What generative AI means for India's talent

Insights

• India is increasing its investment in generative AI and utilizing the technology effectively.
• Yet there is concern about the technology’s negative impact on talent and cost efficiency, among companies.
• There is a scarcity of AI talent, and companies are struggling to hire the right talent.
• Also, lucrative salaries for AI-related roles are resulting in high attrition.
• Upskilling and reskilling existing employees in generative AI skills, along with creating new roles related to AI within the organization, could be helpful.

Generative AI – with its magical ability to whip up text, video, audio, or image content in a matter of seconds – continues to grow in popularity globally. Its boom in APAC, particularly India, is no different. As per Infosys’s Generative AI Radar APAC report, 55% of APAC companies are currently implementing generative AI or using it to deliver business value. Unsurprisingly, the spend of APAC countries on generative AI is also expected to grow, increasing the business value emerging from APAC.

India on track

India is in a good position to benefit from and to service the boom in generative AI. India’s growth over the past few decades has been built on its talent, both deployed at home to build India’s tech industry and exported abroad, and as such India is now one of the largest pools in the world for AI talent. Even as long as two years ago, 16% of the world’s AI talent pool was coming out of India. A recent report by LinkedIn says that India is among top five countries in the world with fastest-growing AI talent. A high proportion of Silicon Valley CEOs have Indian heritage, and many Indians go to work in the tech industries abroad. Yet it is not all rosy for the AI talent scene in India.

Issues to be tackled

The APAC companies surveyed in the Infosys study said that though they are reaping the benefits of generative AI, they are particularly concerned about the negative effects of the technology’s potential on talent.

• Scarcity of AI talent
  The evolving nature of generative AI demands the presence of a workforce with new and evolving skills. Some top AI-related skills in great demand include large language models (LLMs), generative AI, prompt engineering, Stable Diffusion, ChatGPT, and building AI chatbots. The speed at which the technology is growing is creating a scenario of high demand and short supply. In fact, the gap between the demand and supply of AI/ML BDA technology talent in India amounts to 51%.
• Struggle to recruit the right talent
  AI talent recruitment requires organizations to have recruiters with a complex understanding of the role and skills, needed to hire the right talent. Entrusting the task to generalist recruiters who fail to understand the profile well can waste precious time and effort.
• High rate of attrition
  The short supply of AI talent has companies fighting for individuals with the requisite skills. This translates to high salaries for AI-related roles, resulting in high attrition, posing a talent retention problem for companies.

The way ahead

To maintain the position that India has in terms of its AI adoption and AI talent production, whether to cater to demand that’s domestic or international, companies should take an AI-first approach. To achieve this, organizations will need to focus on the following steps:

• The first step is to establish organizational structures and processes. Companies should establish and communicate to the entire organization which individuals and leadership teams internally sponsor and head generative AI projects, so it becomes easier to seek approvals to plan the initiatives required to address the challenges related to AI talent. A collaborative board-CIO relationship can help policy setting and in the smooth execution of initiatives.
• An effective way to manage demand for new generative AI skills, without having to compete with other organizations for talent hiring, is to upskill and reskill existing employees in generative AI skills.
• Besides upskilling current employees, companies should hire new talent and work with partners to build AI-led learning paths that include both the creator community – comprising data scientists, econometrists, machine learning engineers, and so on – and the consumer community that includes prompt engineers. This promotes knowledge sharing and a collaborative culture that adds to a sense of connectedness at the workplace, increases work satisfaction, and can reduce attrition.
• Companies can leverage the benefits of automation to free up employees’ time so it can be applied in more fulfilling areas, increasing their productivity, and aiding talent retention. Firms can also create new roles such as experience designers, digital specialists, and platform engineers that are related to AI, to check attrition.
  

  Firms can create new roles such as experience designers, digital specialists, and platform engineers that are related to AI, to check attrition.

• Develop internal development platforms that allow technical and nontechnical teams to collaborate, along with automated and guided workflows to simplify the process of using AI and reduce the risk of errors. Companies can also provide prebuilt models and templates for common tasks like image recognition, text classification, or sentiment analysis, so that employees do not need to build them from scratch.
• Offer time-saving self-service generative AI tools to help teams to build and deploy generative AI applications without the need to find or develop complex code.

All these measures combined can help create solid AI skills in a workforce and address most of the AI adoption and talent-related issues that companies are facing.