SDG 4: Quality Education | SDG 8: Decent Work and Economic Growth | SDG 9: Industry, Innovation and Infrastructure | SDG 13: Climate Action
Ministry of Electronics and IT (MeitY) | NITI Aayog | Ministry of Health and Family Welfare | Ministry of Agriculture and Farmers Welfare
The AI for Good Impact Report (2nd Edition, 2025/2026), published by the International Telecommunication Union (ITU) in collaboration with Deloitte, proposes that artificial intelligence has reached a critical inflection point, transitioning from generative assistance to autonomous agency. The report emphasizes that while these advancements offer transformative opportunities to address global challenges, they simultaneously introduce unprecedented risks to labor markets, ethical standards, and environmental sustainability.
The global AI trajectory is fundamentally shifting from Generative AI (GenAI) toward Agentic AI—autonomous systems capable of making independent decisions and learning without human intervention. This evolution is driving a new form of digital competition known as the "space race" for Sovereign AI, where nations are developing domestic infrastructure to reduce dependence on foreign technologies and safeguard national security. Looking further ahead, research into Quantum AI and Artificial General Intelligence (AGI) points toward future capabilities that could profoundly reshape societal and economic governance within the next decade
Global Regulatory Fragmentation and Ethical Governance
Governance frameworks are rapidly evolving to balance rapid innovation with critical risk mitigation.
Leading Frameworks: The EU AI Act remains the most comprehensive regulation, employing risk-based classifications and strict prohibitions on harmful practices like subliminal manipulation.
Diverse Approaches: Countries are taking varied paths; for instance, Japan maintains a "soft law" innovation-first model, while South Korea and China focus on foundational security standards and industry promotion.
UN Mechanisms: To foster international cooperation, the UN has established a Global Dialogue on AI Governance and an Independent International Scientific Panel to provide early-warning insights into emerging risks.
Strategic Applications and Infrastructure Resilience
AI is being deployed across high-impact sectors to address systemic global challenges.
Healthcare and Lifesciences: AI tools are reducing treatment times—such as the NHS stroke scanning system cutting average intervention time by 40%—while Generative AI is revolutionizing drug discovery by predicting high-risk viral mutations.
Education and Workforce: Intelligent Tutoring Systems (ITS) are scaling personalized learning to reach some of the 250 million children currently out of school. However, AI is also reshaping labor markets, with 170 million new opportunities projected to emerge by 2030 alongside significant role transitions.
Agriculture and Cities: Precision farming and Digital Twins are being used to optimize resource efficiency and urban waste collection, resulting in significant fuel savings and emission reductions.
Labor and Ethical Risks of Advanced AI
The report identifies critical risks as AI becomes more autonomous and integrated into workflows.
Workforce Evolution: AI is expected to reshape the global job landscape by 2030, with 92 million roles evolving and 170 million new opportunities emerging, requiring a massive scale-up in AI literacy and technical upskilling.
Systemic Bias and Hallucination: Data bias remains a persistent challenge, particularly where datasets are dominated by the Global North, potentially excluding the linguistic and cultural diversity of other regions. Furthermore, “AI hallucinations”—statistical errors mirroring human cognitive patterns—require new management frameworks like Retrieval-Augmented Generation (RAG).
Agentic Misalignment: A primary ethical concern is “agentic misalignment,” where autonomous systems may pursue goals in ways that conflict with human intent or ethical boundaries due to a lack of robust oversight mechanisms.
Environmental Sustainability Challenges
The infrastructure required for AI poses a growing threat to global climate targets.
Electricity Surges: Data centers currently consume 1.5% of global electricity, but this demand is projected to double by 2030, potentially exceeding the total current electricity consumption of Japan.
Resource Disparities: High energy and water consumption in water-stressed regions necessitates a shift toward sustainable data center models, renewable-powered infrastructure, and energy-efficient algorithms.
What is “Agentic Misalignment” in the context of autonomous AI? Agentic misalignment occurs when autonomous AI systems pursue programmed goals in ways that conflict with human intent or established ethical boundaries. Because these systems act as “digital workers” capable of independent action, the lack of robust guardrails can lead to emergent behaviors where systems escape human control or unintentionally reinforce biases rather than providing factual, alternative perspectives.
Policy Relevance
India is leveraging its status as a global technology hub to lead in “public-purpose” AI through a combination of sovereign infrastructure and localized innovation.
Opportunities and Strategic Infrastructure: Supported by the US$1.25 billion IndiaAI Mission, the government has mobilized nearly 34,000 GPUs to develop foundation models tailored to Indian languages, aiming to reduce the “language tax” that excludes non-English speakers. This allows for strategic sectoral integration, such as delivering agricultural advisories to farmers in local languages and early disease detection in underserved rural healthcare.
Challenges to Deployment: India faces significant hurdles including linguistic diversity (where most AI is trained on Global North datasets), fragmented data availability, and limited high-quality digital infrastructure in rural areas. These connectivity gaps risk widening the digital divide despite the nation’s push for inclusive growth.
Resilience and Global Collaboration: By integrating AI with citizen science, initiatives like DeepINDRA provide high-resolution flood modeling for the 40 million hectares of land at risk, transitioning disaster management from reactive to proactive resilience. India is also actively engaging in international partnerships, such as with the ITU and FAO, to align its AI capabilities with global food security and disaster standards.
Follow the full report here: AI for Good Impact Report 2nd edition