Artificial Intelligence Impact On Business- Benefits Of AI As A Service


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Artificial intelligence impacts business

AI technologies have found their way into almost every business. Artificial Intelligence impact on business has changed the work atmosphere. The most important AI technologies include speech recognition, chat boards, image recognition, sentiment analysis, and natural language generation. Each of these AI technologies is an extensive topic in itself and includes hundreds of underlying features. The businesses can mix these features with advanced applications and hence, increase their value. You should also know the benefits of AI as a service.

For example, a robot might use the features of speech recognition, video recognition, and image recognition technology on the job. With the help of the image recognition software, it would be able to check their placement, price, and quantity of stock on shelves. The video recognition software would help to avoid the obstacles. Lastly, the speech recognition component would facilitate it to communicate and entertain the customers. But before all this, you should know what is artificial intelligence and what are the benefits of AI as a service.

Here are the major impacts of Artificial Intelligence on business:

Image recognition

Businesses are using image recognition in various ways. These ways include-

  1. Generating demand estimates in insurance
  2. Inspection on factory lines
  3. Counting people
  4. Controlling the manufacturing processes
  5. Identifying objects within different images
  6. Entering the store
  7. Detecting events

Researchers have figured out how to break a picture into a grid of pixels and each pixel can be represented as a number. Earlier, people used to describe the brightness of each picture using a single number, but later it was discovered that we could use three or more numbers for the brightness of different colors in each pixel.

In the 1960s, researchers began exploring the use of image recognition to identify characters in digital documents using primitive forms of optical character recognition software. Other researchers also started to explore techniques to interpret schemes based on images that could help in reconstructing 3D worlds from 2D pictures. Now, these techniques have become a part of the machine vision industry.

Later, researchers also discovered that the phenomenon of image recognition could be organized as a hierarchical process. Such a process can make it easier to interpret the complex phenomena. For example, the black and white pixels can be identified as squiggles and lines, which are recognized as part of numbers and digits. This helps you to know the benefits of artificial intelligence in business.

Speech recognition

Algorithms help to translate human speech into text and make it ready for digital processing. Even when speech recognition systems are getting better, they are prone to errors. So, it is important to verify these systems before using them in safety fields like health care. The researchers developed the first speech recognition systems for identifying the single digits in 1952 at Bell Labs. In the mid-1980s, the researchers even started using various statistical techniques like The Hidden Markov models to develop applications that could understand 20,000 words, with pauses between the words.

 In 1990, the first consumer dictation product, called dragon dictate was released, and it could automatically type the spoken text. But these early systems had small vocabularies and hence, required extensive training. At the start of 2010, researchers even found different ways to apply neural networks to speech recognition. The incentive for this growth was the need to find better ways to exhibit the vocal characteristics of different speakers. Now, researchers are also merging the basic speech recognition results with better context to differentiate between the homonyms. The cloud services provide a variety of speech-to-text services that can help in enterprise workflows.


Eliza was the first chatbot and was developed at the MIT artificial intelligence laboratory from 1964 to 1966. These AI technologies allow the software to interact with humans candidly. However, the earliest chatbots were allowed limited vocabulary and interactive activities. This software made use of a decision tree that preceded down various paths based on the users’ answers to a question. These techniques were further strengthened to automated telephone applications in which the conversation was controlled with the help of a dial tone or simple vocabularies, using interactive voice response technology.

The popularity of chatbot applications has augmented nowadays, due to better natural language processing features. These technologies help in interpreting and responding to the texts. Due to better integration with other services, the businesses make use of automatically set up chatbots that can converse and respond to the FAQs or take orders from the users. The development of application programming to represent the users’ intent and appropriate response is one of the best examples of chatbot applications. Externally facing chatbots also facilitate the branch to reach out through various social media channels like Facebook and Instagram in a more interactive way.

Natural language generation

In this era of digitalization, the data is evolving at a huge speed and thus, makes it difficult to prioritize the right information for the customers. Natural language generation or NLG software helps to organize and summarize the appropriate information for the given user. This AI technology can be used in different ways in businesses. A new category of applications known as augmented Analytics makes use of Natural Language Generation as a front end to business intelligence. These technologies take queries and generate appropriate conclusions of analysis in simple English. 

For example, an NLG application was built by USAA to improve the answers given to the business users about different insurance products and their sales This AI technology also helps to ameliorate how the product information is given to the users. This national language generation engine can customize the description of the product based on the users’ needs and preferences. For example, a technical user would be given an insight into the technical properties of the product, like a new phone headset. On the other hand, a fashion enthusiast would be described as the looks of the product.

Sentiment analysis

In the 1950s, the field of sentiment analysis was initiated with marketers assessing the tone of written paper documentaries. Now, virtually everyone writes the digital sentiment of their writings on social media, blogs, news articles, comments, etc.

Artificial intelligence impact on business

Thus, artificial intelligence impact on business combines a variety of techniques and algorithms which are tailored to the specific parts of a task. Such techniques may involve symbolic processing, Neural Networks, statistical analysis, etc. By now, you should know the role of artificial intelligence in business and the benefits of artificial intelligence in business.

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