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Top 15 In-Demand Skills for AI Jobs in India


India’s AI market is booming, with projections by Nasscom and BCG predicting it will reach USD 17 billion by 2027, driven by a 25-35% compound annual growth rate (CAGR). This rapid expansion is creating a significant skills gap, as companies struggle to find qualified professionals with the expertise to implement and manage evolving AI technologies.

Sashi Kumar, Head of Sales at Indeed India, emphasized the importance of skill development: “India needs to focus on improving skills to be a leader in global discussions about AI. Companies should help their workers learn more to keep up with the needed skills.”

Here are the 15 most-wanted skills for AI jobs in India, along with the percentage of job postings seeking these skills, according to the latest findings by Indeed, a leading global matching and hiring platform:

15 Skills Employers Seek for AI Roles

  1. Machine Learning (42%): Essential for developing algorithms that enable AI systems to learn and improve from experience.
  2. Python (40%): Highly valued for its flexibility and wide use in AI and machine learning applications.
  3. AI (36%): Foundational skills for understanding and working with AI technologies.
  4. Communication Skills (23%): Critical for collaboration and project management in AI projects.
  5. Natural Language Processing (20%): Vital for developing AI that can understand and interact with human language.
  6. TensorFlow (19%): A popular open-source platform for machine learning.
  7. Data Science (17%): Necessary for analyzing and interpreting complex data to inform AI models.
  8. AWS (14%): Important for leveraging cloud computing services in AI applications.
  9. Deep Learning (14%): Crucial for creating multi-layered neural networks that mimic the human brain.
  10. Java (11%): Widely used programming language for AI development.
  11. Azure (11%): Microsoft’s cloud computing service, significant for AI solutions.
  12. Image Processing (10%): Key for developing AI that can interpret and manipulate visual data.
  13. SQL (10%): Essential for managing and querying databases in AI projects.
  14. PyTorch (9%): Another popular machine learning library used for developing AI applications.
  15. Agile (8%): Important for managing and delivering AI projects in a flexible and iterative manner.