Businesses up and down the country are looking to automate some elements of white collar work. While the AI singularity isn’t quite here yet, the technology is advancing at such a rapid pace that it might as well be.
The growing trend of automation is expanding beyond manual labor and into cognitive areas of the economy. These changes are being driven by AI and machine learning, allowing for the automation of more complex tasks, once thought possible only in sci-fi movies.
“The rise of white collar automation is shocking to many people,” explains Flamingo Digital, “but it is speeding up.” The company, which makes an AI receptionist, believes that the power of AI is now so advanced that the era of the conventional call center is “dead.”
The Rise Of White-Collar Automation
The rise of white-collar automation is something that has been a possibility for some time now. However, it is only really in the last two or three years that we’ve seen concrete examples of how it could be done. The combination of robotic process automation with generative AI is extraordinary, and promises to reshape the world in ways that only a handful of people imagine.
For example, chatbots are now playing a massive role in customer service. Many enterprises are using them to communicate with their clients twenty-four-seven, without any annoying breaks.
Other examples include things like document processing and data analysis. These would have taken months in the past, but can now be done incredibly inexpensively.
Of course, human oversight still plays a role in many of these industries. AIs are not yet autonomous in the workplace. But they can be great for screening and anything that involves spreadsheets of hard-to-interpret data.
Industries leading the charge in this area including the financial sector, legal sector, and HR. These are using these systems for things like automated accounting and legal research automation.
The best way to use AI is for customer service, because of its language skills. These systems can work online and over the phone for improved customer interactions long-term.
“The quality of AI-powered virtual assistants is growing all the time, but a lot of businesses aren’t aware of the sheer growth of the technology yet,” Flamingo Digital explains. “You can now have full voice conversations with these AIs, and they can understand what people want across various languages. If there’s a problem, they can escalate to a team of human reps to deal with the trickiest issues.”
The Benefits Of White-Collar Automation
The benefits of white-collar automation are nothing short of extraordinary. The number of tasks that AIs can perform competently is growing every day, to the point where many roles in the future will simply be oversight,
For example, many companies predict that AI will enhance efficiency and productivity on task completion. AIs can already process thousands of documents in legal practices in minutes, so they are essentially removing much of the work traditionally done by paralegals.
The reduction in human error for repetitive tasks is also something that is having a profound effect at the company level. AIs are better able to get things done without making mistakes, which is a critical issue that requires addressing in many businesses these days.
Another benefit is the sheer scalability of these systems. Many AIs can simply grow to automate tasks and workloads at scale, without executives needing to bring in new people to take up the slack.
“Scaling is one of the benefits that we talk about a lot at Flamingo Digital,” the company explains. “You can have hundreds of simultaneous chatbot conversations at the same time, meaning customers can meet all their clients’ needs for attention, even if they don’t have anyone to physically man the phones.”
As part of this, companies are benefiting from some quite extreme cost savings. Using chatbots and other automated systems can potentially eliminate 90% of the work that humans once did at a fraction of the price.
Finally, companies that automate are also more likely to experience competitive advantage and keep their team’s roles secure. Automation increases productivity substantially, whether it is for physical labor in factories, or cognitive work in businesses.
The extent to which productivity can improve with AI depends on the quality of the underlying technology. At present, siloed software models seem to be working best. But a day in the future could arrive where AI becomes more generally intelligent and is able to carry out more tasks without being constantly under human supervision.
Challenges
Of course, as with any new technology of the same magnitude as AI, there are challenges. Getting it wrong could lead to potential layoffs in many sectors. Data entry clerks and paralegals are already in the firing line.
However, that’s not the only challenge going forward. Another major point of concern are ethical and bias issues. AI may make hiring bias worse and prevent people who could do the job fine from even getting to the interview stage. Furthermore, it isn’t always clear how AI is reaching its decisions. Many systems lack transparency and accountability for evaluation.
Data security might also be a problem for many automated systems. These systems may handle sensitive information and include it in their training sets, making it harder to secure them against jailbreaking.
Ultimately, these changes are likely to bring a revolution in the way society thinks about white collar work. The desirability of these professionals is already crumbling, and the demand for degrees will probably fall even faster, given the current technological trends. Whether things will turn around right now is anyone’s guess.
As the technology currently stands, it is fostering more collaboration between people and machines. AI trainers and ethicists are emerging, but the vast bulk of people are simply using AI as a tool for existing roles. That number is likely to grow substantially in the future as the technology becomes more widespread. However, future expansion will depend on whether the technology can operate unsupervised, and that remains to be seen in many companies.
