Bots at Work: No Longer Restricted to the World of Science Fiction
A few decades ago, AI was simply a creation of science fiction. Now, artificial intelligence and machine learning are reality.
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In the 1980s, the television program Knight Rider gave a glimpse into a world where artificial intelligence could learn, communicate, and make independent decisions. The star of the show, a self-aware computer, was housed in a 1982 Pontiac Trans Am, and it intrigued viewers. They imagined how the technology could change lives, handling dull or dangerous tasks with a simple spoken command. At the time, such software sounded like a creation of science fiction. Now, less than four decades later, artificial intelligence and machine learning technology are our reality, communicating with users through natural language interfaces.
Robots and Digital Assistants Enter the World of Work
Robots have had a place in manufacturing for many years, primarily consisting of machines that require operators to manage tasks. These tools have enabled significant automation of repetitive jobs, and they have successfully taken the place of their human counterparts in uncomfortable or dangerous conditions. With specialized programming, they can do everything from packing eggs to performing surgery. However, until recently, these machines could not think, and they were only capable of communicating with people who had appropriate training.
New technology has changed the user experience, offering advanced speech recognition and chat capabilities that make it possible for laypeople to perform basic transactions without specific commands. For example, Apple's Siri, Amazon's Echo, and Microsoft's Cortana recognize a wide variety of questions and commands, acting as personal assistants for users. However, even these applications don't reach the level of thinking and learning that writers imagined when creating Knight Rider in the '80s. Siri, Echo, and Cortana use linear coding that, while robust, is essentially unchanging. The next step — which is happening now — is artificial intelligence that writes its own code as it learns from experience.
The Rise of Artificial Intelligence and Machine Learning
Leaders in the field of artificial intelligence have long studied and planned for the development of technology that is capable of gathering data — including historical information from previous experience — and making analytical decisions. Today, this software is available for use in the business world, which promises a transformation in the way human capital is utilized. As it is implemented, artificial intelligence will take over time-intensive tasks that consume valuable man hours, allowing workers to focus their efforts in areas where they add the most value.
Early wins include the adoption of artificial intelligence technology in basic human resources transactions. For example, there are entire departments made up of staff who manage requests for time off, address changes, payroll adjustments, and benefits inquiries. Processing time punches for nonexempt workers requires an extraordinary amount of work, and it must be completed quickly and accurately to stay within federal and state labor regulations. Perhaps most surprising of all is that most of these transactions are already automated. The manpower is necessary to handle exception requests, errors, and other issues that result from incorrect use of automated HR systems.
Current automated and self-service HR platforms are only capable of managing transactions that fall squarely within rules defined by programmers, and they flash an error message when an issue comes up outside of program rules. With advanced artificial intelligence, HR platforms will learn how to handle exceptions, drawing on previous experience with similar situations to make a decision on handling new issues. When these tasks are transitioned to smart technology, HR staff will be freed up to work on projects that add long-term value to an organization such as training, engagement, and conflict resolution.
Seamless Blending of Artificial Intelligence and Digital Communication
There is a long history of high-quality technology that never caught on in the mainstream because the intended users were unable to get the results they wanted with the level of effort they were willing to invest. Consider the essentially unknown AT&T PicturePhone developed in 1956, which offered callers the ability to see each other. It was an exciting invention, expected to become indispensable in homes and offices nationwide. However, the wiring was so complex that potential consumers decided to do without. Compare that to today's video calls, which operate using wireless mobile technology. The simplicity of these applications has made them popular with millions of users.
The new generation of artificial intelligence is designed to be as simple as possible to accessibility to workers in every industry. It meets users where they are already comfortable, conversing through common communication software such as Skype and Facebook Messenger. The software is capable of understanding user instructions without requiring certain key phrases, and most importantly, it learns from experience. After showing these systems how a transaction should be done, how an exception should be processed, and what the user's typical habits are, they remember — and they can apply this information to similar situations.
Unit4’s Wanda (whatever name and identity the customer wants to give him/her/it) is one of the first examples of a truly intelligent, helpful digital assistant for the enterprise. She represents a new user experience that feeds from core data in the back-office systems, then makes a growing number of essential but non-value add processes like completing timesheets, managing purchases and approvals, and self-driving. The user simply talks to her through their messaging app to confirm assumptions, ask questions, and complete tasks.
The process of completing timesheets tends to be arduous, for example. However, with the help of artificial intelligence, it is possible to automate timesheet entries to the point that users barely provide any input at all. The applications automatically generate timesheets based on multiple data streams, plus GPS and beacon location data to track time. After some experience, they understand which project or customers to apportion time to, and they automatically complete the process as users focus on activities that add greater value.
Estimates of the amount of time most workers spend on basic, repetitive transactions vary by position, but the bottom line is that any amount is too much. Through automation of these processes, businesses will enjoy a dramatic uptick in worker productivity and a much happier workforce.
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