Impact of AI on entry-level campus jobs: How the roles of engineers are being redefined

Time of India

a day ago

As the landscape evolves, specific skills in AI are becoming increasingly valuable, commanding higher premiums. (AI image)
By Dr Neelesh Gupta and Dhruv Dudeja
Per our Campus Workforce Trends Study 2025, entry-level management roles post-MBA typically pay 1.5 times more than entry-level technical roles.
However, for graduates from the top 10 and tier-1 institutions, this salary gap has consistently narrowed over the past five years, decreasing from 2x to 1.5x and from 1.8x to 1.4x, respectively.
Despite this trend, the technology talent landscape faces a growing replacement threat, as AI and GenAI increasingly take over tasks once performed by human talent.
The AI tsunami: Threat or transformation?
Ongoing discussions highlight that leaders increasingly view entry-level roles in technology (such as coding), content creation, customer support, technical helpdesk and translation and localisation as tasks that AI or GenAI can perform more quickly and accurately.
The real-world implications of this perception remain uncertain; it may signal either a replacement of human roles or a simple augmentation of workforce capabilities.
Conversely, the demand for on-site staff to maintain AI data centres or associated facilities may give rise to new job categories, ranging from basic to complex.
The fear factor: Automation anxiety a catalyst for career realignment
As the debate continues, it is clear that GenAI is rapidly becoming part of everyday work.
According to Deloitte's Campus Workforce Trends: Placement Cycle 2025 study, 69 percent of engineering students believe their jobs are at risk due to AI. This apprehension reshapes their learning preferences and redefines their career entry strategies and long-term trajectories.
Roles once considered stable and future-proof, such as QA testing, data processing, level 1 support and documentation, are now being swiftly automated.
Technologies such as chatbots, Robotic Process Automation (RPA) engines and auto-coding assistants perform these tasks with remarkable speed and efficiency. This results in twofold problems for entry-level talent: (a) fear of job loss and (b) missing out on formative critical experiences that define and shape one's career trajectory.
As automation continues to take over routine tasks, the nature of human-led functions in the workplace is undergoing a significant shift.
This change is evident in entry-level campus jobs, where individuals typically begin as 'makers', those who produce content, write code and deliver outcomes as individual contributors.
Traditionally, their work is overseen by slightly more experienced professionals or first-line managers, known as 'checkers', who review and validate what the makers produce. However, this maker-checker model is evolving in two key ways:
• Checkers hold tightly to their roles, often viewing makers as increasingly replaceable due to automation.
• Makers increasingly take on checker responsibilities, diminishing the traditional work hierarchy.
As a result, organisations grapple with either an inflated middle management layer or redundant managerial roles, with each organisation's situation telling its unique story.
Reimagining careers: The emergence of the hybrid engineer-manager
Instead of shunning technical learning, students increasingly gravitate towards hybrid roles integrating technical expertise with business acumen and leadership capabilities.
This evolution is reflected in current skilling trends. While many continue to focus on AI and Data Science, they are increasingly pairing these subjects with leadership, project management and strategic thinking courses.
This shift creates new opportunities in emerging roles, such as prompt engineers, AI support engineers, data annotation specialists, cybersecurity analysts and AI ethics assistants, which require a blend of critical thinking, domain expertise and ethical reasoning.
As the landscape evolves, specific skills in AI are becoming increasingly valuable, commanding higher premiums. Notable in-demand skills include:
AI development and prompt engineering: About 15–20 percent premium
ML engineering: Approximately 15–20 percent premium
Cloud AI and infrastructure: Nearly 5–10 percent premium
Real-time and specialised data analytics: About 10–15 percent premium
These high-demand skills are compelling entry-level professionals to pivot towards them for better compensation and career prospects.
Our report shows that 83 percent of engineering students are now pursuing training in leadership and management. This marks a significant shift, as these were once considered separate career paths.
This trend is driven not only by apprehension but also by ambition. Management positions are perceived as gateways to faster career advancement, broader strategic influence and higher compensation.
Organisations are embracing AI in their campus hiring and cadre management processes
As student aspirations shift, campus recruiters are adjusting their strategies accordingly. Companies are increasingly using AI in their recruitment processes, with clear evidence apparent at three levels:
Smart resume parsing
Automated screening
Skill-based matching
Organisations are also revamping their hiring models to attract tech-plus-business talent.
Fast-track management programmes, rotational leadership roles and digital transformation fellowships are gaining popularity. Recruiters now prioritise applied skills, hands-on project experience and cross-functional adaptability over traditional academic metrics.
Preparing for an AI-augmented workforce
The mantra 'AI for all and all for AI' is becoming essential for students and organisations. Its adoption spans various levels:
Academic institutions: Approximately 20 percent of institutions are integrating AI into their curricula and administrative processes, using tools for personalised learning and automated admissions. For example, MIT employs AI for real-time feedback, enhancing student engagement.
Individual students: Students use AI-powered platforms for personalised tutoring and writing assistance, enhancing academic outcomes. Notably, about 83 percent of tier-1 students now use AI-generated mock interviews, job-specific simulations and automated profile audits.
Organisations: Companies are adopting AI to optimise operations by employing data analytics for customer insights and using AI tools in HR to enhance recruitment while personalising employee training. This adoption showcases AI's transformative impact on decision-making across various sectors.
Conclusion: Redefining the role of engineers
India Inc.'s
graduating class of 2025, along with those of the coming years, will continue to experience the impact of AI-driven disruption. The surge in AI solutions and their ability to deliver precise results will shape the future paths of engineers, prompting many to reskill or shift towards management roles.
At the same time, India Inc. stands at a pivotal juncture where jobs are being redefined. As roles evolve, campus curricula will adapt and the mindset of future generations will shift accordingly.
This transformation necessitates a re-evaluation of traditional talent models. Employers and educators must invest in developing multidimensional capabilities that bridge the divide between code and commerce.
In the GenAI era, success hinges less on static knowledge and more on the ability to adapt and grow with emerging technologies. Engineering students are already responding to this shift by actively seeking out cross-disciplinary skills, blending technical expertise with leadership, strategy and innovation. Engineering students are already demonstrating a deep understanding of this imperative.
(Dr Neelesh Gupta is Partner, Deloitte India and Dhruv Dudeja is Director, Deloitte India)
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