According to recent statistics from the World Bank (2023), the unemployment rate among the youth labour force (ages 15-24) in Nepal is 21 percent, a slight increase from 20 percent in 2017. This rate is higher than the regional average. Additionally, older statistics from the International Labour Organisation indicate that approximately 26.1 percent of university graduates in Nepal are unemployed. Most of these graduates are employed in routine jobs. With the advent of Artificial Intelligence (AI), many of these positions are at risk of being replaced by AI and automation. As it is often said, "AI won’t replace humans, but humans with AI will replace humans without AI.”

Despite this precarious situation, Nepal is home to an aspirational youth population eager to establish themselves in the growing domestic and foreign economies. These youths need employable skills relevant to today's digital and AI-driven world to climb the economic ladder.

As global digitalisation and the adoption of AI and data science transform various sectors, the demand for new skill sets is increasing both nationally and internationally. Organisations are becoming more AI-driven, rendering many traditional job roles obsolete. Consequently, students worldwide must acquire AI skills to remain competitive in the future job market. This trend is particularly relevant for Nepal's Higher Education Institutions (HEIs), where there is a significant data science and AI skills gap. Data science combines mathematics, statistics, specialised programming, advanced analytics, AI and machine learning to uncover actionable insights hidden within organisational data.

Based on our interactions with students and corporate entities in Nepal, this piece examines the pressing need to integrate data science and AI into Nepal’s HEIs curriculum. Given the low employability rate among university graduates in Nepal, it is imperative to equip them with these essential skills.

Best practices

Addressing these issues requires significant interventions at both policy and strategic levels. India's example reveals a massive impetus from government and private stakeholders on AI skilling over the past several years. Numerous skilling programmes on data science are available in India, ranging from secondary schooling to doctoral levels. Under government initiatives like Skill India, large-scale programmes have been completed and are ongoing to reskill and upskill the workforce in these areas. For instance, many Indian states have introduced Python programming as a compulsory or elective course in secondary school curricula to expose young minds to AI and data skills. Likewise, AI-related courses are going to be added to China’s education system, including primary and secondary schools.

What needs to be done

A similar curriculum intervention is necessary in Nepal to cultivate young Nepali minds with data and programming skills for future AI roles. Currently, only a few top-notch business schools in Nepal have incorporated Python coding into their curriculum. However, this practice is not widespread. For undergraduate and graduate curricula across all professional HEI courses in Nepal, introducing data science skills in applied statistics, R programming, Python programming, SQL, data visualisation (using tools like Tableau), machine learning, and deep learning is essential. Additionally, each data science course should include at least one compulsory industry guest lecture (physical or online) from AI or data science experts, whether from Nepal or globally. This will ensure that students know the latest AI trends relevant to the industry.

Furthermore, there should be more industry-academia collaborative projects wherein industries can offer real-time data science challenges to students through physical and virtual hackathons. From the perspective of skilling HEI educators, upskilling and Faculty Development Programmes (FDP) should be organised to familiarise them with the latest data science and AI tools. Such programmes should be incentivised to motivate educators to engage actively and learn from these opportunities. Educators skilled in these programmes should be encouraged to work on research projects connecting AI to their field of expertise, with the aim of filing patents or copyrights or publishing them in reputable journals. As the world transitions from Industry 3.0 to Industry 4.0 and soon to Industry 5.0, Nepal must also move its industrial and economic sectors in the same direction using AI and data science.

Implementing these interventions would gradually build a culture of AI, data science, and innovation among Nepal's student community, addressing the existing skill gap. Moreover, such initiatives would foster the growth of AI-powered startups in Nepal, providing solutions for various socio-economic and business challenges. Nepal's recent launch of a concept paper on the application and practice of AI is a welcome move. However, it is crucial to formulate how AI can be integrated into the curriculum to ensure that future graduates possess the necessary skills.

In conclusion, by incorporating data science and AI into HEIs, Nepal can better prepare its students for the uncertain future job market and foster innovation and economic growth.