Atlanta, GA, July 28, 2016 (Newswire.com) - Artificial Intelligence (AI) is described as a branch of computer science that focuses on the development of machines to be able to perform tasks that usually require human intelligence.
Published in 1950, Computing Machinery and Intelligence, by Alan Turig opens with the line: "I propose to consider the question, 'Can machines think?'" In this paper, Turig proposes a test of a machine's ability to display intelligent behaviors equal to or indistinguishable from that of a human being. This is now known as the Turig Test. A great example of such a test can be seen in the movie Ex Machina.
Receivables solution providers are leveraging AI more each year as they incorporate technology such as Robotic Process Automation (RPA). Incorporating RPA allows non-technical personnel to 'train' software robots in a way that allows them to learn specific steps in a process. Where traditional software programming will use code-based instructions to execute tasks, RPA software can be configurable for non-technical users so that is makes better choices based on how it has been trained, very much like staff members.
The term 'artificial intelligence' was first coined by John McCarthy, one of the organizers of a conference held at Dartmouth College in 1956. McCarthy has since come to be known as one of the founding fathers of AI. The proposal for the conference included the following claim: every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it. This conference is where AI, as a field of study, began.
As Moore’s law suggests, the cost of computing has decreased while the power of computing has increased significantly. The emergence of mobile phones, tablets, social networks and wearable electronic devices has made AI applications more practical and easy to access. Because there is such a tremendous amount of data being shared, without the implementation of some form of intelligent automated support, the data would be too cumbersome and expensive to handle. The reality is that artificial intelligence is now very much a part of our every day lives.
AI advances in every day life
The advancement of intelligent technology in recent years means that individuals and organizations no longer must rely solely on manual intervention to accomplish learnable tasks. Some examples of how AI has made its way into our every day lives include:
- The introduction of virtual personal assistants such as Siri on iOS phones and tablets. Why take the time to look things up on your browser or dial that best friend when you can simply have Siri do it via voice command.
- Fraud reduction through AI tools that can learn a user’s habits by following their behavioral patterns and warning of any inconsistencies.
- Recommendations for movies and music from providers like Netflix and Spotify. Watch enough movies and listen to enough music and these providers will leverage technology that can now make recommendations based on your habits.
- Smart appliances and devices that can anticipate your needs in your home. Lights that come on and burn at a certain brightness or thermostats that adjust the temperature based on your home activity are just two of the mundane but repetitive tasks AI-enabled appliances and devices can manage.
Utilizing AI In Finance and Accounting
Where organizations are concerned, AI provides many benefits through the automation of manual processes. Automation greatly reduces the risk of human error while speeding up processes. Not only does this save time, it reduces costs and eliminates long hours of unnecessary manual labor.
Receivables solution providers are leveraging AI more each year as they incorporate technology such as Robotic Process Automation (RPA). Incorporating RPA allows non-technical personnel to ‘train’ software robots in a way that allows them to learn specific steps in a process. Where traditional software programming will use code-based instructions to execute tasks, RPA software can be configurable for non-technical users so that is makes better choices based on how it has been trained, very much like staff members.
RPA can dramatically streamline and improve a number of areas related to Accounts Receivable, including:
- Incorporating better credit risk analysis and decision making in credit management
- Refining data capture and application through Optical Character Recognition (OCR) without template or rules management while resulting in a higher rate of accuracy.
- Enhancing workflows related to the collections process, allowing for greater efficiency of dedicated resources and improved invoice collections.
- Automating the cash application process, where remittance data is gathered through various sources, matched with the invoice data and the resulting electronic payment occurs and is reconciled with the corresponding customer account.
Solution providers such as HighRadius, Rimilia and Billtrust incorporate some form of AI-based RPA to streamline their customers’ invoice-to-cash operation. While there are many organizations that have yet to take advantage of these capabilities within their organizations, this technology will continue to gain acceptance across multiple industries.
Source: Receivable Savvy