Machine Learning

Five Benefits of Machine Learning for Business Processes

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The role of AI has become more enhanced over the years, as its solutions become more refined and easy to implement. AI and machine learning applications have provided solutions for businesses irrespective of their sizes and the industries in which they operate. But with the increased diffusion of these systems, companies need to be smart about adopting advanced IT solutions and evaluate how they can augment their capabilities.

At present, there are a number of tools and applications available that can perform a multitude of functions. From IBM Watson’s different AI tools to Google’s TensorFlow which is used for developing machine learning based applications, there is an abundance of ML tools available. However, businesses must understand what tools are needed for each purpose individually. Some of the benefits offered by ML to businesses include;

Customer Service

This is perhaps the most well known and common application of AI and machine learning. There are now tools available that use Natural Language API to gauge entire personalities, opinions and preferences from simple customer interactions. These insights further help in delivering top of the line customer services. Additionally, machine learning tools are also available for managing customer service functions through chatbots. These bots can answer questions and queries within seconds without causing any lag in the process.

Marketing and Sales

ML tools for sales have allowed businesses to better manage leads and interact with clients more efficiently. Through algorithms that can evaluate customer data through purchase patterns, product surfing history and their interactions with the company to generate valuable insights for designing targeted campaigns. This data can also be used to develop long term relations with clients, thus focusing on providing value-based care.


Accounting procedures have perhaps been the easiest to automate. However, machine learning systems are giving attention to detail and developing accounting and invoicing tools that can generate invoices for clients based on their past preferences. This has enabled customization in accounting procedures as well. Such tools use machine learning that allows for better and more efficient processing of accounting procedures. They have also lent increased flexibility and even customization for even small businesses to maintain their financial records in a more transparent manner.

Digital Security

AI and ML-based systems have enabled better security structures for businesses. Machine learning algorithms are available that use behavioral analytics to detect fraudulent transactions in a client’s account. These tools have significantly reduced the number of false positives that were a hallmark in legacy systems. Other ML fraud detection systems use online identity proofing of customers through document verification and biometric authentication methods to authenticate the identity of a customer. Fast and efficient processing of financial transactions has made it easier for businesses to eliminate the vulnerabilities in their security systems and investigate irregular transactions.


Google is known to use machine learning algorithms to optimize its search results for user convenience. Similar ML algorithms can be used in SEO tools to evaluate the traffic on a website and to look for factors that can improve the website’s ranking.

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