Today, we are going to talk about the 9 uses of AI and machine learning in business communications.
Artificial intelligence/AI and machine learning are becoming an indispensable part of our work or family life. Companies use AI and machine learning to simplify business processes and help employees improve work efficiency.
Social media sites, search engines, and OTT platforms use AI and machine learning to help users find what they want. And we use AL-based voice assistants such as Alexa, Siri, and Google Home Assistant for multiple purposes.
Over time, we see AI and machine learning being widely adopted by enterprises. North America occupies first place in AI and machine learning applications, with 80% of companies using AI and machine learning in some way. According to Globe Newswire, it is said that the global market value of AI and machine learning will reach 117 billion US dollars by 2027, with a compound annual growth rate of 39%.
What do companies use AI and machine learning for?
Why are AI and machine learning so important in today’s scenario that it is necessary to invest in AI and machine learning to stay competitive? Let us find the answer to this question.
The importance of machine learning in business
Machine learning is a subset of artificial intelligence. It analyzes data sets to track patterns and identify trends that are difficult to spot. It allows companies to automate data analysis and save resources.
Know the customer
Due to increasingly fierce competition, companies have become customer-centric. If you want to retain customers, it’s important to understand their needs. Remember, your competitors are making more effort to attract your customers to their business. Machine learning will analyze customer data to help you understand their likes, likes, and dislikes.
Automated business processes
How can machine learning be used in business? When a task can be completed by a machine in a shorter time and with higher efficiency, why pass it on to the employees? Let machine learning automate repetitive tasks, so your employees have more time to focus on core projects.
Advertising personalization
Customers like diversity. They also like to provide a variety of product/service options that they want. How do you attract customers to join your business? Personalized advertising is the result of machine learning. You can contact users who want the products/services you provide by analyzing their search history and purchasing preferences.
Improve business security
Network security has always been a concern of every enterprise. No one is immune to hacker attacks for a startup or a multinational company. But antivirus software based on AI and machine learning can protect your business and prevent cyberattacks by providing multiple layers of security.
Of course, it is expected that hackers will also use the same technology to enter. But machine learning can help identify weaknesses in advance and strengthen the overall security system.
Human Resource Management
Can machine learning enhance human learning in the business work environment? Absolutely! Machine learning is used in human resource management in many ways.
From identifying talent gaps to screening applicants and assessing the value of employees, to providing customized training options, machine learning can help employees work better. The career development of each employee can be carried out simultaneously with the development of the company.
Manufacturing and logistics
Artificial intelligence/AI and machine learning are used to simplify inventory and shorten delivery time. Machine learning uses existing data to provide valuable insights, whether it is predictive maintenance or alternative routes to a destination earlier. This helps you make better decisions.
What is artificial intelligence/AI in business communication?
What role does artificial intelligence (AI) play in business communication? Artificial intelligence (AI) combines machine learning, deep learning, natural language processing, and more such technologies to effectively understand, analyze, and process data to provide meaningful insights.
In recent years, artificial intelligence has been used to promote better communication.
The following is how artificial intelligence is used in communications:
Customer Service Chatbot
Chatbots have changed the way companies interact with customers. Customers do not need to wait for a long time and hope that the representative will reply as soon as possible. These chatbots can be found not only on commercial websites but also on other communication channels.
You can develop a chatbot for Facebook Messenger to respond to followers on the platform. The use of chatbots also reduces the expenditure costs of the customer service department.
Smart campaign
Artificial intelligence (AI) solutions can create smart marketing campaigns and promote brands among target audiences. Customers are segmented and classified based on their online data. This allows you to create hyper-targeted ads for every customer group and every customer. It can increase the chance of converting potential users into successful potential customers and customers.
Filter email
Do we need to tell you about the nuisance of spam? They keep coming, don’t they? Unless you have an artificial intelligence-based filter, it will effectively block phishing emails and prevent your employees from becoming victims of cyberattacks.
Although Gmail is effective, using your own machine learning-based filters and spam software can better defend against phishing attacks.
Send automatic smart reply
Natural language processing helps to understand the text and the intention behind the text. This can be automated using artificial intelligence/AI and machine learning instead of requiring employees to respond to every email. Automatic Smart Reply uses appropriate wording to construct a reply to each email.
Employee self-service
Similar to the way chatbots communicate with customers, the same help desk system can be set up for internal customers (ie employees). AI and machine learning in business applications can help employees answer their questions by contacting chatbots instead of human agents. This saves time for the two groups of employees.
How to apply AI and machine learning to business?
If you know how to use AI and machine learning, it can solve multiple business problems. Of course, the adoption of AI and machine learning has its own set of challenges that need to be addressed. This is why most companies rely on offshore AI and machine learning consulting companies to help with the adoption process.
Forecast and decision:
You need to determine whether you want to use AI and machine learning to make predictions or decisions. Using AI and machine learning for the wrong purpose will result in losses greater than profits.
Data processing and analysis:
Although the data is abundant, not all data are useful. Data needs to be cleaned first before it can be processed and analyzed. Even unstructured data needs to remove duplicates.
Allow errors:
Remember, even when using AI and machine learning applications in the industry, there are opportunities for error. Nothing is absolute, and AI and machine learning are not 100% accurate. It can only reduce the risk of human error. But if the data you enter is wrong, the AI and machine learning software will be powerless.
Priority issues first:
When developing a prototype for an AI and machine learning model, you need to focus on the problem domain first. Don’t waste your resources on using ML for things that are already effective.
Adjustments and changes are necessary:
You need to constantly make the necessary changes and adjustments in order for an AI and machine learning-based system to provide the results you want.
Hiring an AI and machine learning consulting team will ensure that they solve these problems and help you achieve your goals.
Application of AI and machine learning in business communication
Here are 9 uses of AI and machine learning in business communications:
Email marketing
Did you know that spam accounted for 57% of total email traffic in 2019? But for many years, email marketing has been an effective strategy. How do you balance the two? You need to create higher-quality emails and pay special attention to the content to avoid being filtered as spam.
Restricting promotional words, segmenting and tailoring emails to target audiences, regularly updating subscriber lists, and sharing these emails using proprietary IPs are ways to improve email marketing strategies. Machine learning can help you achieve this goal.
Smart call center
AI and Machine learning in business communications has led to the use of the latest technology to transform call center systems. The intelligent call center is the call center of its communication system on the cloud platform. VoIP (Voice over Integrated Protocol) is used to make calls. This is integrated with the company’s social media and CRM software.
The data collected by the virtual call center is processed using AI and machine learning to achieve rapid analysis and insight. You can use robots to provide support to the customer service team. These bots can assess the emotional state of customers and connect them with real agents to solve problems quickly.
Selective sales by categorizing potential customers
Increasing sales is the ultimate goal of an enterprise. AI and Machine learning can help you determine the best way to reach potential customers and convince them to become customers. Is the person more likely to respond to calls from agents or emails? Would they prefer to chat with bots?
AI and Machine learning will detect patterns in the data and share insights with the sales team. The team can then develop a comprehensive strategy to successfully add customers to the list. A communication method can be developed for each customer.
Analyze communication to gain insight
By analyzing your communication with customers, you can learn a lot about your customers. How do they respond to suggestions? What angered the customer? Has the tone changed? What makes them happy? What kind of feedback do they provide?
Analyzing this information manually is a very difficult task and may lead to misunderstandings of customers. The machine learning solution simplifies the process and makes it very effective.
Supervised AI and machine learning
What are the applications of supervised AI and machine learning in modern enterprises? Recommendation engines are the best example of supervised AI and machine learning in business communications.
Netflix is known for using it to recommend relevant content to subscribers. Amazon is another platform with an accurate recommendation engine. This form of communication seems simple and easy, but it has a very positive impact on sales and revenue.
Dynamic pricing
Taxi services such as Uber and Ola are the best examples of dynamic pricing. The cost of the trip depends on the selected vehicle, the distance to the destination, and the general traffic conditions of the route. Machine learning algorithms use historical and real-time data to suggest favorable prices for businesses and customers. This makes customers happy.
Artificial Intelligence Voice Assistant
Another well-known example of machine learning is the use of AI voice assistants at work. Several companies have begun to use voice assistants to help HR teams manage their daily work. This reduces the need for multitasking and hiring more staff to manage reporting and communication.
Content
AI and Machine learning can be used to improve the quality of the content you publish on the Internet. Sharing valuable and authoritative content is the key to becoming an industry leader. Use AI and machine learning to help marketing teams and editors find new topics, build posts and phrases to maximize readership.
A/B testing
A/B testing is an important part of marketing strategy and can determine the correct way to attract target audiences. Using AI and machine learning for A/B testing can make the process more effective and minimize the risk of lost opportunities by optimizing advertising.
Conclusion
Artificial intelligence/AI and machine learning can improve business communication in many ways. AI and Machine learning is not limited to only part of the business, this is another advantage. You can adopt AI and machine learning throughout the enterprise and include it in every process.