India’s Skilling Gap Is an Inclusion Gap: Why Urban Slum Youth Must Be Central to Improving Workforce Outcomes

Over the past decade, India has made deliberate and sustained investments in skilling infrastructure. Through Skill India and allied initiatives under the Ministry of Skill Development and Entrepreneurship, training capacity has expanded rapidly, enrolments have scaled, and industry participation has deepened. This expansion has laid a strong foundation for workforce preparedness, particularly in term sof scale and access.

At the same time, government data indicates that the next phase of skilling reform must focus on inclusion and outcomes. The Periodic Labour Force Survey (PLFS) 2022–23 shows that more than two-thirds of India’s urban workforce continues to be engaged in informal employment, with young workers disproportionately represented in low-skill and low-security roles. While participation in short-term training has increased, the transition into stable, higher-quality employment remains uneven- — especially for young urban workers in informal settings.

The Parliamentary Standing Committee on Labour, in its reviews of skilling programs, has constructively highlighted this gap. Its observations emphasise that certification targets are often achieved without proportional gains in job retention or wage progression after placement, particularly for candidates from economically vulnerable urban backgrounds. These findings are not a critique of intent or effort, but a signal that program design must evolve to reflect the realities of diverse learner cohorts.

Urban slum youth occupy a unique position within this landscape. They are physically close to economic opportunity yet face structural constraints that limit continuity in skilling and employment. Many enter programs with interrupted schooling, limited exposure to formal work environments, and immediate income responsibilities. When skilling systems are designed around uninterrupted attendance and linear progression, these learners struggle to remain engaged. The challenge, therefore, is not participation, but sustained inclusion across the training-to-employment path.

Digital and AI Readiness Is Becoming Foundational to Employability

India’s policy discourse increasingly recognises the importance of future-ready skills. Reports by the NITI Aayog emphasise that adaptability, digital fluency, and continuous learning will shape employability in the coming decade. This shift reflects broader changes in the labour market, where technology is embedded across sectors rather than confined to specialised roles.

Urban youth are not digitally disconnected but they are often underprepared for fomal work environments. Smartphone access in cities is widespread, and exposure to digital platforms is common. However, government and industry data reveal that structured digital readiness remains uneven. The India Skills Report 2024–25 indicates that overall employability remains just above the halfway mark and declines sharply for candidates without post-secondary education or stable learning pathways. This gap is particularly visible in urban informal settlements.

Artificial intelligence brings this challenge into sharper focus. Entry-level roles in retail, logistics, customer support, and services increasingly require interaction with AI-enabled systems. These roles do not demand advanced technical expertise, but they do require confidence in engaging with unfamiliar tools, asking structured questions, and refining responses through iteration. For many urban slum youth, the barrier is not capability, but unfamiliarity with structured workplace- oriented digital systems.

Government program evaluations implicitly recognise this. Reviews by the Ministry of Skill Development and Entrepreneurship have noted weaker learner engagement and lower completion rates in longer-duration courses for vulnerable cohorts. This suggests that digital and AI literacy must be treated as foundational learning capabilities, not optional add-ons, if skilling systems are to remain effective.

Retention and Progression Are the Next Frontier of Skilling Reform

One of the most valuable insights emerging from Parliamentary reviews is the emphasis on retention and progression. Enrolment figures, while important, do not capture whether learners are able to complete training and transition into sustainable employment. Dropout patterns reveal where systems need to adapt.

PLFS data and program evaluations suggest that disengagement among urban informal youth is driven primarily by competing income needs, family responsibilities, and loss of learning confidence. This underscores the importance of designing skilling systems that are flexible, supportive, and responsive to early signs of disengagement.

Technology can play a constructive role here when embedded with human support systems. Learning platforms generate data on attendance, pace, and engagement that can help identify learners who may need additional support. When used responsibly, such insights enable early, human-led intervention rather than retrospective reporting. The International Labour Organization has consistently highlighted the effectiveness of early support mechanisms in improving retention among vulnerable youth.

India already has promising examples of how this approach can work in practice. Community-anchored skilling models that combine local delivery, digital platforms, and sustained learner support demonstrate that technology can strengthen inclusion when paired with mentoring and counselling. Organisations such as NIIT Foundation have operationalised elements of this model at scale, using technology-enabled learning within human support systems to help learners overcome fear of unfamiliar tools and remain engaged through their skilling journey.

As India advances towards a more technology-enabled economy, the focus of skilling policy is rightly shifting from scale to quality and inclusion. Urban slum youth represent both a challenge and an opportunity within this transition. With targeted design improvements that treat digital and AI readiness as foundational, measure retention alongside enrolment, and accommodate non-linear learning journeys, India’s skilling ecosystem can convert demographic potential into durable workforce outcomes.

This evolution builds on the strengths of existing institutions and reflects India’s confidence in refining its systems to meet the demands of a changing economy.

References

1. https://www.indiabudget.gov.in/budget2024-25/economicsurvey/doc/eschapter/echap08.pdf
2. https://www.business-standard.com/industry/news/house-panel-skill-programmes-local-needs-pmkvy-skill-gap-reports-125081000274_1.html
3. https://www.urbanagendaplatform.org/sites/default/files/2020-09/challenge%20of%20slums%20_0.pdf
4. https://niti.gov.in/sites/default/files/2025-10/Roadmap_for_Job_Creation_in_the_AI_Economy.pdf
5. https://wheebox.com/assets/pdf/ISR_Report_2024.pdf
6. https://www.msde.gov.in/static/uploads/2024/11/4f71465f72e9f90ff079f76ca2e374a9.pdf
7. https://www.ilo.org/sites/default/files/2024-09/GET_2024_EN%20web.pdf
8. http://niitfoundation.org/transforming-education-through-technology-the-role-of-learning-management-systems-lms/