Why TCS Changed Its Bench Policy
Tata Consultancy Services (TCS) has introduced a significant change to its talent deployment policy, setting a new benchmark for employee utilisation. Under the revised guidelines, all employees are now mandated to be billed for a minimum of 225 days, with a reduced allowable bench time to 35 days per year. “At any given point in time, associates must have been allocated for a minimum period of 225 business days in the last 12 months, failing which, necessary due diligence and appropriate management action will be exercised,” read an internal company email verified by AIM. “Benching” is an ordinary term in Indian IT services, which refers to employees who remain on the company payroll but are not actively engaged in client projects or other billable tasks. These employees are essentially “on the bench”, standing by as available resources for future projects. Although some amount of bench time is unavoidable, its management is crucial. This is the reason behind TCS’ bold, performance-driven policy shift—a move aimed at fostering learning and greater accountability among employees. However, such a policy is primarily designed to drive maximum resource utilisation, which is expected to improve business margins. On the sidelines, this structured upskilling is meant to keep pace with the rapid evolution of AI. Survival of the Fittest While artificial intelligence (AI) is reshaping service delivery by introducing automated processes, predictive analytics, and intelligent systems, companies like TCS are under pressure to optimise their human capital for high-value, tech-driven projects. Students and aspiring IT professionals, meanwhile, get a loud wake-up call: the industry rewards skills tailored to AI and digital innovation. “All new joiners are expected to have an allocation from day one of joining the organisation. In case of any deviation, such associates should connect with the concerned RMG on an immediate basis for guidance,” the mail read. This policy, overseen by regional general managers (RGMs) and utilisation-focused dashboards, ties employee performance directly to revenue-generating projects. It reflects TCS’ drive to maximise resource efficiency amid a global IT spending slowdown, projected at 6.8% growth in 2025. As seen in the earnings call, TCS reported weaker-than-expected Q4 results, with revenue and net profit falling short of analyst projections. Moreover, TCS typically distributes annual increments between April and July. However, this year, the company has deferred the decision, citing macroeconomic uncertainty, as Milind Lakkad, chief HR officer, indicated during a post-earnings call. Alouk Kumar, founder and CEO of Inductus Group, told AIM that global clients are increasingly demanding faster project turnarounds and AI-integrated solutions, reducing the tolerance for idle resources. To address this, TCS aims to curb bench-related costs, which, as he mentioned, are estimated to account for 8-10% of its payroll, especially given its operating margin of 24.6% in FY24. Moreover, automation is diminishing the demand for low-skill roles, pushing the company to redeploy talent to high-value AI/ML, cloud, and cybersecurity projects. “In the event of an associate’s failure to comply with the provisions of this policy, the organisation reserves the right to take disciplinary action—including cessation of service, as per the organisation’s disciplinary action framework,” the mail read. Failure to meet billable targets could result in consequences such as salary freezes, deferred appraisals, or even performance-based exits, which have historically affected 1–2% of TCS’ workforce of over 6 lakh employees annually, Kumar highlighted. He further added that this policy reflects a broader shift within the Indian IT industry, where companies like TCS, Infosys, and Wipro are transitioning from labour-arbitrage models to innovation-driven growth. To this, Biswajeet Mahapatra, principal analyst at Forrester, said, “While the new bench policy does not explicitly mandate AI adoption, it underscores the increasing importance of upskilling in AI, automation, and other emerging technologies to remain competitive and relevant in the IT sector.” Need for Urgent Upskilling With AI expected to automate a wide range of IT tasks, including coding and testing, traditional bench roles may shrink. TCS is addressing this by reskilling 3.5 lakh employees in AI/ML, GenAI, and digital platforms. The upskilling initiative focuses on tools like Azure AI, AWS SageMaker, and low-code platforms. Neeti Sharma, CEO at TeamLease, told AIM that organisations are looking for freshers who are not just digitally literate but also have skills that can help them incorporate, use and create AI, GenAI and agentic AI tools and models. The 225-day billable target incentivises employees to upskill proactively but exposes systemic challenges. Reports indicate that only 20% of India’s 1.5 million annual engineering graduates are AI-ready, creating pressure on internal reskilling programs. Positively, it offers access to TCS’ robust learning ecosystem, including AI certifications and in-house hackathons, enabling career mobility toward roles like AI solution architects. In the long run, the policy has the potential to reshape India’s IT talent pipeline by driving academia-industry collaboration and widening inequality for non-elite graduates. In essence, TCS’ new bench policy serves as a microcosm of the Indian IT sector’s AI-driven transformation, balancing opportunity with intense pressure for its current and future workforce. For TCS Employees However, the 35-day cap heightens anxiety, especially for employees in commoditised roles—for example, legacy Java developers—who face fiercer internal competition for billable projects. Furthermore, “project availability” is also seen as a job satisfaction factor, and reduced bench time could spike attrition among mid-career professionals with five to 10 years of experience. The strict bench time rules and mandatory work-from-office (WFO) policies may lead to increased stress among employees, while potentially reducing flexibility, which could result in talent attrition. There is also a risk of focusing too heavily on utilisation rates, which might hinder innovation within the organisation. One Reddit user pointed out a potential downside of TCS’s new policy, suggesting that employees may get threatened or blackmailed by RMGs to take irrelevant roles. Another LinkedIn user commented that TCS’s push for structured learning is a smart approach, but it needs to be paired with mentorship and realistic timelines. Hybrid work flexibility is increasingly seen as the future of work, and mandatory WFO during bench periods may alienate valuable talent. Moreover, performance should not solely be measured by billing hours—value also comes from contributions to R&D, internal innovation, and readiness efforts.Furthermore, project volatility could leave employees stranded on the bench despite efforts to redeploy them.
With AI expected to automate a wide range of IT tasks, including coding and testing, traditional bench roles may shrink.
With AI expected to automate a wide range of IT tasks, including coding and testing, traditional bench roles may shrink. 
["Indian IT", "TCS"]
["GenAI", "artificial intelligence", "agentic AI", "AWS", "AI", "ML", "predictive analytics", "RAG", "Aim", "analytics", "Indian IT", "TCS"]
["AI", "artificial intelligence", "ML", "analytics", "GenAI", "agentic AI", "Aim", "RAG", "predictive analytics", "AWS"]
Shalini is a senior tech journalist, exploring the latest advancements in AI. When she's not reporting on the latest innovations, you can find her immersed in her next literary adventure.