By 2025, the AI market is poised to grow up to USD 190 billion, predicts research by Markets and Markets.
Over the chaotic cacophony of AI replacing jobs, the benefits it offers cannot be frowned upon. Big giants such as Google, Huawei, IBM, and Microsoft have their separate departments to handle multiple business demands.
Based on Gartner’s 2019 CIO Survey, about 270% of growth in the number of enterprises adopting AI took place within four years.
We may fail to realize but we’re already living in the AI era. As AI gets involved in our daily lives with countless used cases, it is evident to note how AI will lead to increased interest by most of the industries. Thus, job opportunities for AI engineers will be plentiful.
A recent report by Gartner also mentions how 37% of organizations are looking forward to implementing AI strategies. However, for companies to integrate AI strategies into their business must first understand why and how AI will serve the purpose for them. The most important industries with the used cases cover marketing, data, technology, sales, customer services, and security, etc.
- Data Cleaning – with AI’s help, problematic data and records can be easily identified. While it is quite possible for the company to be led by dirty data to reach irrelevant conclusions, it is also possible that through AI-powered data cleaning tools, certain rules can be processed to avoid faulty readings and help the company make better decisions.
- Data Visualization – this is a data exploration technique that helps organizations to comply with better analytics along with better decision making.
- Data Integration – if you’re looking to have a unified view of the data obtained from multiples sources, then you need to have a data integration solution. Data integration simply means obtaining data from different sources to make it usable.
- Internet of Things (IoT) – AI, when combined with IoT, is said to create wonders. IoT according to Gartner is defined as the network of objects (physical) that also have the technology to communicate with the internal and external environment. In short, AI aims at making the networks intelligent and make them self-operated.
- Natural Language Processing (NLP) – NLP is now used in multiple applications across different domains. However, a machine learning algorithm that is programmed with natural language could easily provide information to customers. As an NLP AI engineer, the individual is responsible for designing conversational chatbots and system and ensure it is functional.
- Image Recognition – Image recognition is to help the computer understand and then implement human visual perception. It is an ongoing process, as these algorithms tend to improve, the system will also be able to detect faces and analyze its emotions through the photograph.
- Robotic Process Automation – according to Gartner, RPA is bound to have a positive effect on businesses. Not only this technology promises to be a new development in the business field but it also has the potentiality to offer ROI of 30-200 percent within the first year itself.
- Marketing Analytics – the AI system tend to learn by analyzing and measuring the efforts made through marketing. Such solutions give the PR the insights regarding what prompts the traffic, what drives engagement, and what drives the revenue. Doing so allows the company to offer better results and accurate marketing services to the customers.
- Personalized Marketing – for every company that completely understand their customers are bound to serve them better. For instance, AI is doing a great job by assisting companies and supporting them in providing personalized customer feedbacks.
- Social Media Monitoring – with the help of machine learning, companies can easily optimize the timing of the social media post, the target audience, and the channel.
- Chatbots – as algorithms start improving, chatbots will be able to understand more complicated queries to solve problems. With the help of AI specialists, general templates and dialog trees can be created in a language that helps identify possible issues. These templates can further cover hundreds of possibly correct language constructions.
- Call Analytics – AI is used as an added advantage to improve customer satisfaction rate and efficiency on call data. Such feedback and insights will help improve problems faced during calls.
- Call Routing – the intelligent call routing system helps in identifying the caller and detects the reason for the call upon which the call can be assigned to the right agent.
- Data Security – you can find millions of cyberattacks taking place daily. It is however impossible to prevent all of them, but companies can yet learn from past experiences. Malware has always been an issue for many companies. During the year 2014, Kaspersky Lab detected about 325,000 new malware files almost every day. For such problems, AI algorithms can start looking for patterns in how the data cloud has been accessed. Abnormal anomalies can be reported preventing a data security breach.
- Fraud Detection – scams and frauds can now get detected across different areas. PayPal is one company that has already started using AI algorithms to detect fraudulent activities. AI engineers must be able to apply behavioral profiling analytics to detect fraud. They should also be able to distinguish specialized behavior from generic behavior.
Looking back at the challenges faced by industries today, it comes as no surprise to see how AI is transforming every business.