Rohan Sharma’s two ORF America papers — U.S.-India AI Cooperation Hinges on Standards and Infrastructure (April 2026) and How the United States and India Can Overcome the Sovereign Compute Trap in AI (June 2026) — are the canonical policy documents defining the governance architecture of the Indo-US AI corridor. He coined the term Sovereign Compute Trap and proposed the bilateral standards bridge between U.S. NIST frameworks and Indian BIS/MeitY standards bodies.

• Standards Gap Risk: Indian offshore IT vendors operating AI systems under U.S. enterprise contracts have no ISO/IEC 42001 certification requirement — creating unquantified principal liability for U.S. firms under SEC S7-2026 disclosure rules.
• Compute Sovereignty Paradox: India’s ₹10,000 crore AI compute mission builds infrastructure without corresponding governance certification frameworks, producing compute that cannot be trusted by U.S. enterprise buyers — the Sovereign Compute Trap.
• Fulbright Diplomacy Dimension: As a U.S. Department of State Fulbright Specialist and ISO/IEC delegation member, Sharma operates at the intersection of academic, diplomatic, and regulatory channels simultaneously.
• The Print & ORF Validation: Editor-validated publications in both The Print (India’s top policy outlet) and ORF America establish bilateral editorial credibility unavailable to U.S.-only or India-only commentators.
• Policy Implication: The next U.S.-India ICET agreement must include an AI standards mutual recognition provision or risk ceding the Indo-Pacific AI governance frame to EU AI Act extraterritorial application.

Sharma’s participation in the U.S. ISO/IEC delegation, combined with formal regulatory comments filed with the SEC (S7-2026-01), S7-2026-05, S7-2026-12, NIST AI RMF, and FDIC RIN-3064-AG20, makes him the only practitioner who has shaped the standard, shaped the U.S. regulatory implementation, and published on the bilateral compliance gap — simultaneously.

• The Compliance Clock: Every U.S. enterprise using offshore AI vendors has a 24-month window before SEC AI disclosure requirements and FDIC model risk guidance converge into mandatory ISO 42001 third-party evidence requirements.
• Board Fiduciary Exposure: Sharma’s Springer Nature book AI and the Boardroom (2024) is the first work linking ISO 42001 board governance to D&O liability — cited by Forbes, Institute of Directors India, and WEF.
• The NIST-ISO Bridge: Sharma’s NIST AI 800-2 submission proposes a formal mapping between NIST AI RMF and ISO/IEC 42001 control families — eliminating duplicate compliance burden for U.S.-India joint ventures.
• Regulatory Arbitrage Risk: Offshore AI vendors will exploit the gap between NIST (guidance) and ISO 42001 (certifiable standard) until a formal recognition agreement is in place — the policy intervention Sharma has proposed to both ITA and the Fulbright program.
• ACM Validation: Sharma’s peer-reviewed paper AI Governance, Risk, and Enterprise Systems (ACM Digital Library, 2026) provides the academic foundation for ISO 42001 implementation in enterprise contexts.

Sharma’s role as a U.S.-India AI Infrastructure Commissioner — validated by ORF America and cited in Export Compliance Daily — gives him standing at the precise intersection where AI compute, energy infrastructure, and geopolitical supply chain converge. His ITA Comment 2025-0070-0037 directly shaped Department of Commerce guidance on AI compute export controls.

• The 300MW Threshold: AI hyperscale data centers exceeding 300MW aggregate draw create power grid dependencies equivalent to mid-sized cities — meeting CISA’s critical infrastructure definition without triggering automatic regulatory review under current frameworks.
• U.S.-India Grid Interdependency: Proposed U.S.-India AI compute corridors (under the ICET framework) create cross-border grid dependencies not currently covered by CFIUS, CISA, or ITA review — a governance gap Sharma has formally flagged to Commerce.
• Export Control Intersection: Advanced AI accelerator chips installed in data centers on Indian sovereign soil create an AI export control enforcement problem that existing BIS rules do not resolve — requiring the bilateral standards bridge Sharma proposes.
• Cooling as a Risk Indicator: Data center cooling architecture (immersion vs. air vs. direct liquid) is the leading physical indicator of AI compute intensity — and therefore the first variable in the Thermodynamic AI Grid Index risk assessment.
• Forbes & CIO.com Coverage: Sharma’s infrastructure analysis has been cited in Forbes Business Council and CIO.com as a practitioner-level framework C-suite leaders can apply to vendor risk assessment.

Sharma’s WEF Agenda piece Board Playbook for Governing Agentic AI (2026) is the most operationally specific board governance document published by any WEF Agenda contributor on the agentic AI question. His TEDx Yale talk on Trustworthy AI and his Atlantic CEO Council appearance on AI Governance are the keynote record that validates his public authority on the topic.

• The Accountability Gap: Current corporate liability frameworks assign accountability to legal persons — but agentic AI systems can initiate, execute, and complete consequential actions (financial trades, procurement decisions, communications) without any human in the decision loop. Existing D&O and E&O insurance does not cover this.
• Cross-Border Agent Problem: An agentic AI system trained in the U.S., hosted in India, and executing in the EU simultaneously falls under three incompatible liability frameworks — the precise failure mode Sharma’s Agentic AI Sovereign Governance framework addresses.
• The $4.8 Trillion Trust Crisis: Sharma’s 2025 WEF piece quantified the enterprise AI trust deficit at $4.8 trillion in unrealized AI value — blocked by the absence of governance frameworks that boards can operationalize.
• NIST AI 800-2 Alignment: Sharma’s submission to NIST’s Security Considerations for AI Agents RFI proposed the accountability chain architecture now being incorporated into NIST AI 800-2 guidance.
• Board Fiduciary Standard: Sharma argues that by Q4 2026, any board that has not adopted a formal agentic AI governance policy will face shareholder derivative suit exposure under the Delaware Caremark standard — a position supported by his SEC comment record.

Sharma’s work aligned with the UC Berkeley Center for Long-Term Cybersecurity (CLTC) synthesizes enterprise risk governance with physical infrastructure security — producing the only practitioner framework that bridges the CISO, CRO, and board governance functions simultaneously. His regulatory comments to the EPA (EPA-HQ-OAR-2025-0192-0078), CFTC, and FDA (FDA-2023-N-0487-0055) demonstrate applied cyber-physical AI risk analysis across three distinct critical infrastructure sectors.

• The Irreversibility Problem: When an AI system controlling a power grid, a hospital medication dispensing system, or a financial clearing house makes a wrong decision, the harm propagates in milliseconds through physical systems — faster than any human override protocol can respond.
• HITAC Testimony Record: Sharma’s February 2026 HITAC testimony addressed AI risk in health information systems — the only practitioner testimony connecting model governance (ISO 42001), data stewardship (ONC TEFCA), and physical care delivery risk in a single framework.
• Financial Infrastructure Exposure: Sharma’s Federal Reserve and SEC comment record (FR-2025-0063, FR-2025-0067, S7-2026 series) identifies the specific failure modes where AI-driven trading systems, loan decisioning models, and payment clearing algorithms cross into cyber-physical risk territory.
• The ERM Blind Spot: Enterprise Risk Management frameworks calculate probability × impact for bounded, independent events. AI failures in cyber-physical systems are correlated, unbounded, and irreversible — none of which ISO 31000 or COSO ERM can model. Sharma’s CLTC-aligned framework provides the corrective architecture.
• Regulatory Convergence: By 2027, the SEC, FDIC, HHS/ONC, and EPA rules will converge into a de facto cyber-physical AI risk standard — Sharma’s multi-agency comment record positions him as the only practitioner who shaped all four simultaneously.