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Feb 19, 2026
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Artificial Intelligence
Global
From Policy to Practice: Stanford’s New Model for Governing AI in Global Enterprises
NewDecoded
3 min read
Image by Stanford
Stanford researchers and luxury conglomerate LVMH have introduced a new governance model to help global corporations deploy artificial intelligence responsibly across diverse business units. The Adaptive RAI Governance (ARGO) framework balances central coordination with local autonomy to ensure ethical standards are met without stifling innovation. This research addresses the growing gap between abstract corporate principles and their messy, real-world application.
The collaboration involved a year of study within LVMH, a massive enterprise with 200,000 employees and 75 distinct subsidiaries. Researchers identified that centralized mandates often struggle because local units face different regulations and market demands across 190 countries. ARGO provides a structured toolkit that allows these subsidiaries to adapt high-level ethics to their specific operational needs.
The framework operates through three interdependent layers starting with a shared foundation of non-negotiable standards. This includes global baselines for privacy and mandatory triage tools to identify high-risk applications immediately. A middle layer offers centralized support through reusable assets and training, while the final layer empowers local teams to conduct their own oversight and reporting.
Efficiency is a primary focus of this flexible approach. Instead of every department building its own ethics protocols, they can utilize shared templates and fairness testing modules. This reduces duplication of effort and allows for rapid scaling with minimal additional costs beyond essential leadership roles. Stanford scholar Kiana Jafari notes that even simple measures, like regular cross-departmental forums, can significantly improve consistency.
By focusing on visibility rather than rigid control, the model ensures that executives understand where AI is used without creating bureaucratic bottlenecks. Mandatory human-in-the-loop reviews and regular audits help maintain public trust. This transparency protects the corporate brand while allowing the business to capture the full utility of generative tools in a competitive global market.
As the industry shifts from the speculative hype of previous years toward the rigorous evaluation expected in 2026, the ARGO framework signals a move toward operational maturity. In an era where generative AI scandals and regulatory pressure are mounting, corporations can no longer rely on vague ethical charters. This shift toward localized accountability means that responsible AI is moving from a marketing buzzword to a standard line item in global risk management. For the broader industry, it suggests that the most successful companies will be those that treat ethics as an integrated feature of their business architecture rather than an external constraint.
