Tata Consultancy Services (TCS) is placing greater emphasis on digital and artificial intelligence (AI) capabilities as it adapts its workforce to changing technology requirements. According to a senior company official, around 80% of the employees hired by the IT services major in the July–September quarter had broader digital and new-age technology skills, highlighting the growing importance of AI-related expertise in the technology industry.
Of the 4,500 employees added during the quarter, approximately 25% to 30% had specialised AI skills, Chief Operating Officer Arathi Subramanian told the Press Trust of India (PTI). She indicated that the company expects this hiring pattern to continue, adding that the required talent is available in the market.
The development highlights an important shift in IT recruitment: knowing how to use ChatGPT or another AI tool may not be enough. Employers increasingly need professionals who can combine technology skills with problem-solving abilities, business understanding and the capacity to deliver reliable results.
TCS Hiring Strategy: Why AI and Digital Skills Matter
TCS’s hiring approach reflects the growing role of AI and digital technologies in enterprise projects. Businesses are exploring AI to automate tasks, improve productivity, analyse information and transform existing processes.
The company added 4,500 employees during the July–September quarter, with a significant proportion bringing new-age technology capabilities. According to Subramanian, specialised AI skills accounted for approximately 25% to 30% of these hires, while nearly 80% had broader digital and technology skills.
These figures describe different, potentially overlapping skill categories and should not be interpreted as separate groups that add up to 100%.
The hiring trend suggests that candidates with knowledge of AI, data, cloud computing, software development and other emerging technologies may be better positioned for relevant opportunities. However, individual job requirements will continue to depend on the role, project and experience level.
Is ChatGPT Knowledge Enough to Get an IT Job?
Learning to use ChatGPT and other generative AI tools can help professionals improve productivity, but tool familiarity alone does not necessarily demonstrate job readiness.
Nikhar Arora, Director and Builder of Bots.ai by HR Anexi, told NDTV that widespread AI usage does not automatically translate into organisational capability. Employees may use AI tools regularly without following consistent standards, integrating them into business workflows or checking whether the results are accurate.
His argument highlights the difference between using AI and applying it effectively to solve business problems.
For job seekers, this means that learning prompts and experimenting with AI applications can be a starting point, but developing practical skills is equally important. Candidates should be able to explain how they used technology to complete a task, evaluate the output and improve the final result.
AI Skills Freshers Should Learn to Improve Job Prospects
Students and recent graduates looking to build careers in technology can focus on a combination of AI knowledge, technical fundamentals and practical experience.
1. Generative AI and Prompt Engineering
Understanding how generative AI tools work and how to communicate requirements clearly can help candidates use them more effectively.
Freshers should learn to structure prompts, provide relevant context, assess generated responses and recognise when AI outputs need correction. They should also understand the limitations of AI-generated information rather than accepting every response at face value.
2. Programming and Software Development
Programming fundamentals remain valuable for candidates pursuing software engineering and AI-related roles.
Depending on their career goals, learners can focus on Python, Java, JavaScript, data structures, algorithms, APIs and software testing. Understanding how applications work makes it easier to integrate AI tools into practical projects.
3. Data Analysis and Data Literacy
AI applications often depend on the quality and relevance of the data they process. Basic knowledge of data analysis, SQL, spreadsheets, statistics and data visualisation can help candidates understand business information and evaluate results.
For more specialised AI roles, machine learning, model evaluation and data preparation may also be relevant.
4. AI Automation and Workflow Integration
Businesses are interested in applying AI to actual workflows rather than using it only for isolated tasks.
Candidates can build projects that automate repetitive activities, organise information, summarise documents or assist with customer support. Understanding APIs, workflow design and error handling can help demonstrate practical capability.
5. Critical Thinking and Output Verification
AI systems can generate incomplete, misleading or incorrect information. Professionals need to evaluate outputs, verify important claims and identify situations where human judgement is necessary.
The ability to recognise errors and improve AI-generated work can be as important as knowing how to operate the tools.
6. Business and Domain Knowledge
Understanding the business problem behind a technical task helps professionals choose appropriate solutions.
For example, someone working on a banking project needs to understand the relevant financial processes, while a professional supporting a retail client should understand customer behaviour, inventory or sales workflows.
Combining domain expertise with technology knowledge can help candidates deliver more useful outcomes.
Why Experienced Employees May Have an Advantage in the AI Era
The increasing demand for AI skills does not automatically mean fresh graduates will have an advantage over experienced professionals.
TCS Chief Executive Officer and Managing Director K Krithivasan said that an experienced mid-level engineer who is willing to learn new technologies can have a significant advantage because of their understanding of the technology landscape and business domain.
Experienced employees may already know how enterprise systems operate, how projects are delivered and how client requirements are translated into technical solutions. Adding AI capabilities to that foundation can help them apply new tools more effectively.
Fresh graduates, meanwhile, can benefit from learning emerging technologies early in their careers. They can strengthen their prospects by combining AI knowledge with programming fundamentals, practical projects, communication skills and an understanding of business requirements.
Ultimately, adaptability and the ability to learn are important for professionals at different stages of their careers.
TCS AI Business Reaches 10% of Revenue
TCS’s emphasis on AI skills also comes as the company seeks to expand its AI business and improve profitability.
According to the supplied report, AI accounted for 10% of TCS’s overall revenue in the September quarter. The company expects AI-related engagements to provide margin benefits as projects grow in volume and scale.
Krithivasan said that larger AI deals could support profitability. However, the company has not disclosed the AI component of its reported $9.6 billion total contract value for the September quarter.
TCS also indicated that many client engagements now include some element of AI, although it follows a conservative approach when classifying contracts as AI deals.
The company said clients frequently begin with AI projects in a specific business function. When they see measurable results, they may expand the work to other areas of their organisations.
This approach places greater emphasis on demonstrating business value, which in turn increases the importance of professionals who can connect AI capabilities with measurable outcomes.
Why Companies Need More Than AI Tool Users
AI adoption can appear successful when measured by the number of employees using AI applications. However, widespread usage does not necessarily mean that a company has developed the processes, skills and standards required to benefit from the technology.
According to Arora, businesses need to define which capabilities matter, establish expectations for quality and determine where AI should produce measurable improvements.
For organisations, this may involve providing structured training, setting guidelines for responsible AI use, reviewing output quality and integrating AI into clearly defined workflows.
For employees, it means learning how to use AI in ways that improve accuracy, efficiency or decision-making rather than simply demonstrating familiarity with popular tools.
This distinction is becoming increasingly relevant as employers evaluate candidates for technology roles and businesses look for measurable returns from AI investments.
How Freshers Can Prepare for AI-Focused IT Jobs
Students preparing for recruitment at TCS and other technology companies can take several practical steps to strengthen their profiles:
- Build technical foundations: Learn programming, databases, software development and other fundamentals relevant to the target role.
- Develop AI literacy: Understand generative AI, prompt design, limitations, verification and responsible usage.
- Create practical projects: Use AI to address a specific problem and document the approach, implementation and results.
- Learn a business domain: Explore how technology supports industries such as banking, healthcare, retail or manufacturing.
- Demonstrate problem-solving: Explain how a project works, what challenges arose and how the final solution was evaluated.
- Keep learning: Follow developments in relevant tools and technologies while strengthening core technical knowledge.
Candidates should also review the specific requirements of each job posting. The skills needed for an AI engineering position may differ significantly from those required for software development, consulting, testing or business analysis.
TCS Hiring and the Future of AI Skills
TCS’s hiring mix points to the growing importance of digital capabilities and specialised AI expertise in the IT services sector. With AI accounting for a reported 10% of the company’s revenue in the September quarter, the technology is also becoming an increasingly important part of its business strategy.
However, the broader lesson for job seekers is that learning a popular AI tool is only one part of career preparation. Programming knowledge, data literacy, business understanding, critical thinking and the ability to verify results can help turn AI familiarity into practical workplace capability.
For freshers and experienced professionals alike, the strongest approach is to combine technology skills with continuous learning and the ability to solve real business problems.
