For decades, Indian higher education has focused on deep disciplinary knowledge. But as industries adopt AI-driven processes, digitize their workflows, and face unprecedented complexity in decision-making, employers are increasingly seeking graduates who can think critically, adapt swiftly, and collaborate creatively.
To meet these requirements, the landscape of undergraduate education requires a fundamental rethinking, as three essential modern competencies have become critical for all students regardless of their field of study: computational thinking, AI literacy, and design thinking.
These skills are no longer a question of technological specialization but have become foundational literacies necessary, just like reading text or arithmetic. Every graduate, whether they are an artist, scientist or a lawyer, needs to understand how to work with AI, think algorithmically, and solve problems creatively.
The 21st century demands a paradigm shift in how we prepare future generations, moving beyond the acquisition of discipline-specific knowledge to the cultivation of versatile and adaptable skillsets. Modern education must equip students not just with content knowledge but with frameworks for problem-solving, technological understanding, and innovation.
Three essential competencies
Today’s rapidly evolving workplace and society require three core competencies that should be integrated into all undergraduate programs:
Computational thinking and problem-solving: This involves breaking complex problems into manageable parts, recognizing patterns, creating abstractions, and developing step-by-step solutions. Contrary to common misconception, computational thinking extends far beyond programming or computer science — it’s a universal approach to problem-solving applicable across disciplines.
AI tools and applications: As AI rapidly transforms industries and daily life, understanding its fundamentals has become crucial. AI literacy means comprehending how machines simulate human learning, problem-solving, decision-making, and creativity. Students need to understand AI’s applications, limitations, and ethical implications to navigate an increasingly AI-integrated world.
Design thinking and innovation: This human-cantered approach to innovation integrates user needs, technological possibilities, and business requirements. The five-phase process—empathize, define, ideate, prototype, and test—provides a structured yet flexible framework for developing creative solutions to complex problems.
These skills have valuable applications across different fields.
Arts
In the arts, the synergy of computational thinking, AI tools, and design thinking has transformed creative processes and outcomes. Artists now decompose complex creative challenges into algorithmic components while using AI-powered tools like generative design systems and digital composition assistants to expand their creative horizons beyond traditional limitations. This technological foundation is complemented by design thinking’s human-centered approach, where artists deeply engage with audience needs through empathy, prototype iteratively based on feedback, and create more resonant work.
For example, a theatre director might use computational thinking to analyse successful performance structures, leverage AI to visualize different staging possibilities, and apply design thinking to understand audience experiences — resulting in productions that are both technically innovative and emotionally impactful.
Commerce
Business professionals have revolutionized commercial practices by integrating computational thinking’s systematic problem-solving with AI-powered analytics and design thinking’s customer-centric approach. Market analysts apply computational patterns to decompose complex market dynamics while simultaneously employing AI tools for predictive modelling, sentiment analysis, and automated customer segmentation. These data-driven insights are then filtered through design thinking methodologies to ensure innovations truly address customer pain points through extensive empathy work, rapid prototyping, and iterative testing.
This integrated approach has transformed everything from product development to service delivery — for instance, a retail business might use computational thinking to optimize inventory algorithms, implement AI-powered personalization systems, and apply design thinking to create seamless omnichannel customer journeys that dramatically increase satisfaction and sales.
Science
The scientific community has embraced the powerful combination of computational thinking, AI tools, and design thinking to accelerate discovery and enhance real-world impact. Researchers systematically decompose complex natural phenomena into testable components using computational frameworks while leveraging sophisticated AI systems for data analysis, simulation, and prediction that would be impossible through human capacity alone.
Design thinking principles then guide how scientific discoveries translate into practical applications by ensuring research questions address genuine stakeholder needs and solutions are tested with end-users before full implementation. For example, climate scientists might apply computational thinking to model environmental systems, use AI to process vast satellite datasets and predict future scenarios, and implement design thinking to develop climate adaptation strategies that communities will actually adopt — creating a virtuous cycle where science becomes both more rigorous and more relevant.
Law
The legal practice has been transformed through the integrated application of computational thinking’s systematic analysis, AI’s processing capabilities, and design thinking’sclient-centeredd approach. Legal professionals now decompose complex cases into structured components and recognize precedent patterns while implementing AI-powered tools for predictive case outcome analysis, automated document generation, and comprehensive legal research. This technological foundation is humanized through design thinking methodologies that place client needs at the centre of legal service delivery through empathetic understanding, clear problem definition, and iterative solution testing.
A forward-thinking law firm might use computational thinking to develop standardized approaches to common legal challenges, implement AI tools for contract analysis and risk assessment, and apply design thinking to create legal services that clients find more accessible, transparent, and valuable—ultimately delivering better outcomes while improving client satisfaction.
Integration with curriculum
A comprehensive approach to integrating these skills would involve courses tailored to each major, ensuring relevance to students’ primary fields while developing these essential cross-disciplinary competencies. For example, Arts students would focus on computational thinking for creative expression and algorithmic approaches to artistic creation, while commerce students would learn computational methods for business process optimization and data analysis. Similarly, the AI curriculum for science students would emphasize research applications and scientific modelling, while law students would explore legal technology applications and ethical implications.
Implementing these changes requires thoughtful curriculum restructuring and resource allocation. However, the benefits far outweigh these challenges. The most successful graduates will be those who can apply their disciplinary knowledge through these modern frameworks.
Push for NEP goals
The National Education Policy (NEP) 2020 emphasizes multidisciplinary learning, critical thinking, and digital literacy. This proposed curriculum aligns seamlessly with its vision.
Rather than add more content to already packed programs, we need to rethink what and how we teach. These courses will enhance — not replace — traditional subjects by making students more adaptive, employable, and innovative.
Universities that integrate these three competencies as core requirements will foster critical thinking, problem-solving, innovation, and adaptability in all graduates — skills that transcend specific career paths and prepare students to address complex challenges in an ever-evolving world.
As we plan curriculum revisions for coming academic years, integrating computational thinking, AI literacy, and design thinking offers a blueprint for educational transformation that will shape higher education for decades to come. The future will not belong to those who memorize answers, it will belong to those who know how to ask the right questions — and design better solutions.
(N. Siva Prasad is a former professor of Mechanical Engineering at IIT Madras)
Published – April 16, 2025 08:34 pm IST