Machines have been making work easier for some time now, but thanks to cognitive technologies, they’re about to start dealing with much higher-level tasks — as well as make us all better workers.
The technology we create to handle human tasks is advancing at a rapid rate, increasingly becoming smarter, more efficient, and more independent from their operators than ever before. These cognitive technologies, a term Forrester uses “broadly to refer to robots, automation, robotic process automation (RPA), smart machines, intelligent machines, and machine learning,” are changing the landscape of the modern workforce.
Indeed, according to a recent Forrester report, entitled “The Future of White-Collar Work,” 74% of automation technologists believe cognitive computing will usher in a new era of man/machine collaboration, and a further 60% anticipate that cognitive will facilitate a shift to more person-to-person interactions. Importantly, these changes will not exclusively impact entry-level workers like back-office clerks and call center agents — even those at the highest levels of work, from the financial sector to healthcare, will feel the effects of implementing cognitive technologies.
In the Office
Already, administrative and office tasks are being automated at a rapid pace, and cognitive technologies are ready to automate more complex assignments. Take the work of mortgage origination, for example: the process traditionally involves three separate groups of employees that have to work with 15 systems in consecutive order, making for an obtuse and training-heavy operation. Using robotic process automation to enter and review captured data, Forrester details how managers only needed two groups working with just seven systems, which both streamlined the entire process and expedited the training required for new team members.
Those working in the financial industry can also expect to see their job requirements change, as cognitive support systems not only leverage trading applications and analysis, but are also primed to close quarterly and annual books as well. Rather than relying on some 2,000 people using inaccurate or inefficient data, UBS anticipates robots will be closing their books autonomously within five years. This incredible breakthrough will free up their human employees to focus on the “strategic side of closing.”
Because cognitive technologies are capable of processing so much more data so much more quickly than humans, the ways researchers and analysts conduct their work is going to transform.
For example, Goldman Sachs uses the machine learning platform “Kensho” to mine data from the National Bureau of Labor Statistics and compile all that information into regular summaries. The reports feature 13 exhibits predicting stock performances based on similar employment changes in the past, and they’re ready to print just nine minutes after the data is entered.
In medicine, artificial intelligence is already being used to improve current diagnostic methods and reduce hospital readmission rates. Researchers were able to use machine learning techniques to automatically apply the LACE diagnostic framework to patients in Singapore, improving its decision-making processes based on medical outcomes. In the future, experts expect that AI-powered software will be able to systemically improve health outcomes by identifying high-risk patients and customizing treatment plans.
We are also already witnessing significant changes for customer service professionals, who are seeing their burdens lightened and performance bolstered by cognitive platforms. In the future, customer service representatives will likely add “Teacher” to their resumés — one A.I. project called MetaMind is developing a chat bot that can observe interactions between a human representative and a customer. As the rep addresses and resolves the issue at hand, the platform records the text and reprograms itself accordingly — that is to say, he learns to improve.
Intelligent machines could even start changing the way we dress. WIRED reports that a software program developed at the University of Toronto is capable of recognizing fashion flaws and suggesting corrective clothing adjustments. With the customer service aspect of the fashion industry being handed off to robots, human workers can turn their attention to creating new lines and changing tastes, tasks that their non-human counterparts simply aren’t capable of.
Finally, there’s marketing, where artificial intelligence-based platforms like Albert from Adgorithms promise to remove much of the data-related drudgery of digital advertising. By coordinating campaigns across multiple channels, AI tools will allow marketers to drop the data entry tasks and take on greater and deeper levels of creative and strategic work. This development is particularly necessary in the marketing arena where the explosion of channels, devices, data, and technology has created a landscape that is no longer humanly possible to manage at the pace and scale with which the modern-day consumer demands. Ultimately, this collaboration between man and machine frees up humans (and their valuable time) for higher-value work such as delivering content unique and personalized to each and every individual customer and consumer. Not only will this maximize productivity, but it will also lead to happier employees — which in turn leads to happier customers and better businesses.