools can generate application code based on natural language prompts, but these tools are still in their early stages and are unlikely to replace software engineers anytime soon. AI is also being used to automate many IT processes, including data entry, fraud detection, customer service, and predictive maintenance and security.
AI in Security. AI and machine learning top the list of buzzwords used by security vendors to market their products, so buyers should approach with caution. Nevertheless, AI technologies have been successfully applied in various aspects of cybersecurity, including anomaly detection, resolving false positives, and conducting behavioral threat analysis. Organizations use machine learning in Security Information and Event Management (SIEM) software and related fields to detect anomalies and identify suspicious activities that indicate threats. By analyzing data and using logic to identify similarities with known malicious code, AI can provide alerts for emerging attacks faster than human employees and previous technological iterations.
AI in Manufacturing. Manufacturing has been at the forefront of integrating robots into workflows. For example, industrial robots, once programmed to perform a single task and kept separate from human workers, are increasingly serving as collaborative robots (cobots): smaller, multitasking machines that work alongside humans and take on more parts of the workload in warehouses, factory floors, and other workspaces.
AI in Banking. Banks have successfully used chatbots to inform customers about services and products and to handle transactions that do not require human intervention. AI virtual assistants are employed to improve and reduce the cost of regulatory compliance in banking. Financial institutions leverage AI to enhance loan decision-making, set credit limits, and identify investment opportunities.
AI in Transportation. Beyond its foundational role in operating autonomous vehicles, AI technology is applied in transportation to manage traffic, predict flight delays, and make maritime shipping safer and more efficient. In supply chains, AI is replacing traditional methods of demand forecasting and disruption prediction, a trend accelerated by COVID-19 when many companies were caught off guard by the pandemic's impact on global supply and demand.