Yair Green GlobalDots, CTO of artificial intelligence and machine learning how to change the software as a service industry are explained.
He said that software as a service (SaaS) is not easy, because SaaS is a concept involving many components. SaaS vendors have developed to the point of managing their own software, without having to install, because the software is through the global Internet (through cloud platform) immediate distribution. Cloud computing enables organizations to consume computing resources on the Internet in the form of Gongyongshiye company, like water or electricity consumption of the same. Despite the different departments at different speeds steering SaaS model, but SaaS-based cloud model now provides businesses with significant efficiencies and cost savings. Technically, SaaS cloud delivery is dependent on a large scale, widely available connectivity and enterprise-level security minimal.
And SaaS will not stand still. As part of this continuing development, artificial intelligence and machine learning will play their respective roles, because they have become an integral part of the SaaS space. 
data collection
In the past, companies have to distribute software to consumers and customers, but did not get an insight about how they use the software, such as which function is in use, which function is not used. Providing "software as a service", the user will also have a lot of data and insights that can help them improve their service. Thus, the user can use this information to provide insights into their customers can better understand usage patterns and, ultimately, can use this data to provide intelligent feedback. SaaS era of big data concept coincides almost everywhere. SaaS can make use of artificial intelligence and machine learning techniques, and software providers in the past era has obvious advantages compared to, because the software vendors now have access to aggregate data from different clients, you can use the data to build a better service.
Now, companies large amounts of data from customers all in one place. Artificial intelligence and machine learning to achieve a more automated mass data processing. According to research firm Gartner Inc. not only quantity, but also to define big data based on its diversity and speed.
Diversity refers to data used to represent different media, depending on the speed of data collection, analysis and speed of implementation. The final reality is that more and more data and IT teams are dealing with a variety of tools to monitor these data, which may mean that there are significant delays in identifying and solving problems. With the rapid growth of data (must capture, analysis and action) challenged the entire field of IT operations, many companies are turning to artificial intelligence solutions more quickly to help prevent, identify and resolve potential problems.
Marketing is particularly suitable for the use of artificial intelligence and machine learning techniques. SaaS data collection company must be relevant and to-date. Data update, the more effective to implement. Large companies can access data collected through loyalty programs and cross-promotional activities, and small companies through customer surveys, online tracking or competitor analysis to obtain the data. Artificial Intelligence / Machine Learning Solutions business is undoubtedly a great opportunity to expand the horizons of potential customers.
Automation Technology
For B2B customer-centric businesses, before artificial intelligence allows more features to automate manual processing components, for example, it enables them to automate many customer experience process, such as training and on-boarding, marketing activities and ongoing customer service. Artificial intelligence is essentially the polymerization large amounts of data (e.g., customer data) and filtered to an automatic process. Customer service platform, such as artificial intelligence, like a chat robot can automatically respond to and resolve customer inquiries, customer service can make other queries. To maintain revenue and reduce customer churn, this is good news, because after a positive customer service experience, customers tend to exhibit higher purchase interest.
Similarly, a negative customer service experience is also a good way to get rid of customers. Supplementary artificial intelligence technology in corporate customer service team can be for convenience, seamless connection between solve problems and experience of staff, typical examples here may include the use of machine learning to automate customer service (especially self-service).
The main users of SaaS experience challenge is remoteness. Artificial intelligence can help reduce this sense of distance, while providing customers with a more satisfying experience. For a machine to take over from humans in the hands of the machine, there is a lot of headaches, automation and artificial intelligence will bring in almost all their working lives. However, a more likely scenario is that, when deployed in conjunction with the staff, artificial intelligence will bring the greatest value. SaaS can and should manage those interactions may be processed automatically (traditional SaaS) and requires manual intervention interaction, artificial intelligence, human-computer interaction can be enhanced to promote the SaaS interaction. 
Personalization
Natural language processing and machine learning enable SaaS companies can greatly facilitate personalized. Moreover, consumers have become increasingly demanding, they want to provide a personalized experience based on their specific needs. Artificial intelligence can help analyze the behavior of its users by providing previously, and in-depth understanding of the user's preferences and interests. This allows enterprises to configure the user interface to provide important customized experience.
In the process of adoption of new capabilities in artificial intelligence will also provide assistance to consumers, if you want to install more complexity in the consumer application or interface, it will be a great help. Moreover, in addition to helping enterprises to develop more personalized e-mail activities, artificial intelligence can also support voice control and other functions, in order to more accurately track user behavior (to return to the individual user interface).
Artificial intelligence and machine learning have been subverted in various industries, and will continue to subversion. Their long-term use has unlimited opportunities. Looking to the future, SaaS industry, too.