AI Chatbots are Create New Jobs by Killing the Old Ones
Whenever technologies advance, there is often a fear that the newer, faster machines will replace human workers for good, leaving an unemployed populace and a devastated economy in its wake.
Whenever technologies advance, there is often a fear that the newer, faster machines will replace human workers for good, leaving an unemployed populace and a devastated economy in its wake. The fear was there with the invention of steam power machines, the assembly line, computers and now AI and chatbots are at the root of that fear.
As AI and chatbots become more popular each day in the fields of finance, health, law, and retail, workers are wondering how soon it will be before they lose their jobs to the latest machine. This is true particularly in customer service, retail, and telemarketing positions where automated chat bots already have a strong foothold. Inevitably this new wave of tech will eliminate many menial jobs but it will also allow new employment opportunities to be created as well.
So, how will chatbots destroy these jobs and is it really so dramatic as to cause such anxiety? According to a study by Forrester, 25% of unskilled jobs will be affected by AI and intelligent chatbots by 2019.
One of the most impacted jobs will be in customer service, thanks to instant messaging. Nowadays, most customers expect instantaneous responses to simple questions on websites, Twitter, Facebook, and other social media. Chatbots are being used to answer these questions instead of waiting hours for a human response or waiting on hold on a 1-800 helpline.
As this type of digital communication has become the primary means between clients and businesses, especially in circumstances when clients know exactly what they want and need very little help otherwise, an intelligent chatbot can assist with these type of transaction often in less time and with fewer mistakes than their human counterpart.
Whereas in the finance industry there are already a number of investment firms, like AlphaSense, Cerebellum Capital, and Sentient Management, which have already turned completely to AI for being more productive and aid in making better decisions but up to 32% of total firms rely on them in one way or another according to Narrative Science.
As for your everyday bank, many already automate their chat messages and alert systems so that customers no longer have to get their information from a human. And in an industry where 45% of their main focus is customer service, according to a survey by Econsultancy, you can be sure more of these jobs will go to AI if it improves customer satisfaction.
Yet, all is not lost, there is good news too. Plenty of the jobs killed by AI can be replaced with new human only rules if companies can be flexible and adapt quickly. Talented individuals can be moved into important business roles that require the creativity of a human variety.
Because they eliminate human errors and remember incidents and preferences going as far back as its databanks, intelligent chatbots can support a customer service division very well, especially one under great demands as a bot can handle a number of customers at once. Gartner predicts that 85 percent of customers will deal only with chatbots in their relationships with businesses by 2020.
Still, customer requests these days come in from every avenue and chatbots can help ease the congestion. Lithium Technologies have discovered that 53 percent of customers who ask questions via Twitter and other social media forums expect company responses within 24 hours. A chatbot support team can be at the ready 24 hours a day 7 days a week to meet those needs. For example, a small business, expanding quickly, can employ a chatbot to deal with a larger customer base, before it may have the money to hire a new human employee.
AI tools are a great help for teams that need to scale their services up to a new level. Many service jobs previously given to human works will undoubtedly go to chatbots in the future in order to keep order within businesses and at the same time meet the demands and expectations of their customer base.
Theoretically, a chatbot could respond to millions of millions of bits of information and demands all at once with less time and money, and therefore makes a great addition to companies at any level. As such, there is a great demand for creative minded workers and entrepreneurs in the technology sectors servicing the chatbots. So, while low-level customer service jobs are going to the chatbots, the jobs of building, maintaining, and marketing those chatbots are going to humans in the tech industry.
According to a study by Modis, the technology industry is projected to increase 12 percent by 2024. A current LinkedIn survey reaffirms these findings while adding healthcare, energy, and oil sectors to the list of businesses and employment opportunities that are growing.
It’s obvious that the era of chatbots and other AI is upon us and the best we can do is to adapt and be flexible to meet whatever the employment market demands. Chatbots are already present in a variety of sectors contributing automation, efficiency, and scalability to many types of industries. A few jobs may go as bots are more suited to perform those duties but many more positions will be created to supervise, maintain, and create the chatbots as well as work alongside them.
All industry and markets will benefit with greater productivity as long as human intelligence and artificial intelligence keep pace and work together.
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Daniel Okafor
Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.
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