India’s New Labour Codes represent the most significant transformation of the country’s labour law framework since Independence. While the consolidation of multiple legislations into four Codes promises simplification and flexibility, the real challenge lies in organisational implementation—particularly for manufacturing enterprises with complex workforce structures and legacy industrial relations (IR) practices. This article examines the practical challenges faced by human resource (HR) and IR leaders in implementing the Labour Codes and proposes solution pathways grounded in workforce architecture rather than compliance minimalism. It argues that the Codes reset labour cost structures through wage redefinition, expanded social security and formalised collective bargaining, converting previously deferred costs into visible and auditable obligations. These changes exert direct pressure on workforce composition decisions, often triggering reactive restructuring that can undermine long-term stability. The article analyses the strategic deployment of permanent employees, Fixed Term Employment, contract labour and apprentices under the new regime, with particular focus on restrictions on contract labour in core activities, governance of exception scenarios and risks arising from indiscriminate conversion of contract workers into Fixed Term Employees. It highlights the critical role of skill-based wage architecture in preventing industrial disputes and positions apprenticeship as a strategic pipeline feeding into Fixed Term and permanent roles. The article further explores how the Industrial Relations Code strengthens bipartism and tripartism through mandated grievance redressal mechanisms and structured collective bargaining, creating a pressing need for IR capability building within organisations. It concludes that successful implementation of the Labour Codes depends not on checklist compliance, but on HR leadership’s ability to integrate cost governance, workforce design and institutional maturity into a coherent, future-ready strategy.
This article examines the transition from legacy labour regulations to the new Occupational Safety, Health and Working Conditions (OSH) Code in India. While legal consolidations often focus on administrative efficiency, this piece prioritises the human element—exploring how the new code impacts worker dignity, health and gender parity. By contrasting the historical ‘paper-only’ compliance culture in India with stringent international standards, like the Occupational Safety and Health Administration (OSHA), the analysis highlights the shift from transactional compliance to a relational social contract. Key focus areas include the formalisation of the informal workforce through appointment letters, the proactive approach to preventive healthcare, the modernisation of workplace definitions and the inclusion of the gig economy.
This article is an open and honest attempt to analyse the challenges for different personas in implementing the new labour law from the way I see it as Fractional Chief Human Resources Officer (CHRO) lens. The New Labour Codes are no doubt a great step towards the new evolving business and people of the digital economy. As the New Labour Code aims to simplify the major regulatory reforms aiming at beginning compliance efficiency, it is also a fundamental change in the approach. Despite the consolidation of multiple labour statutes and the promise of enhanced transparency, the effective implementation of these reforms has generated significant uncertainty across organisations and administrative systems. In this article, I am adopting a stakeholder-centric, practical challenges on the floor in implementation, while also emphasising a conceptual approach based on policy analysis and stakeholder mapping to examine implementation challenges associated with the New Labour Codes. The analysis focuses on four key stakeholder groups: senior leadership, human resource (HR) professionals, employees and HR technology platform providers.
The two major National Labour Commission (NCL) reports, first in 1969 and the second in 2002, suggested improvements for industrial relations and addressed worker protections, leading to major reforms such as the four Labour Codes. The second National Commission on Labour (2002), constituted in 1999, focused on rationalising the existing labour laws into four functional codes (wages, industrial relations, social security and safety/working conditions). It emphasised labour flexibility and, for the first time, focused heavily on the unorganised sector, advocating for an umbrella legislation for their protection. These reports serve as the foundation for the Ministry of Labour & Employment in shaping India’s modern labour laws. The codification of 29 central labour laws into four Labour Codes in 2020 represents one of the most significant labour law reforms in post-Independence India. While the stated objectives of the reforms include simplification, ease of doing business and expanded worker protection, their implications for Human Resource Management (HRM) are complex and contested. This article critically examines the impact of the Code on Wages, 2019 ; the Industrial Relations Code, 2020 ; the Code on Social Security, 2020 and the Occupational Safety, Health and Working Conditions (OSH) Code, 2020 on HRM practices in India. Drawing on doctrinal legal analysis and secondary literature, the study argues that although the Labour Codes promise long-term efficiency and workforce formalisation, they simultaneously intensify compliance responsibilities, redistribute power in industrial relations and reposition HRM as a strategic governance function rather than a purely administrative role. The article highlights implementation challenges, equity concerns and state-level variations that complicate the realisation of the Codes’ stated objectives.
This article provides a comprehensive comparative analysis of India’s newly implemented Labour Codes against the established US labour law framework. Drawing from over a decade of global practitioner experience, the study deconstructs complex legal statutes such as the Code on Wages, the Industrial Relations Code and the Code on Social Security. The analysis highlights critical divergences in gratuity eligibility, wage structures and gig worker protections. Written in plain English to ensure accessibility for non-legal professionals, this research utilises comparative tables and practical examples to equip human resources (HR) leaders with the clarity needed to navigate the evolving cross-border employment landscape.
This article provides a comprehensive analysis of the practical challenges faced by human resources (HR) professionals in interpreting and implementing India’s unified labour legislation framework, which consolidates 29 central labour laws into four major Codes: Wages, Industrial Relations, Social Security and Occupational Safety, Health and Working Conditions (OSHW). While the reform aims to simplify compliance, enhance ease of doing business and extend social security coverage, significant ambiguities and interpretive gaps remain between the legislative text and operational guidance. Key challenges include confusion over effective dates, wage definitions, variable pay treatment and benefit computations, which impact payroll design, compliance risk and employee relations. Drawing on practitioner feedback and official policy documents, the article identifies critical areas of uncertainty and proposes solution pathways such as harmonised frequently asked questions (FAQs), cross-Code consistency, illustrative computation examples, stakeholder consultation mechanisms and safe harbour provisions. The article emphasises that successful implementation requires HR leadership to evolve from transactional compliance to governance stewardship, bridging legal, business and workforce welfare imperatives. Ultimately, the transformative potential of the New Labour Codes depends on clarity and integrity in their operationalisation.
Organisations need both effectiveness and efficiency to remain competitive. In a BANI world (Brittle, Anxious, Non-linear and Incomprehensible), accelerated change is the norm rather than the exception. With the advent of the internet, the rules of business changed substantially. The traditional set of metrics that provided a competitive edge, such as location, business scale and volumes, and financial strength, lost significance. The human equation in an organisation continues to be a significant metric of competitive strength. The quality of manpower is a critical source of effectiveness and efficiency. Company management must today focus on the agility to embed technological advances to remain competitive. In this context, we enumerate and emulate a key artificial intelligence (AI) initiative taken by Balmer Lawrie, a Government of India enterprise.
This article explores how artificial intelligence (AI) and data analytics are fundamentally transforming human resource management (HRM) from an administrative function to a strategic pillar in organisations. AI enhances decision-making, boosts employee retention, and streamlines key human resource (HR) functions like recruitment, learning and development (L&D) and performance management. Key benefits include improved hiring accuracy, personalised employee development and data-driven performance evaluation. The article emphasises the importance of ethical AI use, addressing concerns around bias, data privacy and the need for human oversight. India is emerging as a leader in AI adoption in HR, especially in sectors like information technology (IT) and small to mid-sized enterprises. However, challenges such as workforce readiness, upskilling and change management remain critical for successful implementation. The article concludes that while AI offers unprecedented efficiency and personalisation, its integration must remain rooted in ethical, inclusive and human-centric practices.
This article explores the critical role of human resources (HR) leadership in founding and establishing educational start-ups. The article examines three key dimensions: (a) the formation and selection of founding teams, (b) the development of organisational culture and values in early-stage institutions, and (c) practical challenges and strategies for HR leaders in educational start-ups. The findings reveal that successful founding teams prioritise chemistry and complementary skills over technical competencies alone, that organisational values should emerge organically after basic systems are established, and that HR leaders in educational start-ups must possess multi-functional capabilities beyond traditional HR domains. The article provides actionable insights for founders and HR professionals entering the educational start-up ecosystem.
This article proposes a comprehensive transformation of India’s teacher education system to address quality concerns in school education and prepare the workforce for 2040 and beyond. With India approaching 100% literacy by 2040, the focus has shifted from enrolment to quality education delivery. The study identifies three key triggers for transformation: the need for quality education, rapid global changes over the past 30 years (since the inception of the National Council for Teacher Education (NCTE)), and currently being unfolding with the rapid penetration of artificial intelligence (AI) in our lives and work, and inadequate teacher education approaches. Six transformation principles are outlined, including upgrading teacher education institutions in the government hierarchy, segregating policymaking from implementation bodies, treating teachers as national assets, implementing a medical college model, mandatory teacher recertification and formal leadership training. A two-tiered organisational structure is proposed with specialised programmes for first-time teachers, teacher educators, school leadership, continuous professional development (CPD), recertification and upgradation. The framework emphasises practical experience through school integration, standardised assessments, and a centralised portal for teacher management. The article concludes that world-class teacher attraction, selection, training and development will address most challenges in India’s school education system.
Teaching practices in classrooms have evolved dramatically—from traditional content delivery to content curation and now moving towards content creation with the support of artificial intelligence (AI). We may classify the various advancements in teaching into three or four major phases in the history of education: (a) The era of chalk and talk; (b) the introduction of smart classrooms or the pre-COVID phase; (c) post-COVID phase—concentrated on curation of content by teachers; (d) the AI phase—creation of content. In the 20th century, teachers were the primary source of information, delivering knowledge through lectures, chalk and talk. The arrival of the internet and digital platforms shifted the role of teachers towards curating resources and relevant content from vast online repositories. Today, AI is driving a new phase—teachers and students collaboratively creating content. AI-powered simulations enable educators to design personalised lesson materials, quizzes and learning experiences within minutes. A 2024 HolonIQ survey found that 48% of teachers in developed countries use AI to generate teaching aids, while pilot projects in Finland and Singapore show AI reducing lesson prep time by up to 30%. In this article, we will discuss if AI is really going to replace teachers or is it just an extension of their creativity in the classroom.
This study explores the evolving understanding of school leadership in India through the lens of both contemporary theory and lived experiences. Drawing on semi-structured interviews with four school principals from diverse Indian cities, the research investigates how leadership is defined, enacted and challenged in everyday practice. The article reviews existing models of educational leadership while tracing the historical trajectory of leadership in the Indian context. In doing so, it foregrounds the importance of cultural and temporal specificity in shaping effective leadership competencies. The study suggests that leadership cannot be divorced from its sociocultural and institutional setting; instead, it must be continuously reinterpreted through the needs of time, place and audience. Indic philosophical traditions, such as the Gurukul system and thought frameworks by figures like Swami Vivekananda and Rabindranath Tagore, are discussed as potential epistemological resources that could inform a more rooted and holistic approach to leadership.
This reflective article by G. Viswanath explores the value and impact of formal education through the lens of personal experience and the Montessori method. The author recounts a journey through 11 years of traditional schooling, followed by a Bachelor of Science degree and a rigorous 2-year MBA at IIM, questioning the lasting lessons imparted by these academic pursuits. While advanced degrees fostered skills in communication and self-confidence, the author remains sceptical about their effectiveness in imparting deeper life lessons or practical wisdom. The piece suggests that prevailing educational structures focus predominantly on preparing students for the job market, often at the expense of nurturing curiosity, critical thinking and genuine learning. In contrast, the Montessori approach is highly practical: emphasising self-directed discovery, intrinsic motivation and holistic development. Through this introspective account, the article challenges readers to reconsider the ultimate objectives of education and to seek pedagogical methods that cultivate not just employable skills, but also personal growth, adaptability and lifelong learning. It invites educators and learners alike to value lessons that extend beyond the classroom and to rethink what it means to be truly educated. ‘Learning to learn’ is essential, while rote learning and high academic scores are often valued at the expense of what will help the learner grow as a person, a professional and a significant contributor to the very society they are a part of.
This article examines the evolving role of Human Resources (HR) in Indian schools, arguing for a shift from transactional administration to Strategic Human Resource Management (SHRM) that directly advances teaching quality and student outcomes. Drawing on sector context and practitioner experience, the article analyses HR structures across public and private schools, detailing persistent challenges in recruitment, retention, professional learning and policy implementation, It explores emerging priorities such as staff well-being, DEIB (Diversity, Equity, Inclusion, and Belonging), digital HR systems, and leadership that promotes learner agency and staff empowerment. Central to the analysis is employee voice as a catalyst for cultural and policy change, illustrated through practices in international schools across India, with a focus on The British School, New Delhi. The article outlines HR’s role in fostering inclusive cultures and translating staff feedback into actionable policies. It also presents a practical framework for Continuous Professional Development (CPD) through workshops, mentoring, and global collaborations, aligning people strategy with educational vision.
This article is derived from my personal experiences and examines the transformation of talent acquisition practices in K-12 schools across Indian metropolitan cities in the post-COVID era, drawing from over a decade of professional experience in educational recruitment. The research analyses sources, processes, challenges and emerging trends in acquiring quality teaching talent across metro markets. The findings reveal significant shifts in recruitment strategies, persistent talent gaps, and evolving expectations from both employers and educators. The study contributes to understanding the contemporary landscape of educational talent management in India’s rapidly evolving school systems, based on first-hand operational insights from facilitating thousands of teacher placements.
The article discusses the intersection of artificial intelligence (AI) and human resource (HR) analytics, emphasising the need for indigenous frameworks in AI, particularly in the Indian context. It highlights how data has become a critical resource, leading to the rise of HR analytics, which integrates information technology (IT) infrastructure with statistical tools for data-driven decision-making. However, the advent of AI represents a significant disruption, automating decision-making processes and necessitating a re-evaluation of existing frameworks. The authors argue that AI applications often reflect Western epistemologies, perpetuating biases and overlooking indigenous knowledge systems. This ‘Western Universalism’ marginalises diverse cultural perspectives, particularly in management and social sciences. The article critiques the dominance of Western frameworks in knowledge creation and dissemination, suggesting that this has resulted in a lack of representation and innovation in indigenous contexts. The authors also address the ethical implications of AI, particularly algorithmic bias, which can reinforce societal inequalities. They provide examples of biases in contemporary AI tools, such as ChatGPT and Google Bard, which have been found to censor sensitive information or exhibit gender bias in decision-making processes. The article concludes by advocating for developing indigenous AI frameworks that incorporate local knowledge systems and address diverse populations’ unique challenges. This approach aims to create more equitable and inclusive AI applications that benefit a broader segment of society. The authors call for further research into the implications of human-algorithm interactions and the need for accountability in AI practices to mitigate biases and promote fairness in organisational decision-making.
Traditional compensation systems often struggle to adapt to dynamic market conditions and evolving regulatory requirements with the necessary agility. This research article advocates for the adoption of artificial intelligence (AI)-based compensation systems as a transformative solution, enabling organisations to transition to fair, equitable and responsive frameworks. These systems leverage real-time data to support decision-making during periods of change and uncertainty. AI-powered compensation models foster structured, unbiased decision-making while enabling hyper-customisation of compensation packages to promote diversity and inclusion. The article highlights practical use cases for AI adoption, illustrating how these systems can drive fairness and efficiency. However, it also addresses potential hurdles, including ethical considerations, algorithmic bias, substantial investments and data privacy challenges. Ultimately, adopting AI-based compensation systems is not merely a technological upgrade but a continuous learning journey that empowers organisations to create equitable, innovative and future-ready compensation practices.
The article presents a comprehensive analysis of 15 key principles essential for implementing responsible artificial intelligence (AI) and proposes a practical framework for their evaluation; this includes the three core principles: Explainability, interpretability and ethics. As AI systems become increasingly integrated into society, ensuring their responsible development and deployment has become crucial. The article examines fundamental concepts, including explainability, interpretability, ethics, reliability, safety, robustness, privacy, security, fairness and non-discrimination, human-centric values, inclusive and sustainable innovation, accountability, explainability, transparency, trustworthiness and counterfactual explanation. For each principle, the article provides precise definitions, identifies relevant stages in the AI lifecycle for investigation, and outlines specific metrics and tools for measurement. Building on this analysis, the research introduces a structured evaluation framework featuring a detailed questionnaire that organisations can use to assess their AI systems. The assessment utilises a 1–5 rating scale for each concept, where 1 represents ‘not implemented’ and 5 indicates ‘fully implemented and optimised’. The article also proposes a weighted scoring system that can be customised based on specific use cases or industry requirements. For instance, healthcare AI applications might weigh safety and privacy more heavily, while AI systems that are used in hiring and recruitment might emphasise fairness and non-discrimination. This adaptability ensures the framework’s relevance across different domains and applications. The framework presented serves as a foundation for incorporating and assessing key principles of responsible AI and developing standards in the rapidly evolving field of AI.
