Artificial Intelligence (AI) and Machine Learning (ML) are becoming an integral part of our lives, at work or home. Enterprises use AI and ML to streamline the business processes and help employees become more productive.
AI and ML are used by social media sites, search engines, and OTT platforms to assist users in finding what they want. At home, we use AL-based voice assistants like Alexa, Siri, and Google Home Assistant for several purposes.
As days pass, we see ML being extensively adopted by businesses. North America grabs the first place for ML adoption, with 80% of the companies using artificial intelligence and machine learning in some way or another. According to GlobeNewswire, the global market value of machine learning is said to touch $117 billion by 2027 at a CAGR of 39%.
So, what do companies use machine learning for? Why are AI and ML so crucial in today’s scenario that it has become necessary to invest in machine learning to stay competitive? Let’s find the answer to this question and more.
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Machine learning is a subset of artificial intelligence. It analyses data sets to trace patterns and identify trends that are otherwise difficult to find. It allows a business to automate data analytics and save resources.
Businesses have become customer-centric, thanks to the increasing competition. Understanding what the customer wants is essential if you wish to retain them. Remember that your competitors are putting in more effort to attract your customers to their business. Machine learning will analyze customer data to help you understand their preferences, likes, and dislikes.
How is machine learning used in business? When a task can be completed by a machine in less time, with more efficiency, why dump it on employees? Let machine learning automate recurring tasks so that your employees will have more time to focus on the core projects.
Customers like variety. They also like to be provided with several options of products/ services they want. How do you attract a customer to your business? Personalized ads are the result of machine learning. You can reach out to a user who wants a product/ service you provide by analyzing their search history and purchase preferences.
Cybersecurity has been a cause of concern for every business. A startup or a multinational company, no one is safe from hackers. But AI and ML-based antivirus software can safeguard your business and prevent cyberattacks by providing multilayer security. Of course, it is expected that hackers will also use the same technology to get in. But machine learning can help identify the weak spots in advance and strengthen the overall security system.
Can machine learning enhance human learning in business working environments? Absolutely! Machine learning is used for human resource management in several ways. From identifying the talent gap to screening applicants and assessing the value of an employee to providing customized training options, ML can help employees become better at work. Every employee’s career growth can be mapped in parallel to the company’s growth.
AI and ML are being used to streamline inventory and shorten the delivery time. Machine learning uses the existing data to provide valuable insights, whether predictive maintenance or alternative routes to reach the destination earlier. This helps you in making better decisions.
What role does AI play in business communication? Artificial intelligence combines machine learning, deep learning, natural language processing, and more such technologies that effectively understand, analyze, and process data to provide meaningful insights. Artificial intelligence has been used to facilitate better communication in recent years. Here’s how AI is used in communication:
Chatbots have changed the way businesses and customers interact with each other. There is no need for customers to wait long hours, hoping the representative will respond soon. These chatbots are found not only on business websites but also on other communication channels. You can develop a chatbot for Facebook Messenger to respond to followers on that platform. Using chatbots also reduced the cost of expenditure incurred by the customer service department.
Artificial intelligence solutions can create smart campaigns for marketing and promoting the brand among the target audiences. Customers are segmented and categorized based on their online data. This allows you to create hyper-targeted ads for each customer group and every customer. It can increase the chances of converting a prospective user into a successful lead and customer.
Do we need to tell you about the nuisance of spam emails? They keep coming, don’t they? Unless you have AI-based filters will effectively keep phishing emails out and prevent your employees from falling prey to cyberattacks. Though Gmail is effective, using your own ML-based filters and spamware will better protect against phishing attacks.
Natural Language Processing helps understand the text and the intent behind the words. Instead of asking employees to send replies to every mail, this can be automated using AI and ML. The automated smart replies use the appropriate wording to frame the response for every email.
Similar to how chatbots communicate with customers, the same helpdesk system can be set up for internal customers, aka employees. Machine learning in business applications can help employees answer their queries by contacting the chatbot instead of a human agent. This saves time for both sets of employees.
Machine learning can solve several business problems if you know how to use it. Of course, adopting AI and ML has its own set of challenges to deal with. That’s why most enterprises rely on offshore machine learning consulting companies to help with the adoption process.
You need to determine if you want to use machine learning for prediction or decision-making. Using ML for the wrong purpose will result in more loss than profits.
While data is available in abundance, not all of it is useful. Data first needs to be cleaned before it can be processed and analyzed. Even unstructured data needs to be rid of duplicates.
Remember that even when using machine learning applications in the industry, there is a chance for error. Nothing is absolute, and ML is not 100% accurate. It can only reduce the risk of human error. But if the data you enter itself is wrong, there’s nothing the machine learning software can do.
When developing a prototype for a machine learning model, you need to focus on the problem areas first. Don’t waste your resources on using ML for something that is already efficient.
You will need to keep making the necessary changes and adjustments so that the ML-based system is delivering the kind of results you want.
Hiring an ML consulting team will ensure that they take care of these problems and help you achieve your goals.
The following are some of the uses of machine learning in business communications:
Did you know that spam emails accounted for 57% of the total email traffic in 2019? But email marketing has been an effective strategy for years. How do you balance these two? You’ll need to create better quality emails with extra focus on content to avoid being filtered as spam.
Limiting promotional words, segmenting and customizing the emails for the target audiences, updating the subscribers list regularly, and using an exclusive IP to share these emails are ways to improve your email marketing strategies. Machine learning can help you achieve this.
Machine learning in business communication has led to revamping the call center system by using the latest technology. A smart call center is the one with its communication system on the cloud platform. VoIP (Voice over Integrated Protocol) is used to make calls. This is integrated with the social media and CRM software of the enterprise.
The data collected by the virtual call centers are processed using AI and ML for fast analysis and insights. You can empower the customer service team with bots. These bots can assess the customer’s emotional state and connect them with a real agent to solve the problem quickly.
Increasing sales is the ultimate objective of a business. Machine learning can help you identify the best way to reach out to prospective leads and convince them to become customers. Is the person more likely to respond to a call from an agent or an email? Will they prefer to chat with the bot instead?
ML will detect patterns in the data and share the insights with the sales team. The team can then formulate a comprehensive strategy to add a customer to the list successfully. A communication method can be developed for each customer.
You can learn a lot about your customer by analyzing the communication you’ve had with the person. How did they respond to a suggestion? What irked a customer? Is there a change in tone? What can make them happy? What kind of feedback do they provide?
Manually analyzing this information is a very tough task and can result in a wrong understanding of the customer. Machine learning solutions simplify the process and make it highly effective.
What are the applications of supervised machine learning in modern businesses? Recommendation engines are the best example of supervised machine learning in business communication. Netflix is famous for using this to suggest relevant content to its subscribers. Amazon is another platform that has an accurate recommendation engine. This form of communication looks simple and easy but has a very positive impact on sales and revenue.
The cab services like Uber and Ola are the best examples of dynamic pricing. The cost of a trip is dependent on the vehicle selected, the distance to the destination, and the general traffic in that route. Machine Learning algorithms use historical and real-time data to suggest a price that’s beneficial to the business and the customer. This keeps the customers happy.
One more from the famous machine learning examples is the use of AI voice assistants at work. Several companies have started using voice assistants to help the HR teams in managing their day-to-day work. This reduces the need for multitasking as well as hiring more employees to manage reports and communication.
Machine learning can be used to improve the quality of content you post on the internet. Sharing valuable and authoritative content is the key to becoming an industry leader. Use ML to help the marketing team and editors find new topics, structure the posts, and phrase content to maximize readers.
A/B testing is a vital part of the marketing strategy to identify the right method to attract the target audiences. Using machine learning for A/B testing makes the process much more effective and minimizes the risk of losing an opportunity by optimizing the ads.
AI and ML can improve business communication in numerous ways. It’s another advantage that ML is not limited to one part of the business. You can adopt machine learning throughout your business and include it in every process.