With the ability to quickly analyze huge amounts of data, businesses today can enhance customer interaction and drive workflow efficiency.
From voice assistants to face recognition, active listening, and virtual reality, artificial intelligence is booming. According to Traction, a market analysis firm that focuses on human interaction with technology, the annual global artificial intelligence sales will be increasing in 2025.
Equipment exploits artificial intelligence (AI) algorithms that use machine learning – machine learning to exploit these massive data sets. The devices are then ordered to analyze that data to answer questions. System of learning machine – machine learning – then continue to add to the sample train. Every photo that the computer determines, true or false, is added. The program will increasingly upgrade its “intelligence” after each mission completion over time.
10 extensive applications of AI
Many technology experts emphasize that AI capabilities have not yet caught up with human skills overnight. The main application cases in 2018 will involve helping businesses make decisions with the huge data blocks they have.
Here are 10 typical use cases for AI that have played an important role in today’s business world:
IT security: AI can analyze millions of files and identify which files contain malware. AI can also look for end-user patterns in how they access the cloud to identify anomalies and predict security threats.
Financial transactions: Based on historical trends, AI can predict when to buy and sell securities and then execute transactions at high speed and high volume so that investors can lock in buying and selling prices.
Healthcare: Machine learning algorithms can process more information and detect more patterns to understand the pathogens and the risk of disease in large populations.
Insurance: Businesses can predict customer needs by identifying life events and predicting how those events will impact insurance needs.
Marketing: In this area, AI has been well developed and will continue to be expanded. Companies can deliver personalized online ads, emails, direct mail and coupons, based on end-user Internet activity.
Fraud detection: AI can detect potential fraud cases in different types of online credit card transactions. Technology will compare millions of transactions and find the difference between legal and fraudulent activity.
Personal assistants: Google, Amazon and Apple’s assistants are already popular in the home. Chat interfaces will also become increasingly popular when interacting with technology in a business environment as voice assist interaction is added to the dashboard on screen.
Customer service: A machine learning algorithm with natural language processing can replace customer service staff, authenticate customers with their voice and quickly transfer them to the right information. need or a suitable support person.
Legal: The natural language processing system can translate legal documents into client-friendly languages and help lawyers categorize information to prepare for hearings.
Manufacturing: Wi-Fi and networking devices can collect data from the supply chain as well as from product design data, development, production, distribution and product experience points. – customer touchpoint – to build a detailed database to improve workflow efficiency.
To succeed with AI requires a clear strategy
As big data application cases continue to expand, many businesses are beginning to seriously invest in AI development and integration. This technology has been somewhat exaggerated in 2017, but in 2018 we have and will continue to see real strides to harness the full potential of AI. The robotization of manual work of workers is already felt in the automotive industry and the growth rate of AI-based systems is expected to increase from 8% in 2015 to 109% in the year. 2025.
At the same time, it is important to realize that AI will not be a “cup” that can help all businesses change immediately. While Google, Apple, Facebook, and the auto industry can make AI look easy, inexperienced companies and deep tech resources won’t see the same results right away.
But in 2018, we will begin to see more use cases of AI power in smaller businesses. As more money is poured into AI projects and as the pace of technological change continues to rise, many business leaders in the related field are forced to act with increasingly urgent priorities. Being behind competitors in applying AI to deliver value to customers can be a strong motivating factor!
As is the case with emerging technologies, some AI projects may fail. In addition to the technological challenges, the size of the investment and the ability to manage data provided to AI will greatly affect the level of success that a business can achieve. Projects most likely to thrive are those that are backed by a clear strategy and the results achieved must be within the specified roadmap.