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Sound Practices for Responsible Adoption of Artificial Intelligence (AI): Overview of consultation responses

This document provides a comprehensive overview of the stakeholder feedback received by the Financial Stability Board (FSB) following its public consultation on 'Sound Practices for Responsible Adoption of Artificial Intelligence (AI)'. Initiated on June 10, 2026, the consultation aimed to gather diverse perspectives from financial institutions and other relevant entities on how to foster the responsible integration of AI technologies within the financial sector. The consultation period concluded on July 22, 2026, attracting approximately 160 responses from a wide array of sectors and geographical regions. This report meticulously summarizes the key themes, suggestions, and concerns raised by respondents. Furthermore, it details how this invaluable feedback has been meticulously incorporated into the final version of the sound practices document, underscoring the FSB's commitment to developing robust and inclusive frameworks for AI adoption that balance innovation with stability and risk management within the global financial system. The updated practices reflect a collaborative effort to ensure that AI's transformative potential is harnessed prudently, addressing areas such as cyber resilience, financial innovation, and governance.

AI-driven workforce changes create anxiety but may offer opportunities

Oct 16,26 | 01:40 EST

New research from McKinsey suggests the U.S. economy could create more jobs over the next decade than automation replaces, though millions of workers will need to transition to new roles.

How books are being scanned and destroyed to train artificial intelligence

Oct 16,26 | 01:39 EST

To train artificial intelligence models, millions of physical books are being digitised and destroyed. Our colleagues at France 2 investigate this controversial practice and the risk of seeing many rare second-hand books disappear forever.

The Role of Artificial Intelligence (AI) in Agricultural Credit Underwriting and Scoring

Oct 16,26 | 01:36 EST

This article explores the increasing integration of AI in the banking industry, particularly its potential role in agricultural credit underwriting and scoring. While AI offers speed and efficiency, the authors emphasize the critical need for careful consideration of its implications before full implementation in this specialized sector.

Maximus’ David Chou on grading AI success

Oct 16,26 | 01:35 EST

AI can significantly boost productivity across federal agencies, but the critical and often overlooked challenge lies in the mentally taxing work required by employees to fact-check its outputs. David Chou of Maximus highlights that while federal organizations are increasingly proficient at deploying artificial intelligence tools, the paramount next step is to effectively measure their actual efficacy and demonstrable impact on operational success, ensuring that AI truly adds value rather than creating new burdens.

Companies show off AI technology, new innovation hubs at APTA Expo

Oct 16,26 | 01:32 EST

The American Public Transportation Association's triennial Expo recently gathered nearly 700 companies to unveil their latest advancements in AI technology and innovative infrastructure solutions, signaling a transformative era for public transportation. This key event highlighted significant efforts towards making urban transit faster, more efficient, and more responsive to the needs of modern cities and their commuters.

Anything not tied to artificial intelligence took off this week

Oct 16,26 | 01:31 EST

S&P 500 stocks beyond the realm of AI are on pace for their second-largest weekly outperformance since 2024.

AI ML Now: Gert Desmet on the State of Artificial Intelligence and Machine Learning in Separation Science

Oct 15,26 | 01:43 EST

Gert Desmet explores the current role of AI/ML in separation science.

Opinion: Artificial intelligence needs oversight before it runs amok

Oct 15,26 | 01:42 EST

A reader says artificial intelligence requires real rules before, not after, a disaster.