Implementing Artificial Intelligence in Enterprises
Artificial Intelligence is and will continue to be a valuable component of machines because it enables them to learn. Machines are designed to help people accomplish different tasks; the more machines learn, the more they will contribute to improving the lives of their users. Online customer service systems are an example of an everyday use of Artificial Intelligence; it could take a long time before a human representative of a company could talk to us over a phone, AI steps in to facilitate the work of operators, attending clients’ queries quickly and effectively.
If AI is to truly make our lives better, it must be implemented in the areas that most affect our lives, such as the working environment. According to the CIODIVE study, 6 in every 10 employees hope that within the next three years AI will help them in their tasks at work. AI support tools in enterprises will increase working efficiency, reducing spending and increasing profits. There are countless companies who already use AI to increase their productivity. Accenture Consulting, for example, employs AI solutions to make finance- and accounting-related predictions.
Despite continuous advances, 31% of CIODIVE study participants did not know what to answer when asked how they thought AI could facilitate their tasks at work, this points to the need of teaching employees about the correct application of AI at work.
According to GlobalData, low-code applications are an alternative that will make AI more practical, useful and easy to use. Low-code platforms have minimal requirements for manual code development, given that they are constructed and preconfigured. This form of AI is more intuitive and accessible for people with no previous experience of using such tools.
Air Institute promotes the study of Artificial Intelligence and its application in both personal and professional dimensions. We strive to make AI simple and accessible to everyone. Our projects are crucial for the development of AI in the business field, we design algorithms for client analysis, facilitating decision-making in enterprises.