CEO speaks: Industry-academia collaboration: A must for AI workforce
Artificial Intelligence (AI) is no longer a futuristic concept—it is an undeniable force transforming industries, economies, and job roles at an unprecedented pace. From automating complex processes in manufacturing to revolutionising medical diagnostics, from reshaping financial services through fintech to redefining creativity with GENAI, the impact of AI is everywhere. Yet, as industries rush to integrate AI-driven solutions, a glaring problem has emerged—the widening gap between the skills the workforce needs and the training that universities provide.
The World Economic Forum (WEF) predicts that by 2025, nearly 85 million jobs will be displaced due to automation, while 97 million new AI-augmented roles will emerge. Yet without robust skill pipelines, these opportunities may remain unfulfilled. A staggering 75% of companies globally report difficulties in finding AI-skilled talent, despite a surge in AI-driven job openings. Traditional higher education, built on rigid curricula and theoretical instruction, is struggling to keep pace with the rapid evolution of AI. The conventional degree model, which prioritises textbook knowledge over hands-on experience, is proving inadequate in an era where employers demand immediate industry readiness.
India, despite being a global technology powerhouse, faces a similar predicament. The country produces over a million engineering graduates annually, yet many lack the practical AI and data science expertise required by the industry. The root cause lies in outdated curricula that fail to keep up with industry trends, leaving students with theoretical understanding but little exposure to real-world AI applications. At a time when AI is evolving at breakneck speed, universities cannot afford to operate on slow, bureaucratic academic cycles. A shift is urgently needed—one that moves away from knowledge-heavy degrees toward a skill-first, competency-driven education model.
To bridge this gap, universities must embrace experiential learning, where students are immersed in real-world problem-solving rather than passive classroom instruction. AI cannot be effectively taught through textbooks alone; it requires practical exposure to datasets, machine learning models, and real-time AI deployment. Universities should establish AI labs, where students can work on industry-led projects, gaining hands-on experience with the latest technologies. Additionally, incorporating global capability-based certifications—such as TensorFlow Developer Certificates, AWS AI/ML Specializations, or Microsoft AI Engineer Certifications—into AI programs can offer students direct industry validation of their skills, making them far more employable than a degree alone ever could. We, at Sister Nivedita University (SNU), Kolkata are already integrating industry leading courses and certifications from Coursera into our pedagogy and curriculum.
Beyond technical proficiency, the evolving nature of AI and Industry 5.0 demands a holistic skill set that integrates human intelligence with artificial intelligence. Industry 5.0, which emphasises human-AI collaboration rather than pure automation, requires workers who not only understand AI but also know how to apply it ethically, responsibly, and innovatively. Universities must, therefore, expand AI education beyond engineering disciplines, making AI literacy a core part of business, healthcare, law, and humanities programs.
A crucial aspect of bridging the AI skills gap is fostering stronger industry-academia collaboration. Universities cannot prepare students for AI-driven careers in isolation; they need active participation from the industries that will ultimately employ these graduates. One way to achieve this is through co-op education models, where students alternate between classroom learning and real-world internships, ensuring they graduate with both theoretical knowledge and hands-on expertise. Tech giants like Google, NVIDIA, and OpenAI are already at the forefront of AI research, and their involvement in academia—through curriculum co-development, guest lectures, and AI boot camps—could help keep university programs aligned with real-world demands. However, if the prime movers in the AI arena continue to be focused solely on individual market dominance through tightly controlled research, humanity as a whole stand to lose out on creating the next generation of human capital that shall take this giant leap forward!
Countries that have successfully addressed the AI talent deficit, such as Germany, Canada, and Singapore, have done so by embedding industry participation into higher education. India must follow suit by encouraging universities to develop joint AI research initiatives, corporate training partnerships, and startup incubation programs focused on AI innovation. Creating AI-focused centers of excellence, where students and faculty collaborate with industry experts on cutting-edge AI challenges, could significantly enhance the employability of graduates.
The future of work is changing faster than most universities can adapt, and unless higher education institutions take the lead in AI workforce preparation, the talent gap will continue to widen. AI is set to be the defining technology of the 21st century, and it is universities that must ensure that the next generation is equipped not just with theoretical knowledge, but with the practical skills to thrive in an AI-driven world. The future belongs to those who can seamlessly integrate human intelligence with artificial intelligence—and it is up to our education system to make that future a reality.
The author is the Group CEO of Techno India Group, a visionary and an educator. Beyond his corporate role, he is also a mentor who guides students towards resilience and self-discovery
