Like with all technology solutions, the savings that using cognitive AI provides come from reducing the use of human resources in the process. This has been the trend with every single technological transition: we eliminate some jobs or parts of jobs. At the same time, we create new jobs that are different in nature. Cognitive AI will not replace humans but is aiming to transfer human effort to important work.
In this blog, we look at the cost savings and business benefits that can be achieved with automation based on cognitive AI. The blog discusses the following questions: Which business processes can be automated by cognitive AI and that way save money? What kind of savings are we talking about? What factors affect the potential cost savings of process automation and what is the typical timescale for achieving cost savings with cognitive AI solutions?
Savings can be achieved in processes that require human understanding
Cognitive AI can create savings in almost all business processes and support processes where humans are required to interpret and manually transfer information. In this case, we are talking about processes that require manual human work on handling records and documents. By utilizing cognitive AI, those human resources could be released to do something more beneficial. Often the people handling these processes are skilled and highly trained, but parts of their job include simple manual work. On the other hand, if the process requires a lot of people to do the manual work and the work can be automated, the number of people can be reduced.
A concrete case example of the savings that can be achieved
Let’s take an example from the insurance business. Imagine you have 100 people working on a case, making decisions based on claims or other back-end material. In the insurance business, about 80% of the cases are called “easy cases”, which means that they are paid out and never heard of again. When we use deep AI to read through the claims or medical records relating to the case, we can create a sufficient structure for the back-end machine to calculate whether this is an easy case or a difficult case. If it is an easy case, we can save about 70% of the effort, which means that 70 people out of the original 100 can work on something more productive.
What factors affect the potential cost savings of process automation?
Simply said, the time that is saved. The more time is spent on manual handling of the process and the more records or documents there are that need to be handled, the greater the potential savings are. Moreover, it is not only about the direct cost savings following the human-understanding AI-based automation, but the focus is on how the time saved can be used more efficiently.
Let’s take the example of business process accounting. With outsourcing, the quality of the accounting data is not necessarily as high as needed. With outsourcing, decisions on invoice allocation and accounting are correct from a legal point of view, but they might be wrong from a business-oriented data acquisition point of view. This means that you cannot really use your accounting data to make business decisions because it is not accurate enough. If we can make accounting more accurate by using AI instead of a human, we can make more use of the data, make better decisions and lower the cost of procurement. For example, we can use the accounting data to decide which vendor we should buy specific things from. The information gained through AI can be used to develop other areas of the business to be more efficient.
What is the typical timescale for achieving cost savings with AI solutions?
In a best-case scenario, savings can be achieved within a month of the completion of the automation project. This could be the case if a project of 100 000€ helps 100 or even 500 people save 70% of their time to do more productive work.
However, the payback depends on the company and the process that is being automated. Normally, savings are achieved in less than a year, often as soon as in 5-6 months.
