বাংলা · The Impact of AI
Verified reporting, original sources and clear analysis of what changes for people.
2026-09-28 · UK edition · 113 reports across the archive
Translation is temporarily unavailable. This page currently shows the UK English original. Open the UK edition.
In a 1,719-person global survey, more respondents report AI helping their own productivity than report a measurable effect on company earnings. The gap deserves scrutiny, not a promise of inevitable returns.
Goldman Sachs data cited by Reuters projects record gross hyperscaler issuance next year. Investors are asking whether data-centre returns justify the scale and concentration of borrowing.
ECB Governing Council member Fabio Panetta said central banks need to understand how AI-driven gains are distributed because the split between wages, profits and prices will shape demand and inflation.
The IMF says AI is compressing time in trading, credit and supervision, making operational resilience, third-party oversight and cross-border coordination more important.
An IMF analysis argues that the largest systemic concern is AI's ability to accelerate and spread attacks across common technologies used by many financial institutions.
The Bank's July Financial Stability Report assesses AI through core decision-making, markets, service-provider concentration and the changing cyber threat environment.
Cambridge Judge Business School's 2026 report brings together researchers and institutions including the BIS, IMF, World Bank and regional development bodies to assess AI in financial services.
A BIS bulletin argues that AI affects demand, supply, trade and asset prices at different speeds, complicating the task of reading inflation and underlying economic capacity.
The BIS reports that AI-related investment is rising rapidly and examines how a build-out initially funded by large technology-company cash flows is drawing in more debt and outside capital.
An ECB research bulletin examines how the architecture of algorithmic systems can shape financial stability when many institutions use related data, models and decision rules.
A BIS Financial Stability Institute paper reviews emerging policy and supervisory approaches to data used by AI in financial services, where quality, permission and provenance determine downstream fairness and reliability.
Banks are warning that software able to choose and purchase products creates new fraud, privacy and accountability risks. Convenience will depend on clear consent and reliable redress.