NEW DELHI, Sept 30: India’s technology sector is experiencing rapid growth in artificial intelligence, cloud computing and cybersecurity, but the availability of specialised professionals is failing to keep pace with demand, according to a new industry report.
TeamLease Digital’s Digital Skills & Salary Primer FY2026-27 found that India faces a talent supply gap of around 53 per cent in generative AI and between 55 and 60 per cent in cloud technology. The report analysed 37,000 technology and digital roles across technology companies, global capability centres and other industries.
The report also found that only around 16 per cent of IT professionals currently possess AI skills. Although approximately 20 lakh professionals have undergone some form of upskilling, only about three lakh are considered to have advanced AI capabilities.
The findings point to a widening difference between the pace at which organisations are adopting emerging technologies and the availability of people capable of building and managing those systems.
Generative AI has rapidly moved from an experimental technology to an area of business investment. Companies are using AI for software development, customer support, data analysis, document processing, cybersecurity and other functions.
As adoption expands, employers are looking beyond basic familiarity with AI tools. Increasing demand is being seen for professionals who can develop models, integrate AI into existing systems, manage data and maintain secure infrastructure.
TeamLease divided the emerging technology workforce into three broad categories: AI-Core, AI-Adjacent and AI-Support roles.
AI-Core positions include professionals who build and develop intelligent systems, including generative AI and machine-learning engineers. AI-Adjacent roles involve applying AI within areas such as data engineering, cloud computing and cybersecurity. AI-Support positions focus on monitoring, validation and first-level assistance for AI-enabled operations.
The report indicates that demand is particularly strong for specialised engineering positions. GenAI developers, machine-learning professionals and data scientists are among the roles attracting greater attention from employers as organisations attempt to move beyond experimental projects and deploy AI in production environments.
The salary figures also show how the skills shortage is affecting the employment market. A GenAI developer with zero to two years of experience has an average annual salary of around Rs 11.2 lakh, according to the report. For professionals with six to eight years of experience, the figure rises to about Rs 34.5 lakh.
Data engineering roles also command substantial premiums. A data engineer with zero to two years of experience earns around Rs 9.1 lakh annually, while those with six to eight years can reach approximately Rs 29.6 lakh.
Technical support positions remain lower on the salary scale, with reported compensation rising from about Rs 5.2 lakh for professionals with zero to two years of experience to Rs 14.6 lakh for those with six to eight years.
The difference reflects a broader change in the structure of technology employment. Companies increasingly need workers who can design, operate and govern AI systems rather than simply use commercially available tools.
Cybersecurity is another area where demand remains high. The TeamLease assessment places the cybersecurity talent gap at roughly 25 to 30 per cent. Although smaller than the shortages reported for cloud and generative AI, the figure indicates that security expertise remains in short supply as organisations expand their digital infrastructure.
The combination of AI and cybersecurity is becoming particularly important. AI systems are being incorporated into business applications, while attackers are also using automation and machine-learning tools to improve the speed and scale of cyber threats.
This has increased demand for professionals who understand both software systems and security requirements.
Cloud computing presents an additional challenge. Modern AI applications depend heavily on scalable computing infrastructure, storage, networking and specialised hardware. As companies deploy more AI workloads, their reliance on cloud and data-centre capabilities is also increasing.
The shortage of qualified cloud professionals could therefore become a constraint on the broader expansion of enterprise AI.
The skills shortage is also changing the way companies approach recruitment. Instead of relying primarily on conventional qualifications, technology employers are placing greater emphasis on practical capabilities, specialised certifications, project experience and the ability to work with emerging tools.
For employees, this means that learning how to use AI applications may no longer be enough to remain competitive in the technology labour market. Knowledge of machine learning, cloud architecture, data engineering, cybersecurity and AI governance is becoming increasingly relevant.
The report suggests that demand for GenAI professionals could cross 10 lakh roles by 2026. That requirement would place additional pressure on universities, training institutions, employers and professional upskilling programmes to expand the country’s specialised talent pool.
The challenge is not simply about producing more technology graduates. Advanced AI positions require a combination of programming, mathematics, data management, system design and domain expertise. Employers also need professionals who understand how AI systems behave once they are integrated into real-world business processes.
This is creating a divide between basic AI literacy and advanced technical capability.
At the same time, the technology industry is developing new approaches to enterprise AI deployment. On September 29, IBM and Yotta announced the general availability of a sovereign agentic AI platform for Indian organisations.
The platform combines IBM’s watsonx Orchestrate with Yotta’s Shakti Cloud and is designed to allow businesses to deploy and manage AI agents while keeping data, operations and governance controls within India.
The system is aimed at enterprise applications including document processing, human resources automation and security operations. Yotta’s infrastructure provides computing, GPU resources, networking and security capabilities, while IBM’s technology provides the control layer for managing AI agents.
Such developments demonstrate why India’s AI skills requirements are expanding beyond model development. Organisations also need professionals capable of deploying systems securely, managing infrastructure and establishing appropriate governance procedures.
The country’s technology workforce is therefore entering a period in which AI, cloud, data and cybersecurity skills are becoming increasingly interconnected.
The immediate challenge for businesses will be finding enough qualified professionals to support this transition. For the wider technology ecosystem, the task will involve expanding advanced training while ensuring that workers can move from basic digital literacy into specialised technical roles.
The TeamLease findings suggest that the AI transformation of India’s technology sector is already influencing hiring, compensation and the types of skills employers value. As more companies move AI projects into production, the availability of specialised talent could become one of the key factors shaping the next phase of India’s digital economy.