Base talent erosion in the AI era: Why entry-level hiring needs a reset

AI automation, the structured, repetitive tasks that once served as the primary entry point for IT newcomers are rapidly becoming obsolete, raising concerns about the longevity of their skills. As per the PwC report, only 28 per cent of entry-level workers believe half or fewer of their current skills will still be relevant in three years.

It may not be feasible to safeguard every entry-level role. This reality is compelling the tech industry to explore alternative pathways and redefine the skill sets required for entry-level jobs to prevent base-level talent erosion, critical to building future leaders.

AI skills are becoming universal

While roles most vulnerable to downsizing are largely rule-based and easy to automate, organisations are concurrently unlocking new opportunities by redesigning jobs and investing in AI-focused upskilling to meet the evolving demands of entry-level talent.

Leaders share that entry-level roles are becoming more skill-focused and value-driven from the outset, where professionals are expected to work alongside AI tools and harness their potential.

According to Giridhar G V, CEO – APAC & Global CHRO, HGS, early-career roles are becoming far more dynamic and learning-driven than before. New career paths like AI trainers, data specialists, prompt engineers, and AI operations professionals have emerged in just the last 12-18 months. Career growth, too, is increasingly shaped by adaptability and AI fluency rather than tenure alone.

Shefali Rai, CHRO, InMobi and Glance, pointed out that today’s graduates need to move beyond foundational coding; they must possess a deep understanding of AI accelerators, hardware-software co-design, and model-level optimisation, among others.

With increasing demand for talent in areas such as AI, cloud, cybersecurity, data, and digital engineering, Tech Mahindra has prioritised a skills-focused approach to match the evolving needs of technology and clients. Richard Lobo, Chief People Officer, Tech Mahindra, reiterated that the current shifts in entry-level hiring should be seen as a transformation rather than a contraction of opportunities.

Though core engineering roles remain foundational, Comviva has also seen increased demand for AI and machine learning talent, data and platform engineering capabilities, product analytics expertise, cloud and cybersecurity skills, and AI-enabled product development roles.

“The redesign of entry-level roles reflects the growing convergence of product innovation, data, and AI. AI literacy is becoming a foundational skill, including the ability to effectively use AI copilots and generative AI tools. Also, data fluency, or the ability to interpret insights and use data for problem-solving, is now expected across most roles,” said Bhagwati Chhabbarwal Shetty, CHRO, Comviva.

Ayaskant Sarangi, CHRO, Mphasis, opined that entry-level roles need to evolve to reflect the changing demands of the industry. Familiarity with AI-powered tools and platforms such as GitHub Copilot, ChatGPT, and AI-enabled Integrated Development Environments (IDEs) has also become a key differentiator in modern software development environments.

“Most of the freshers continue to work in programming roles, but we are equipping them with training in AI tools and technologies to enhance their capabilities. This blend of structured learning, practical experience, and mentorship ensures a well-rounded skilling experience for freshers,” said Sarangi.

The broader strategy adopted by UST is to make AI skills universal rather than limited to specialist teams. Freshers are increasingly expected to develop AI fluency alongside technical, problem-solving, domain, and customer-facing skills, with opportunities to progress into AI engineering, AI-enabled delivery, data engineering, solution architecture, and consulting pathways as their proficiency grows.

Rebuilding talent through multi-pronged strategies

Organisations have opted for a multi-faceted approach with a primary focus on early-talent development initiatives, AI-focused upskilling, academic partnerships, and talent filtering through hackathons to meet the evolving talent needs.

HGS has introduced post-onboarding AI upskilling programs to bridge the skill gap. While UST has prioritised widespread AI capability rather than reliance on scarce external talent. The firm has a large-scale AI upskilling initiative that trains more than 25,000 employees (over 80 per cent of its workforce) in AI.

The company has further embedded AI into its capability architecture through role-based learning pathways and programs such as AI Orchestrator, AI Architect tracks, Next-Generation AI Engineer initiative, and integration into everyday roles across work streams.

InMobi and Comviva have dedicated Finishing School and Early Career programs focused on building foundations across technology, domain expertise, and AI.

S&P Global’s investment in early-career talent is primarily through interventions such as role-based, curated AI learning roadmaps, access to tools, including the Kensho Spark Assist, and enabling skills-based career mobility through the internal ‘Talent Marketplace’. The firm has also invested in ‘$10 million Step Forward’ initiative to equip the next generation to succeed in an AI-enabled work world.

Moving away from volume-based hiring

As roles evolve, companies are increasingly shifting from campus-driven, volume-based hiring to a more selective, capability-led approach that prioritises skills, adaptability, and job readiness over sheer scale.

Moving beyond traditional lateral hiring, InMobi has prioritised doubling down on early-career talent to cultivate “AI-Native” professionals. “Instead of waiting for talent to emerge, our approach is to engage students long before they enter the job market. This resulted in higher retention rates at the 18-month mark due to a clearer sense of purpose. The goal is to build a robust pipeline of AI-specialized engineers by investing in the potential of today’s students,” Rai said.

The firm has launched collaborative curriculum development and longitudinal hackathons as a primary talent funnel for second-year students, directly driving 30 to 40 per cent of all campus hiring this year.

About 98 per cent of the engineering graduates were trained through the MetaGeeks programme at Mphasis. The programme has a pre-placement offer and a structured internship integrated into the students’ final-semester academic journey. Over a 3–4-month period, selected students get exposure to emerging technologies, work on real-world business projects, and have hands-on apprenticeship opportunities across delivery locations.

UST has also invested in building academic partnerships, including digital skills bootcamps, internships, and structured graduate programs to rebuild entry-level pathways.

Whereas S&P Global has leveraged career fairs, engagement events, hackathons, virtual sessions, and other targeted channels to connect with a wider talent pool.

There is a focus on including students from a wider mix of universities, backgrounds, and pathways. Internships and apprenticeships are supported through defined learning journeys, regular check-ins, and program experience.

“While academic background continues to play a role, we place greater emphasis on attributes such as learning agility and adaptability, as well as role-relevant skills. Refreshed and relevant job family architectures enable interns, apprentices, and entry-level hires to channel their efforts to contribute meaningfully,” said Bhavna Batra, Vice President – People, India and Enterprise Data Organisation, S&P Global.

Preserving the talent pipeline

Today’s lateral talent can step into project-based or consultant-style contractual roles largely because they benefited from strong early-career learning opportunities. When organisations neglect early talent today and limit their initial industry exposure, it not only creates skill gaps at an individual level but also weakens the very foundation of the talent pyramid across the industry.

Seena Mohan, Senior HR Business Partner, UST, pointed out that a leaky talent pipeline does not become visible only when leadership gaps emerge; it starts much earlier, when organisations reduce the intake, development, and progression opportunities for early-career talent. The right response is not reactive hiring later; it is proactive pipeline design now.

Shetty of Comviva opined that organisations need to focus on creating AI-enabled career pathways rather than viewing AI as a substitute for early-career talent. A bigger risk is not job displacement today, but a shortage of experienced talent five to ten years from now.

He added that the ‘AI Transformation & Capability’ programme rolled out by Comviva last year was instrumental in baselining skills after the first year and identifying high-potential talent for accelerated development, ensuring a strong pipeline of future experts and leaders.

Looking ahead, the organisations that will lead in an AI-first world are those that treat early talent not as expendable, but as essential to long-term resilience. The future of work will belong to companies that proactively invest in developing this next generation, ensuring a steady pipeline of skilled professionals and future leaders.