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Mazenet Solution IT Industry Blog

19 Hot AI technologies in the business sector

Reading Time: 10 minutes

Technology has revamped the way we live today. No one can speak back denying it. Compared to the past generation, current Millenials and the young generation have been standing far thereby using different technologies.  

In the past couple of years, many technologies have revolutionized our lives and it is impossible to live without technology. One such technology is Artificial Intelligence. Being the most happening technology, AI has been transforming the process in several sectors. 

AI impacts in the business area

AI used in business application wanders its uses into automation, data analytics, and natural language processing. Globally, AI has been streamlining in the above-mentioned operations and are improving the efficiencies. 

AI in business

Automation alleviates all the recurring and risky tasks. Data analytics provide businesses with insights that are practically impossible. In addition, natural language processing is used for intelligent search engines, chatbots, and other access devices that promote the convenience of the visually impaired. 

AI technologies to look for in the future 

As AI has become the hottest technology, many technological experts are finding new ways to implement AI in their businesses. By finding new technologies, drives value to the AI and to the business margin too. 

As a result, ample of AI technologies have been bought down into the market. But not all the technologies worth investing in it. There needs a magnifying filter to refine the happening technologies out of the so-called faded ones. 

19 AI technology to watch out,

top AI technologies

Natural Language Generation

Natural Language Generation, an AI discipline to convert data into text. It also enables computers to communicate ideas along with perfect accuracy. 

Natural Language Generation generates reports and summarizes the market happenings. Many companies including Automated Insights, Cambridge Semantics, Lucidworks, SAS, etc. 

Advantages of Natural Language Generation 

When thinking about AI, people’s perception diagonals in the beam which benefits both the marketing and business management too. Here are the advantages of Natural Language Generation.

  • Automated content creation
  • Significant reduction in human involvement
  • Predictive Inventory management
  • Performance Activity Management in the call center

Speech recognition

Every day a plethora of systems have been created and transcribed. Transcribing the human language and reaching hundreds and thousands of individuals with the help of voice-response interactive systems. It is also suitable for mobile apps. Siri comes under one of the systems that understand human needs.

Categories of speech recognition include two parameters. They are, 

  • Dependence of the speaker
  • Recognition style

Dependence of the speaker

Dependence of the speaker mainly denotes the state whether or not they depend on the speaker. It represents that the systems can be trained through a single person’s voice or through the general vocabulary case. Instead of delivering the voice, it is necessary to train the systems accordingly. Based on it, it has also been classified into two types.

  • Speaker independent
  • Speaker dependent

Speaker dependent

With the unique biometric characteristics of the single person, the voice will be processed in the speech manner. Speaker dependent are the types of systems that have been trained by the owner of the system who will be obviously using the system. 

Before using it, train the software by speaking to it thereby analyzing the way the owner actually talks. With the help of speaker-dependent recognition, the accuracy will be high compared to speaker-independent recognition. And, the device also responds to the person who has trained it. 

Speaker independent

Here, the user has to train the systems. According to the general vocabulary, the system recognizes the speech and satisfies their need. Speaker independent software works out well in the business sector. It is not realistic and thus it can be able to practice the phone answer system to their voice. Still, high accuracy limits with some processing points. At the same time, recent developments in AI and speech recognition technology helps in promoting the best output. 

Recognition style

Coming to the recognition style, it has been classified depending upon the utterances who can recognize. Here are the styles pinned down. 

  • Isolated
  • Connected
  • Continuous

Isolated

Isolated form of system recognizes the words separately. The speaker has to give a pause between each word or command. These systems will be trained to recognize or identify the words within 0.96 seconds or less. Thus they come across the easiest method to train and program thereby brings in isolated speech recognition systems that have become common today. 

Connected

In the connected speech recognition system, multiple words run together and thus it needs a minimal pause between them. While comparing to the isolated style, connected style needs 1.92 seconds or less to recognize and respond accordingly. 

Continuous

A continuous recognition system has the ability to recognize the conversational speech that we ought to use in our daily lives.

AI technologies

Virtual agents

Virtual agents are the sort of systems that is not more than a computer agent or a program that helps to interact with humans. Chatbots are examples of virtual agents. They have been created in order to enhance customer service and support measures. As a smart home manager, the virtual agents are rocking their importance in the market bagging up with big results. 

Few companies including Amazon, Apple, and Google are providing virtual agents that improve their customer engagement with the site and the products as well. 

Benefits of using virtual agents

Using virtual agents, the goal of replacing live humans have undergone a change. It is an aid to deliver excellent customer service and satisfy the need for web self-service. There are many advantages to using virtual agents. Here are the advantages for the companies using virtual agents in their sites. 

  • Without any hold, the customer will get a fast and efficient response
  • Lower chances of a language barrier 
  • Integrating the existing systems with the need to download new programs
  • Answering questions all day including business hours
  • With custom-designed avatars, the virtual agents find it more fun and thereby enhances the customer experience
  • Virtual agents help in preventing information overload and helps to generate it. 

Robotic Process Automation

Robotic automation uses scripts and methods that automate human tasks to support corporate processes. RPA can be useful when hiring humans to become more expensive or inefficient. Adext AI stands as a platform to automate the digital advertising process. Using AI, devoting hours are reduced and businesses are saved. 

RPA brings in the solution that helps in stimulating the human talent and helps the employees to move as per the strategies. To make more creative positions, the actions will create a great impact on business growth and its margin too. Advanced systems concepts, Blue Prism, UiPath are examples of robotic process automation. 

Text Analytics and NLP (Natural Language Processing)

In order to understand the structure of the sentences, text analytics has been implemented in many countries. Along with their meanings and intentions, the usage of text analytics differs a lot. With the help of statistical methods and ML, test analytics have been used for security systems and fraud detection. 

A vast array of automated assistants and apps are available to extract unstructured data. Few service providers including Basis Technology, Indico, Knime, Lexalytics, etc have been supplying these technologies with utmost benefits.

Emotional Recognition

Emotional recognition is an advanced AI concept which helps the software to read the emotions on the human face. It can be done using advanced image processing or with the help of audio data processing. As emotional recognition has got a sage, now it is time to capture “micro-expressions. Added to it, the subtle body language cues and the intonation of a betrayed person’s feelings must also be handled in the further emotion recognition process. 

It helps law enforcers to use technology thereby detecting the information about someone. During the interrogation process, a wide range of information can be gathered using emotional recognition. Much emotional recognition AI applications have been widely used to apply facial coding, emotional analytic

Image Recognition

Compared to the emotional recognition, image recognition helps to detect the object or a feature in the digital format. AI increasingly check down the stacked technology and proceed it toward the great effect. The image recognition AI will also help in searching the photos in the social media platform that indulges in a wide data set search. It brings in more relevant during the image searches. 

Image recognition technology will also detect the license, plates, analyze the clients and their opinions based on their faces. It more or less collides with the facial expressions where emotional recognition enters into the phase. Many image recognition systems are there to detect near-duplicates and similar uncategorized images. Various applications have been used in the industry to develop recognition technology. Many processes including bank card verification, picture analysis, and unlocking the images on the web are all possible. 

Marketing automation

AI has benefited the marketing sector with many advantages. Yet, the number of benefits has been increasing. With great faith in AI, the industry brings in a good reason for implementing it in marketing. Around 55% of the marketers are surely implementing AI in their sector. In order to grow revenue faster, marketing automation has been in the digital era. It helps to improve engagement and efficiency in a particular company.

Digital Twin/AI Modeling

A gap between the physical systems and the digital world has been bridged using a digital twin. General Electric, (GE), helps in building AI workforce to monitor and predict failures with the cloud-hosted software. The digital twins are one such designs that aim for 3-D computer-aided design drawings. It is full of interactive charts, diagrams, and data points. 

Many companies are including digital twin and AI modeling technologies in their capital project delivery space.  In order to protect critical infrastructure and Supply Dynamics, Akselos has been introduced. It will be used to develop a SaaS solution to make the raw material sourcing easier. 

Cyber Defense

As known earlier, cyber defense is a computer network defense mechanism that helps in preventing the attacks or threats that occur at a particular infrastructure and information. In the cyber defense sector, both AI and ML are entering into a new evolutionary phase that leads to an increasingly hostile environment. The breaches occurring in the not-so secure world will always tend to increase unless every company indulges in noting down the benefits of the cyber defense. 

In order to process sequences of inputs, cyberdefense combines with the ML techniques. It helps in creating supervised learning technologies to uncover unsuspicious things. Using the cyberdefense combined with AI and ML terms, the user activity detection can round up to 85%. 

Compliance 

When a person or an organization ought to meet the requirement of the practices and legislation methods, then the compliance certification is a must. The compliance industry is a significant industry that upholds the majority of things. It helps in making down the standards, rules, and regulations in the right terms. 

The current world is seeing the first initial wave of the compliance era. It helps in using AI to effectively deliver efficiency through automation and comprehensive risk coverage. AI in the compliance brings in great coverage globally. Using NLP solutions, the regulatory text and the pattern match has become possible with the cluster of keywords. It also identifies the changes that are relevant to the organization. 

With the capital stress testing solutions, the predictive analysis will help the organizations to stay compliant at the capital requirements. The volume of the transaction flagged with the potential things might enroll in the positive stages of the organizational goals. Deep learning has also been used where money laundering has been reduced to apply the business rules sophistically. 

Machine Learning Platforms 

Machine learning platforms are one of the reasons why computers learn easily. Due to the intervention of ML, the systems have become incredibly intelligent. The main goal of machine learning is to develop the techniques to make computers learn. By doing so, the ML platforms are gaining more traction every day. 

Currently, prediction and classification are the main goals that make the ML platform leverage through hurdles. Few companies like Microsoft, Amazon, and Google have been selling ML platforms. Real AI and machine learning can be used to digitally advertise the profitable audience or demographic group. 

AI-Optimized Hardware

With the help of AI technology, hardware becomes much compatible. Along with new graphics and central processing units, the specifically designed structures are easily executed. Mainly, the AI-oriented tasks bring in imminent appearance and wide acceptance over the corporate world. In addition, AI-optimized silicon chips will be inserted into the portable devices and elsewhere. Companies like Cray, Google, and Alluviate have been enabling their clients to get access to technology. 

Decision Management

Now machines have become far more intelligent thereby introducing rules and logic to AI systems. Decision management will include initial setup or training, ongoing maintenance, and tuning methodology. Decision management will comprise a variety of corporate applications that assist and execute automated decisions. It helps in making your business more profitable. 

Deep Learning platforms 

Deep learning platform stands unique in the ML category and thereby involves a pinch of AI neural circuits too. With multiple abstraction layers, the human brain can mimic and process the data necessary for decision making. A deep learning platform helps in classifying the applications that are compatible with large data sets. 

Biometrics

In the biometrics, technology can identify, measure, and analyze human behavior with the help of physical aspects of the body’s structure. Thereby, it allows more natural interactions that allows human and machines to work closer. Few interactions include touch, image, speech, and body language. And, it is big within the market research field. 

Companies like Sensory, Tahzoo, and Synqera are the biometric companies that have been working hard to develop the area of biometrics and safety measures in addition. 

Knowledge worker aid

There are many concerns that are eager to replace people working in their organization. But, it is an essential thing that AI technology has the potential to help employees in their work. According to factual data, the automation of knowledge work has been listed under #2 most disruptive emerging tech trends. 

Sectors including medical and legal fields heavily rely on knowledge. This is the field where AI adoption is on the peak. AI has been used as a diagnostic tool to which more number of companies have been relying upon. Along with AI, companies are focusing on technologies that provide the company with an increased profit margin. 

Kim technologies are one such company aiming to empower the knowledge of the workers who have little IT programming experience. 

Content Creation

Content creation is nothing but a material that helps the people to contribute over videos, ads, blog posts, white papers, and other visual assets. Brands including CBS, USA Today have already been into the AI technology to generate that concent. Many AI-related video production technology has become a significant helping to create new stories based on their data earnings. 

Peer to peer networks

Peer to peer networks is the type of data sharing when more than two PCs are connected and are sharing their resources. Here the shared data will not go through a server computer. Cryptocurrencies also use peer-to-peer networks. The cryptocurrencies have the potential to solve the world’s most challenging problems thereby collecting and analyzing the huge data set. 

Bottom Line

In the nutshell, AI is already re-configuring the digital world. AI technologies reveal various patterns in data. AI technologies have been increasingly leveraging in recruitment decisions. The above said 19 AI technologies are based upon the current scenario. The scenario may become a utopia or dystopia according to the corporate perspective. 

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