SRM-AP Launches AI-Integrated M.Sc. Economics and Psychology Programmes

The Easwari School of Liberal Arts at SRM University-AP in Amaravati has formally launched two rebuilt postgraduate programmes: M.Sc. Economics and M.Sc. Psychology. Both degrees now carry mandatory AI integration throughout their curricula, not as supplementary modules but as core structural elements.

Prof. Ch Satish Kumar, Vice Chancellor of SRM AP, framed the decision bluntly during the launch event. "The future belongs to those who can combine strong domain expertise with AI capabilities. Whether in economics or psychology, understanding the discipline alone is no longer enough." The statement reflects a broader shift in higher education where technical fluency is becoming a baseline requirement rather than a differentiator.

According to The Hindu's coverage, the university positions itself among the first institutions to introduce this level of integration in postgraduate education. The programmes are designed for a technology-driven world, equipping students with advanced analytical, research, and applied skills through interdisciplinary learning, hands-on training, and AI integration.

Dean of ESLA, Vishnupad, drew a distinction between this approach and typical AI offerings. AI is often treated as an add-on in many programmes, but at ESLA, it is deeply interwoven into the curriculum, complementing and enhancing disciplinary learning. This matters because students shouldn't have to toggle between two separate skill sets—domain knowledge and AI tools—when the real world demands they operate simultaneously.

The M.Sc. Economics programme combines strong economic theory with AI-driven tools to address complex global challenges. Assistant Professor B. Srujana from the Department of Economics explained that it integrates policy frameworks, data science, and computational methods to generate real-world insights. Students will likely spend significant time in front of screens running regression analyses, building predictive models, and interpreting outputs from machine learning algorithms.

The M.Sc. Psychology programme takes a different but equally practical angle. Assistant Professor and Head of the Department of Psychology Ayesha Parveen Haroon described it as a research-intensive degree designed to meet the growing demand for skilled psychologists in technology-enabled environments. It blends core psychological science with AI-based applications across mental health, organisational, and educational domains. Imagine a future therapist using AI to track patient sentiment patterns over months, or an organisational psychologist deploying automated assessment tools for workplace wellbeing.

Scholarships and fee concessions of up to 100% are available for eligible candidates, ensuring accessibility for high-achieving students. This financial structure suggests SRM-AP is betting on volume and quality simultaneously—offering full rides to attract top talent while maintaining programme standards.

Director of Admissions Y. Siva Sankar, Associate Dean Vandana Swami, Professor Parag Jayant Waknis, Assistant Professor Ubaid Mushtaq, and Director of Communications Pankaj Belwariar were present at the launch. The presence of multiple senior faculty members signals institutional commitment beyond marketing optics.

Independent reporting from EdexLive corroborates the timeline and scope of the changes. The coverage confirms the programmes were unveiled in Vijayawada, Andhra Pradesh, with emphasis on interdisciplinary learning and hands-on training.

The timing is notable. The Hindu article was published April 29, 2026, placing this announcement within the current academic cycle. Universities that integrate AI this aggressively are making a bet on curriculum longevity—these programmes must remain relevant as AI tools evolve rapidly.

There's a physical reality to this shift that students will feel immediately. Instead of traditional lecture halls where professors deliver content and students take notes, expect more computer labs, more screen time, more debugging sessions. The tactile experience of learning economics or psychology now includes wrestling with code, navigating data visualisation tools, and interpreting algorithmic outputs. It's less about passive absorption and more about active manipulation of digital systems.

Industry impact remains to be seen. Employers in economics and psychology sectors will need to recalibrate hiring expectations. A graduate with AI-integrated training should theoretically command higher starting salaries, but only if the job market actually values this hybrid skill set. (Many hiring managers still treat AI as a buzzword rather than a practical competency, which complicates things.)

Competitive positioning is another factor. Other universities will likely follow suit, creating a new baseline for postgraduate education in these fields. The first-mover advantage SRM-AP claims may erode within 12-18 months as peer institutions announce similar programmes.

Whether students actually pay for it remains the real question. Scholarships help, but the core issue is whether graduates can demonstrate tangible value from this AI integration. A degree with AI training means little if employers cannot verify those skills during hiring. Portfolio projects, capstone demonstrations, and industry partnerships will matter more than course descriptions.

The announcement represents a pragmatic adaptation to technological change rather than a revolutionary break. Universities have always updated curricula to match labour market demands. This is simply the latest iteration, with AI replacing whatever came before it as the essential technical competency.

For prospective students, the decision calculus is straightforward. If you're entering economics or psychology in 2026 or later, AI fluency is no longer optional. The question is whether SRM-AP's implementation delivers genuine competency or merely credential inflation. Time will tell, but the structural commitment appears genuine based on faculty involvement and curriculum design.

Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt Connect on LinkedIn