Industry experts have called for India to develop its own artificial intelligence safety framework rather than replicating the White House Accord on Super Intelligence signed on September 29 by US President Donald Trump and major technology firms. According to Business Standard, Nasscom Chairman Srikanth Velamakanni emphasized that India should not simply replicate the US model, instead using domestic commitment as a building block toward global AI safety understanding. The accord commits companies to internal controls, dedicated oversight teams, independent external audits, and board-level oversight, with regular meetings to set safety standards. Soumen Mandal from Counterpoint Research noted that India doesn't need to copy the US model but can take inspiration from it, while Amit Khanna from Grant Thornton Bharat stressed that any commitment should be suited to Indian market conditions, given India's focus on building AI applications rather than major foundational models.
According to reports from Business Standard, Jacob Coxon, former OpenAI and Anthropic employee, warns that humanity faces potential extinction within this decade due to uncontrolled artificial intelligence development. The concern centers on superintelligence capabilities that may improve faster than researchers can understand or control, creating dangerous feedback loops where capability outpaces oversight. This development has led to what experts describe as a race toward self-improving superintelligence, with many countries viewing themselves as mere bystanders to technological advancement concentrated in the United States and China. Velamakanni warned that voluntary, self-regulatory approaches are necessary but woefully insufficient, citing pharmaceuticals and aviation as examples where strong regulators have strengthened safety without stopping innovation.
As reported by Business Standard, the European Union AI Act has established the world's first binding AI law, creating a risk-based regulatory architecture that prohibits harmful practices, imposes transparency requirements on high-risk systems, and places obligations on general-purpose AI models. The EU market's significance encourages developers worldwide to adopt these standards, though the framework is primarily structured around risk-by-use considerations rather than capability-driven risk assessment. This approach may prove insufficient as future frontier models could evolve from relatively low-risk applications to perform increasingly consequential tasks.
According to Business Standard, India possesses 1.45 billion people, contributes nearly 17% to global economic growth, and maintains strong influence across the Global South. The country's success in building digital infrastructure at unprecedented population scale strengthens its ability to shape global superintelligence debates. India has adopted a pragmatic approach toward AI regulation, focusing on developmental goals and productivity improvements rather than frontier capabilities. The country's vibrant startup ecosystem could contribute world-class solutions to AI governance challenges. India's national strategy for AI is driven by a vision of inclusive growth and societal transformation and was articulated in the 2018 Paper. This has since evolved into the comprehensive IndiaAI Mission, approved in March 2024 with a substantial budget outlay of ₹10,371.92 crore (approximately USD 1.2 billion) over five years. The mission is structured around seven strategic pillars that provide a comprehensive framework for AI development and governance.
Industry experts have advocated for a hybrid approach combining mandatory rules with voluntary standards to address AI safety effectively. According to Business Standard, Mandal from Counterpoint Research suggested mandatory rules for potential harms in defence, healthcare, banking, and government use cases, while voluntary standards would cover fast-moving technical areas. Khanna from Grant Thornton Bharat called for a 'techno-legal' approach pairing strong voluntary compliance with binding mandates, such as provisions on synthetically generated information in the IT Amendment Rules, 2026. Gopalan from Gnani.ai favored self-regulation, stating that mandatory regulation can stifle competition and lead to concerns about preferential treatment. The experts agreed that any framework must ensure autonomy lags behind assurance to provide a margin of safety, with top concerns including large-scale cyberattacks, electoral interference, and loss of control over highly autonomous systems.
According to Business Standard, the Reserve Bank of India (RBI) has taken the most advanced sectoral approach toward AI governance, releasing the Framework for Responsible and Ethical Enablement of Artificial Intelligence (FREE-AI) report for regulated financial entities in 2025. The framework addresses governance, accountability, audits, explainability, cybersecurity and risk management for AI systems used in banking and financial services. SEBI amended the SEBI Intermediaries Regulations in 2025 to formally introduce provisions relating to AI and machine learning use by regulated entities in securities markets. New 2026 regulations mandate that AI-driven trading agents that "learn" and adjust strategies in real-time must be pre-approved by SEBI, requiring "Decision Logic Documentation" ensuring auditable decision-making during market volatility. The Ministry of Health and Family Welfare launched the Strategy for Artificial Intelligence in Healthcare for India (SAHI) aimed at safe and ethical deployment of AI in healthcare ecosystems. The proposed Digital India Act is being designed to replace the IT Act, aimed at introducing risk-based classification for AI systems, while the Department for Promotion of Industry and Internal Trade (DPIIT) is exploring regulations for AI training data including licensing and royalty regimes for copyrighted content.
