What Are the Various Applications of Artificial Intelligence?
Can anyone say various application of artificial intelligence? Originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world.
AI can be used among different industries. The number of possible use cases is huge! What they all share in common is data. Lots of data. Artificial Intelligence can support tasks related to this data: its processing, analyzing, finding patterns, building predictions, etc.
AI can be used across different industries. Let’s see some possible use cases of the AI in e-commerce, healthcare, customer support, telecoms, and HR:
AI in E-commerce
Users often abandon e-commerce experiences because the search results displayed are irrelevant. Artificial intelligence or, to be more accurate, natural language processing (NLP), helps narrow search results to find the most relevant results. Also with the voice search (that is estimated to be 50% of all searches by 2020).
Netflix says that 80% of content watched by their users is based on the algorithmic recommendations. AI is capable of analyzing customer behavior on websites and processing big data. With behavioral targeting methods, AI is able to nurture potential leads at the early stage, personalize pricing, or give suggestions regarding offering discounts to a certain customer. It’s worth to mention that 59% of shoppers who have experienced personalization think it has a big influence on their purchase decisions.
Responding to queries by chatbots.
If the question is fairly simple, the system generates an answer that is relevant to the customer and when it’s more complex, the bot will identify the right specialist to handle it and forward the message there.
Creating product descriptions.
The text-generating system created by OpenAI can write page-long responses to prompts, mimicking everything from fantasy prose to fake celebrity news stories and homework assignments. Its creators decided not to release it due to concerns about malicious applications of the technology (source: This AI is so good at writing that its creators won't let you use it), but anyway - with the AI-based text generators, thousands of product descriptions, unique and optimized for SEO, could be created within minutes.
Filtering fake reviews the way that Amazon does
Their system boosts the weight of verified users’ reviews, those marked as helpful by other customers, and more up-to-date reviews.
Analytics and predicting sales
AI can collect data, study patterns, and predict things. Basing on the historical data of the users and the behavioral patterns, it is able to project future buying decisions, increasing companies’ revenue.
AI in Healthcare
Administrative workflow automation
Solutions such as voice-to-text transcriptions combined with NLP and structuring the information into a report can save a lot of doctors’ time.
It’s not a secret that some hospital consultations are not emergency situations. People feel bad, they’re worried or scared, they want to know what’s going on - AI could analyze your symptoms and assess whether you need to visit a doctor or there is nothing to worry about.
Robotic surgeries are considered minimally invasive as they allow replacing large incisions with a series of quarter-inch incisions and utilize miniaturized surgical instruments. It is estimated that this technique can lead to a 21% reduction in the length of patient’s post-operation hospital stay.
In 2018, there was a famous study published by a leading cancer journal. The researchers from the USA, Germany, and France trained a deep learning convolutional neural network (CNN) to identify skin cancer. To achieve that, they fed the network with more than 100 thousand images of malignant melanoma, as well as benign moles. The researchers compared the performance of AI to that of 58 international dermatologists and found that AI made fewer mistakes: it missed fewer melanomas and misdiagnosed moles as malignant less often.
Wearable health and fitness monitors are more and more popular, and there’s also a whole variety of apps tracking our daily activities. Right now, these solutions provide us with insight into how much we move, how many kilometers we walk, how fast we run, how many calories we burn, what our heart rate is. In the future, they may be able to analyze that data, share it with your doctor and even provide alerts in case of some health issues.
AI in Customer Support
24/7 customer service
When the customers contact the helpdesk, they want to get help as fast as possible. And a lot of the questions can be answered… by a bot. And if the question is too complex, thanks to NLP, it would be able to link the question with the right agent.
Personalized customer experience
AI-driven customer service solutions provide insights into customer behaviors. This information combined with machine learning allows you to build actionable customer service.
A chatbot that can tell when a person is getting frustrated and adjust its tactics accordingly – either by changing the tone, offering a special deal, or seamlessly forwarding the conversation to a human consultant.
AI in Telecoms
Basing on customer behavior and the analysis of the product choices of users who followed similar behavioral patterns, recommendation engines are able to provide users with more accurate product recommendations.
Predicting which clients are the most likely to churn gives the agents a chance to prevent it by contacting them and presenting a better offer.
AI in HR
Processing the CVs
AI can eliminate candidates who don’t meet the requirements. And it does it not by screening the CV, as most of the recruiters would do trying to go through hundreds of them, but by reading the entire documents and reducing the risk of accidental elimination of a good candidate.
AI can help help you plan and coordinate training programs for your staff, adjusted to their position, experience, and the training budget. It can also help schedule training in the time frames that are suitable to all staff members.
AI can analyze data about an employee and, comparing it to other data available, identify how likely the worker is to leave the company. It can also identify the reasons that may stand behind such decisions and help you prevent retention.
You can think of similar use cases of AI across many other industries. As long as they have data (about their products, about their resources, about their clients, or about their employees), AI may help them, e.g. improve their ROI, reduce churn, reduce employees’ retention, or predict customer behaviors.
The decision about implementing AI in a company, however, should not be determined by a simple will of “having AI”. In the first place, it has to solve your business problem and help you achieve some specific goals. In order to make it do so, you need to decide what problem do you want to solve with AI and what goals you want to achieve. Should AI make your tests cheaper? Should it make them more reliable? How would you measure that (how would you know that AI implementation is successful)?
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