Standardized reporting
Develop uniform global metrics for data provenance, compute and energy use, model performance, and algorithmic bias.
Four pillars for comparable AI governance
A proposed shared foundation for transparent reporting and accountable assessment across AI systems and jurisdictions.
Universal presentation
Make disclosures about AI agents and generated content legible to people, institutions, and systems, with relevant rules such as EU AI Act Article 50 in view.
Comparable assessment
Establish a shared baseline for evaluating safety parameters across physical AI, agentic systems, and foundation models.
Independent auditing
Enable verifiable third-party evaluation against defined safety thresholds and context-specific social and cultural considerations.
Research and resource library
Explore the proposal, presentation materials, and technical resources supporting the initiative.
CONCEPTUAL CHARTER
View foundational proposal →Foundational proposal
The baseline framework connecting financial asset accounting with the governance and disclosure of AI systems.
GENEVA DIALOGUE
View Geneva slides →Presentation suite
Presentation materials prepared for the AI Global Dialogue side event in Geneva on July 7.
UN PORTAL RECORD
View portal record →Global Digital Compact contribution
Read the initiative's listing and contribution record on the UN Digital Cooperation Portal.
DIALOGUE DOCUMENT
Read concept note →Geneva 2026 concept note
Background document for the UN Global Dialogue on AI Governance.
IMPLEMENTATION FRAMEWORK
Read whitepaper →Core technical whitepaper
Technical resource on asset assessment, data parameters, and potential auditing approaches.
Real-world accounting & governance challenges
Recent industry events and regulatory investigations highlighting why global, standardized accounting and disclosure rules (IFRS for AI) are urgently needed.
Meta's experimental data center tax credit
Reports reveal Meta reduced its tax bill by ~$3.9B by classifying commercial AI data centers as 'experimental pilot models'—illustrating the boundary blurring between R&D expenses and core infrastructure assets.
Read article →Senate scrutiny on Big Tech AI tax incentives
U.S. lawmakers are probing major tech platforms over massive capital expenditure tax write-offs and federal subsidies for AI infrastructure, calling for tighter corporate disclosure and standardized oversight.
View Senate probe details →The GPU depreciation paradox
Big Tech schedules extend AI hardware useful lives up to 5–6 years on balance sheets, despite rapidly evolving 1–2 year GPU chip cycles, creating potential multi-billion dollar asset impairment risks.
Read financial analysis →Residual value guarantees & hidden liability
Hyper-scalers and AI providers have entered hundreds of billions in off-balance-sheet commitments and residual value guarantees for AI infrastructure, hiding tail-risk from conventional disclosures.
Explore balance sheet analysis →A global translation engine
An early-stage concept for translating varied regional priorities into a common, auditable framework while preserving their distinct legal and policy contexts.
From policy diversity to practical interoperability
The proposed IFRS for AI Ledger would help organize inputs, guide common disclosures, and track evidence over time. This is a concept under exploration, not a finalized standard.
Inputs · diverse priorities
EU risk tiers · US innovation principles · China core controls · AU Agenda 2063 goals
The engine · IFRS for AI Ledger
A structured approach for translating governance objectives into documented requirements and evidence.
ALIGNGUIDETRACK
Intended outcomes
Auditable global safety · cross-border compliance support · responsible innovation
Partner with us and keep momentum of the Geneva 2026 dialogue
We are convening institutional investors, policymakers, and technical researchers to explore a 6-to-12-month AI-IFRS framework pilot.
Start a conversation
Share your organization's interest in research, policy development, or a pilot. The initiative is led by Pride AI and Business Solutions, Addis Ababa, Ethiopia.