India's 920K AI workforce faces critical gaps in deployment, governance as demand shifts to production

India has wide AI talent gaps in deployment, governance, security: Quess report

India faces significant AI talent gaps in deployment, governance, and security roles, with GenAI deployment showing the widest deficit. While the country boasts the second-largest AI talent pool globally, the demand is shifting towards production-ready skills, particularly in the three-to-five-year experience band, as AI becomes a horizontal capability across industries. India's artificial intelligence talent is concentrated in specialist pools and there are steep talent gaps in roles such as AI deployment and engineering, AI governance and AI security, according to the latest AI talent report by staffing firm Quess Corp. GenAI deployment has the widest gap at 83%, followed by AI deployment engineering at 72%, AI governance at 70%, machine learning operations (MLOps) at 68%, AI security at 67%, and natural language processing at 63%, the report said. The three- to five-year experience band carries the steepest demand at 49.5%, it said. IT services make up about 45% of GenAI demand, the report said, as more companies move from testing AI to using it at scale. BFSI and retail come next. BFSI, IT services and GCCs account for 60% of AI deployment demand, since these areas need strict, error-free systems. AI governance jobs are growing three times faster than overall AI hiring in regulated sectors like BFSI, pharma and healthcare, the report said. New data protection rules are pushing this growth. GCCs lead MLOps demand, making up 55% of it, as platform engineering becomes their biggest strength. This shortage is mainly in specialist roles, the report said. Hiring for basic AI and analytics skills remains steady, with smaller gaps in foundational machine learning (29%) and decision intelligence (17%). Overall, demand is moving toward AI systems built for scale, governance and reliable business use, it said. The report found that India's AI talent market has nearly 920,000 professionals, the second most in the world, with core AI skills, such as building models, agents and embedded solutions, who have used these skills in the last 90 days. In these segments, the report said, there are nearly 350,000 active AI-related job roles. IT services lead the talent market, employing 500,000 professionals, followed by global capability centres (250,000) and enterprises (170,000), with most of this workforce in embedded AI roles. "The biggest finding of our report is that India is not about AI builders. It is more about production -- the country is moving towards production," Kapil Joshi, IT staffing chief executive at Quess, told ET. "When we look at the demand-supply gap, the biggest gap is for roles responsible for production." In the three- to five-year experience band, there is active demand for 172,000 against an available talent pool of 247,000. But only a smaller, production-ready segment holds deployment-scale capabilities across open-source frameworks (LangChain), retrieval-augmented generation (RAG), MLOps, and large language model operations (LLMOps) environments. The findings come amid growing fears among employees of losing jobs to AI. While most core AI models are still built by US companies such as Anthropic and OpenAI, Indian sovereign AI companies are getting a push from government schemes such as the IndiaAI Mission. The report found that demand is no longer concentrated in data scientists, machine learning engineers, or research roles. "AI capability is moving into software engineering, cloud, cybersecurity, product, sales, marketing, finance, HR, customer experience, governance and operations," the report said. More than 70% of the workforce now sits in AI-embedded roles, making AI a horizontal capability rather than a vertical function, it added. Tier-1 cities account for nearly 85-88% of India's overall AI workforce supply. Within the more specialised core AI talent segment, these cities contribute 93-95% of the workforce. Sector adoption is diverging fast: IT services and BFSI lead, retail, manufacturing and telecom are scaling selectively, while healthcare and pharma face the sharpest skill scarcity. Most of the workforce is reskilling to stay relevant.

As Enterprise AI Shifts from Pilots to Production, India's Hiring Demand Hits 350K

Quess Report Governance, Runtime Operations and Evaluation Account for More Than a Quarter of Agentic AI Hiring Demand Quess Corp has released its India AI Workforce Analysis 2026. The report is a workforce intelligence study that maps how artificial intelligence is reshaping India's enterprise workforce across Global Capability Centres (GCCs), IT Services and Consulting firms, and Enterprises. The report finds that India now has an estimated 920,000 AI professionals across Core AI, 257K and AI Embedded, 663K roles. The headline is scale; the story underneath is readiness. Hiring demand has moved sharply from experimentation to execution, with employers seeking talent that can deploy, govern, integrate and scale AI within real business workflows. The findings suggest that as AI adoption matures, organisations are placing greater emphasis on AI governance, runtime operations, evaluation and quality assurance to ensure AI systems are secure, reliable and enterprise-ready. Together, governance, AgentOps, runtime operations, evaluation and QA functions account for 26% of hiring demand within the Agentic AI ecosystem, making them one of the largest talent clusters in the market. Other key findings of the report: The Three-Frontier AI Push: GCCs Build, IT Services Scale, Enterprises Embed India's 920K AI workforce is not a single market. It is a three-frontier ecosystem with sharply different hiring intent, capability depth and deployment maturity. The operating-model difference is visible in job descriptions. GCCs are hiring for reusable internal AI platforms, enterprise integration and governance. IT Services firms are hiring to deliver AI across client programmes. Enterprises are hiring selectively to connect AI to finance, risk, operations, customer experience and employee systems. The report identifies a clear shift from pilot-led AI experimentation to production AI execution. AI Job Families Are Expanding Across the Enterprise, Not Staying Within Specialist Teams AI capability is moving across enterprise job families. The report finds that 66-68% of overall demand from the 350K active postings is for Core AI roles, while 32-34% is for AI Embedded roles. This demand mix is the reverse of the supply base, where 72-74% of the overall 920K workforce sits in AI Embedded roles and only 26-28% sits in Core AI roles. Non-tech business functions now account for roughly 120K AI-skill-cited demand, led by Operations at 57K postings. Governance, Risk and Compliance is the pressure point: despite 25K supply, it carries 22K active demand and is classified as Critical. Commenting on the findings, Kapil Joshi, CEO - Quess IT Staffing, said: "What stands out in our analysis is the emergence of three distinct engines of AI growth. GCCs are building reusable AI platforms and governance capabilities, IT Services are industrialising AI deployment at scale, and Enterprises are embedding AI directly into business workflows and decision-making. Together, they are creating a new talent landscape where execution capability matters more than experimentation. Perhaps the most important finding is that AI has become a horizontal enterprise capability. More than 70% of India's AI workforce now sits outside traditional AI specialist roles, while nearly one-third of all AI demand is emerging from business functions such as operations, customer service, marketing, finance, governance, and workforce management. Customer operations alone could see 45-60% of workflows augmented by AI, while marketing functions are undergoing one of the fastest AI-led transformations." The report's workflow-impact modelling shows that AI adoption is being embedded into repetitive, coordination, reporting, service and execution-oriented activities. The estimates do not represent workforce replacement; they show where AI-assisted execution, automation, co-pilots and decision support are becoming part of everyday enterprise work.