AI tools allow businesses to base important decisions on accurate and relevant information. AI has the potential to collect vast amounts of data from a variety of sources. However, the data it gathers is difficult for humans to comprehend and interpret because this data is usually unstructured. Despite this, AI can analyze massive amounts of data, even the unstructured ones, and spot patterns and extract meaning from them.

Types of AI

There are many areas in that AI can benefit businesses. As such, there is a need for organizations to consider how AI will benefit them instead of focusing on technologies. As AI continues to prove its importance to organizations, it has the capacity to support three important needs. These are automation of business processes, gathering insight through data analysis and customer and employee engagement.

Process automation

Automation of digital and physical tasks is beneficial for many businesses. According to Harvard Business Review, the most common type of automation of processes based on their study on 152 projects was digital and physical tasks. These tasks are mainly the back-office administrative tasks and financial activities, which can be automated using robotic process automation (RPA). Unlike the past business-process automation tools, RPA is more advanced because robots act like humans. They are useful in transferring data from email and call center systems into the company’s systems. For example, RPA can be useful in updating customer files with address changes and service additions. RPA is inexpensive and easy to implement. Furthermore, if well implemented, it can bring a quick return on investment.

Cognitive insight

This is another type of AI used in organizations. According to HBR’s study, 38% out of 152 businesses studied indicated that they use algorithms to detect patterns in massive amounts of data as they seek to interpret them and get meaning. AI applications through machine learning are used to predict what specific customers are likely to purchase. They are also used to identify credit fraud in real-time and detect fraud in investment claims. They can also analyze warranty data to determine safety or quality issues in vehicles and other projects. Furthermore, AI can be used to automate personalized ads. Cognitive insights offered by machine learning differ from the traditional analytics approaches in that more data is available, models are trained on a wider dataset, and models are typically better.

Cognitive engagement

In the past decade, there were fewer projects that engaged employees and customers with the use of chatbots, NLP and machine learning. However, HBR study shows that they have been on a steady rise and are helping businesses perform various functions. For instance, intelligent agents offer 24/7 customer service addressing various issues and answering questions or requests. Furthermore, businesses benefit from AI’s ability to answer critical questions asked by customers in areas like IT, employee benefits and policies, among others. HBR notes that companies are using AI to interact more with employees compared to customers. As it has been shown, this perspective can change once companies get comfortable with turning customer interactions to machines and working with the help of bots.