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 called KITT (Knight Industries Two Thousand), 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 (AI) and machine learning technology is a reality, communicating with users through natural language interfaces. Everyday jobs will soon be transformed as this technology advances.
Bots and digital assistants enter the world of work
Robots have had a place in manufacturing for many years, primarily consisting of machines supervised by 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, modern day KITTs such as 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 – happening now – is artificial intelligence that writes its own code as it learns from experience.
What’s next in the rise of AI 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 has become available for use in the business world, which promises a transformation in the way human capital is utilized, fundamentally changing the nature of many jobs. As it is implemented, artificial intelligence will take over the time-intensive tasks that consume valuable man-hours, allowing workers to focus their efforts in areas where they add the most value.
One example is 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, changes of address, payroll adjustments and benefits inquiries. Processing time punches for non-exempt 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 AI and digital communication
Artificial intelligence will have its most significant impact on work patterns in how we interact with automated systems. 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 AI is carefully designed with the end-user in mind to ensure its 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 is one of the first examples of a truly intelligent, helpful digital assistant for the enterprise. Wanda 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, such as completing timesheets and managing purchases and approvals, become self-driving. The user simply talks to Wanda through their messaging app to confirm assumptions, ask questions and complete tasks.
One example is the arduous process of completing timesheets. With the help of artificial intelligence, it is possible to automate timesheet entry to the point that users barely provide any input at all. The applications automatically generate timesheets based on multiple data streams and 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.
Soon we’ll see this type of AI assistance applied to all kinds of repetitive, time-consuming tasks. Estimates of the amount of time most workers spend on basic, repetitive transactions varies by position, but the bottom line is that any amount is too much. A recent global productivity study showed that lost productivity is costing the global service industry more than $5 trillion annually. Workers spend around a third of their time on non-value adding tasks. Through automation of these processes, businesses will enjoy a dramatic uptick in worker productivity, and a much happier workforce.
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