Artificial Intelligence (AI) is a branch of computer science that deals with developing algorithms capable of performing activities that typically require human intelligence. Most of the innovations today are driven by AI or related technologies. From Netflix’s recommendation engine to self-driving cars, AI-based recommendations have created a new economy for startups and established companies alike.
AI owes its meteoric rise in enterprises to its ability to automate repetitive tasks and perform activities at lighting speed. AI algorithms aim at creating models that leverage big data to learn the latent relationships. The trained AI models are then deployed to automate routine tasks. Organisations are using AI to improve the customer experience, from automated hotel check-ins and data entry to chat bot-based customer service.
While it’s true that AI-driven products create value, the idea of automation has built a strong public opinion that AI is going to eliminate jobs. This phenomenon is not new and certainly not unique to AI. People had to reskill to become mechanics and industry workers after the first industrial revolution, electricians after the second, and software and hardware engineers during the third.
We are in the fourth industrial revolution. It redefines the fundamental way we work, live, and use products. The fourth industrial revolution is built on top of massive technological advances we achieved in the prior decades. Advances in cloud computing, AI, the Internet of Things (IoT’s), cyber security, autonomous vehicles, and virtual reality are blurring the gap between the real and virtual world.
Organisations need the talent to build applications related to AI. While the finished product can reduce customer service staff, the process of creating chatbots needs talent as well.
We need data engineers to store and process massive amounts of data, annotators and linguists to analyse and annotate the text, business analysts to define the system requirements, subject matter experts to define customer success, data scientists to create models, software engineers to build products, UX/UI personnel to create great user experience, and the list goes on. In this example, while the chatbots might eliminate a few customer service roles, they disproportionately create more technology-related roles.
Furthermore, AI and ML are creating new economies. Advances in Computer Vision and Natural Language Processing are good examples. It is impossible to imagine automated vehicles or Metaverse without the commercialisation of AI. While some jobs will be redundant and will be eliminated, far more and newer opportunities are emerging.
There is a massive shortage of AI talent right now. A Chinese innovation organisation Tencent has estimated that there are around 300,000 AI experts worldwide, yet “millions” of jobs are available.
The severe shortage of AI talent and extreme organisational interest in AI is a perfect opportunity for higher education institutions and enterprises to bridge the skills gap. Though we have AI specialisations in top-tier Indian higher-education institutions, the programs struggle to keep up with the rapid advances made in AI.
Similarly, organisations can launch reskilling programmess to help associates become AI-ready. “Change is the only thing that’s constant,” and it can be managed easily if we plan.
(The author is a data analytics professional)