Everyday Applications of Artificial Intelligence

Artificial intelligence (AI) is presenting opportunities for businesses we never thought possible before. From taking over mundane tasks to automating analytical reporting, AI can be leveraged in almost any role today. And while it’s understandable that people may be afraid of the unknown, increasing our knowledge of AI and its benefits can help shine a light on where it can fit in and complement the way people work.

By educating both the executive level and employees, companies can begin incorporating examples of AI into their everyday business strategies – not to replace employees, but rather to improve business processes.

Below are two powerful applications of artificial intelligence being used for the better, which can be utilized by your business right now.

1) Chatbots

Many companies have replaced their online customer service presence with chatbots. These chatbots are a form of automated artificial intelligence application, capable of recognizing natural language to discover what customers are needing assistance with.¹ Chatbots provide answers by extracting information from the web or from information that has been preloaded. They can be programmed to respond the same way each time, or by way of machine learning, adapt their responses to better suit the situation, noting the keywords used in the question.²

One initial fear that developers had when designing chatbots was that humans prefer to speak to fellow humans, but in 2021, statistics showed that the vast majority (87.2 percent) of consumers have neutral or positive experiences with chatbots.³

Practical applications of artificial intelligence and chatbots

Xiaoice is an artificial intelligence system developed in 2014 by Microsoft Software Technology Center Asia (STCA). Translating to “little Bing” and referencing Microsoft’s search engine, Xiaoice is based on an emotional computing framework.

Today, Xiaoice has been advanced to make phone calls, and Chinese users can interact with her via WeChat.⁴ Most chatbots used in businesses will not be as high-tech, but even a simple design has the potential to automate user journeys and maintain a positive consumer experience.

Chatbots in your business

It’s clear that consumers are willing to interact with chatbots in specific situations:⁵

• 74% of users prefer chatbots while looking for answers to simple questions
• 65% of consumers feel comfortable handling an issue without a human agent
• 69% of consumers prefer chatbots for quick communication with brands

There are eight relatively simple examples of AI chatbots your business can utilize today:⁶

• Automate part of the marketing process: Make marketing easier with conversational bots that can streamline processes by automating the early stages of the consumer journey. Chatbots can navigate initial communication and collect any necessary details from the customers.
• Boost the volume of marketing conversations: Integrating chatbots into your conversations with customers will enable you to scale the volume of customer engagement, meaning your sales team can close a greater number of leads.
• Auto-qualify your leads: Chatbots will mean your business can auto-qualify your leads by posing prequalifying questions. This is supported by chatbots allowing customers to make choices through the selection of the most relevant options. Chatbots are more engaging than reams of forms to fill in.
• Nurture captured leads: Chatbots can increase sales conversions and revenue, boost customer satisfaction with real-time assistance, and improve brand reputation with a quick turnaround of queries.
• Schedule meetings: Chatbots will automatically schedule, modify, and cancel meetings, which saves time in terms of coordinating calendars.
• Personalize the user experience: Bot marketing improves the personalization of the customer experience, optimizing offers and discounts to customers.
• Give order tracking and shipment details: Customers can avoid offline queues and track their orders in real-time. Chatbots let customers book the place and time for shipment and follow their item’s journey as it progresses.
• Widen your brand reach: Chatbots can be put to work on social media messaging platforms, and improve upselling and cross-selling in a personalized, conversational, and engaging way.

2) Predictive analytics

Many businesses are making use of predictive analytics to increase their bottom line, especially as more interactive and user-friendly software and web analytics services are becoming more readily available.⁷ Predictive analytics, such as Google Analytics, extracts information from sets of data so that unknown patterns and associations can be recognized, and trends can be forecasted.⁸ The process involves using historical data, artificial intelligence, and machine learning to essentially predict what will happen next.⁹

Artificial intelligence examples of predictive analytics in action

Media-services provider Netflix is the most popular streaming service in the world and is now officially known as a ‘global TV brand’. A big reason behind their success is because they’re data-driven and depend largely on predictive analytics.¹⁰ Netflix makes use of the large amount of data they have collected on their users to predict and suggest which content will be successful depending on a number of demographics.¹¹ In the past, Netflix made these recommendations by simply relying on a rating-based system that revolved around user feedback, number of views, whether videos were being watched in their entirety or not, and their IMDB ratings. However, as of 2009, Netflix has been utilizing two predictive algorithms based on collective user-derived feedback and content-based filtering, as well as a hybrid approach that uses both of these methods.¹²

Predictive analytics in your business

There are a variety of ways in which predictive analytics can be used in business to gather large volumes of data, and so inform the way businesses operate.¹³ Below are three artificial intelligence examples of predictive analytics in the business setting:

1. Churn prevention:¹⁴ This AI application allows a business to predict when and why an existing customer would choose to end their relationship with the company. Before predictive analytics, this process was very expensive as it’s easier to acquire new customers rather than maintain uninterested ones. However, collections of large sets of customer data can now be used to create predictive models that can be analyzed before the customer decides to end the relationship.

2. Customer segmentation:¹⁵ By dividing your customers into groups based on similarities and differences in terms of age, gender, interests, education, and spending habits, businesses are able to more accurately target marketing messaging. Predictive analytics is an example of machine learning that can more accurately identify potential customers compared to more traditional predicting strategies.

3. Financial modeling:¹⁶ This example of machine learning is used to create an abstract model representing a real-life financial situation in its simplified form. Financial modeling is used to translate a hypothesis about a market behavior into a numerical prediction. This is then used by the business when making decisions about strategies, returns, and investments.

The number of robots worldwide could reach 20 million by 2030, with automated workers filling up to 51 million jobs in the next 10 years.¹⁷ Embracing the new world of AI and utilizing artificial intelligence and machine learning examples in your business could be the first step to making yourself irreplaceable, both in your career and in the global market.

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