The market for generative AI is expected to grow rapidly in the upcoming years, with a compound annual growth rate of 45% predicted from 2021 to 2028. Business models in a variety of sectors, from software development to entertainment, will shift dramatically as AI services become more widely commoditized.
The automation of a variety of jobs requiring natural language understanding, such as summarization, translation, question-answering, coding, and even dialogue, is being facilitated by LLMs (Large Language Models) and generative AI. AI-powered coding assistants are quickly gaining popularity and assisting developers with common chores, freeing them up to concentrate on more difficult problems. Examples include GitHub Copilot, Amazon CodeWhisperer, ChatGPT, and Tabnine.
The great majority of developers in the US have adopted AI coding tools, incorporating them into their professional and personal workflows, according to a GitHub survey. Ninety-two percent of US-based programmers are now using AI to amplify their coding skills.
There will be major economic issues as a result of these technologies upending the way that media products and information are produced and consumed, including market upheaval, the emergence of inequities, a decrease in the incentives for human creativity and invention, and labor displacement. According to a GitHub research, the vast majority of developers think that using AI coding tools will provide them a competitive advantage. They anticipate deploying AI coding helpers to produce code that is more precise, efficient, and quickly.
Routine information processing, data input, and form-filling tasks could be impacted in fields like customer service, research, and even blue-collar work and the legal sector. Nearly 5 to 10% of roles in the industries may become obsolete in the near future, even with partial automation. As a result, there will be hundreds of millions of skilled and semi-skilled employees without jobs. Additionally, the effects on industrialized and underdeveloped countries would differ.
Those cultures and nations that do not quickly reskill their workers will suffer disproportionately. Additionally, there is no assurance that generative AI and associated technologies will replace lost employment with new ones.
All sectors will be affected by LLMs and generative AI. Sectors in India that involve routine information processing, such as customer service, research, blue-collar work, and legal professions, may be impacted.
India has been a pioneer in IT services partly because low-cost programmers are readily available at home. The benefit of being a majority-English speaking country will soon disappear. The necessity of the hour is for advanced planning through worker training programs, new regulations, and social support systems that assist individuals during this transition.
Funding and motivating people to transition by assisting them in acquiring new technical skills should be a top focus. Severance payments, advance warning of automation, advance notice of severance compensation, and limitations on discriminatory AI systems are all important policy and legal measures. The state can also consider offering tax exemptions and other rewards to businesses who retrain their staff. The policies governing insurance, employment, and pensions may need to change in order to improve social safety nets. These new social safety nets should reevaluate unemployment compensation, maybe consider unemployment insurance, develop avenues for income supplements (possibly as a temporary solution), and establish job placement services to aid jobless individuals in finding new employment.
India is not as equipped to deal with the assault of Generative AI and associated technologies as China and the US are. The nation hasn’t made any sizable investments in the creation of AI chip hardware. A significant flaw is the lack of certified data sets for training and optimizing models. India also lacks a similar basic or generative model to Wu Dao or GPT 3. India has a substantially lower percentage of professionals with PhDs in AI-related subjects than China or the US.
