Recently, leading research and advisory company Gartner, in its report titled ‘The Road to Enterprise AI’, stated that by 2020, 1.8 million jobs will be eliminated.
‘Unplug them all!’ ‘Machines go away!’ These were the common refrains of traditionalists and AI-naysayers as they sharpened their knives and joined in the rising chorus against the technology’s growing use. The second bit of information almost drowned in the commotion.
“2.3 million new jobs will be created in the same duration, with AI-related skills being a significant component of each profile.”
As Artificial intelligence spreads its wings across industries the world over, it is leaving a trail of rapid transformation in its wake. From healthcare to education, public sector utilities to communication, the implementation of Machine learning and AI has enhanced efficiency, productivity, quality of services while reducing costs. Yet, the skepticism surrounding it refuses to die down, thanks to a major, if unfounded, claim that technology is taking away jobs and promoting global insecurity due to rising unemployment.
Outside the hype zone: Analysing the dynamics of AI and unemployment
No doubt, with the arrival of AI, everything that can change, will: from how businesses operate, analyze markets, engage with customers and even gather feedback! But that change need not necessarily be in a way that discourages employment. In fact, as industry trends point out, AI will be creating new jobs and profiles that we are unaware of currently, but will definitely be a significant part of global business ecosphere in the future.
For instance, in the field of business communication, bots are being developed that can carry out initial conversations with customers and clients, a function conventionally performed by human agents. During the initial stages, ‘bot-o-mated’ chats would move to human agents if and when a bot could not answer certain queries satisfactorily. As the product suite grows, however, a massive network of customer interactions across platforms is created, resulting in a lot of ‘training data’ that enriches the bot’s conversational capabilities, resulting in them learning quicker.
However, quick learning bots create a situation wherein gradually, the bot answers all queries by itself, resulting in ‘lesser chats’ being handled by the chat agent. Over time, this would eventually make the agent’s job redundant, an undesirable situation for the entire industry.
Interestingly, such a scenario has actually opened up the possibility of new job profiles hitherto unheard of. The human agents could now become ‘Bot trainers, developers, quality analysts’ etc to teach the chatbots to respond to different user queries. They are the perfect resources to fulfill such a task as they truly understand the user’s needs while being aware of the chatbots’ abilities, thus being uniquely placed to find an ideal amalgamation of the two. With specific guidance provided by an organization’s tech team, these agents can clearly do a great job in enhancing the chat experience of consumers.
Leading conversational AI platforms such as Haptik have already incorporated such a model and successfully upskilled more than 100 such human assistants to the position of ‘bot builders, trainers and QA’s. Even jobs such as avatar designers are becoming mainstream thanks to the rising popularity of technologies such as AR and VR. These productive collaborations between machine and humans is destined to serve as the default prototype of future employment.
Such an associative framework can enrich human agents with skill sets that enable them to move from a completely operations-based domain to jobs in core technology companies as product developers, ensuring they remain relevant in a dynamic and unpredictable business environment.
Technology, the skill of the masses in an AI-dominated world
Worldwide, thought leaders and trend setters all agree on one thing-technological knowledge is going to be the underlying framework of the future and individuals need to learn how to use it to shape the future according to themselves and not remain passive bystanders. It is an incredibly fulfilling experience to be able to understand the intricacies of a software solution which one has been using for a long time.
For employees who have spent almost all of their professional lives only ‘using’ and not ‘understanding’ technology, learning about the internal logic behind all nodes, APIs and the programming language gives them a thrill comparable to what they first experienced when learning about sales processes, the right way to pitch, gathering feedback etc. ‘It is like making your own robot and see it move around’ they say.
From Stephen Hawking to Bill Gates, Barack Obama to Susan Wojcicki, everyone agrees that whether you want to uncover the secrets of the universe, or just pursue a career in the 21st century, knowledge of technology’s practical implementation is an essential skill to learn. In such a scenario, there is an urgent need to create all-encompassing, model-driven automation frameworks that allows individuals to become consumers as well as creators of applications, thus ensuring micro-targeted AI-based solutions serving their personal needs. Only then can real stories of collaboration and success between AI and humans become commonplace and be celebrated all the more.
Aakrit Vaish is Co-Founder and CEO, Haptik
Disclaimer: This article is published as part of the IDG Contributor Network. The views expressed in this article are solely those of the contributing authors and not of IDG Media and its editor(s).