Artificial intelligence use cases can help organizations make a difference in a variety of ways. They can streamline processes, reduce mistakes, and improve productivity.
Several areas of the business can benefit from AI use cases, including finance, healthcare, education, and more. But before companies can reap the benefits, they must first ensure that their AI systems are working optimally.
Predictive healthcare applications that analyze data on patient visits to the clinic, medications prescribed, lab tests and procedures performed in the past can help physicians and healthcare facilities improve efficiency. They can also identify potential health problems in real time and recommend appropriate preventative care measures.
AI has many use cases in healthcare, especially in areas that require data analysis and the ability to process complex information at multiple levels. These include AI capabilities that can examine medical imagery, such as CT scans and MRIs.
The ability to automatically extract data from visual diagnostics can help hospitals and physicians diagnose a wider array of illnesses at earlier stages, reducing patients’ risk of complications. As a result, AI adoption across healthcare stands to benefit all stakeholders — from patients to healthcare providers to payers.
Another key use case is using artificial intelligence to help emergency dispatchers recognize cardiac arrest calls. By using ML to examine the caller’s description of their symptoms, AI could potentially reduce the number of calls that go unanswered and ultimately save lives.
The agriculture industry is one of the most important sectors in our world. It produces food that fuels the economy, yet it faces several challenges including climate change and labor shortages.
Artificial intelligence (AI) has the potential to help the agricultural industry overcome these problems and achieve efficiency, resiliency, and sustainability. Here are 5 AI use cases that will help agriculture excel in the future:
Influence on business
Robotic systems for weeding and plant classification in the field can substitute many human workers, increasing the efficiency of farms while saving the environment. They also work more accurately, minimizing damage to harvested products.
Real-time surveillance and security monitoring for remote farms is another current use case of AI in agriculture. AI algorithms compare satellite images with past data to detect animal or human breaches that may destroy crops. The system then sends alerts to farmers on their smartphones so they can take necessary measures.
AI-powered chatbots can quickly answer course-related questions and help students with their homework. This can free up time for educators to focus on other duties such as grading assignments and planning lessons.
Artificial intelligence can also be used to analyze student essays and long-form answers, map them to traditional grade levels and generate a score for it. This can reduce the time spent on grading and improve the quality of education.
Various educational organizations use AI language models to grade essay and other written work. These algorithms can identify errors and improve content if they find them.
Another important AI use case is speech recognition technology, which can transcribe lectures and help students who have hearing disabilities or who need additional support. This allows more diverse learners to participate in classrooms around the world and learn at their own pace.
AI can be applied to business in many ways, such as optimizing supply chains, customer service or marketing. It can also be used to improve a company’s ability to manage data and analyze it.
AI uses advanced algorithms to process large amounts of data and make predictions about it. These algorithms are often called machine learning.
ML models learn from experience to improve their performance and adapt to new circumstances. Using progressive learning, these models can learn to perform tasks that would have previously required human input.
For example, self-driving cars and AI concierges use ML algorithms to recognize objects and traffic signals and respond accordingly. They also help companies offer customers personalized promotions based on their previous online purchases.