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Traditional business analytics has undergone significant changes thanks to the internet revolution, cloud computing and the shift to self-service analytics, contributing to the recent rise of embedded analytics in business operations. Embedded analytics involves embedding and integrating visualizations, dashboards, reports or predictive analytics in everyday business applications. 

The OECD.AI Policy Observatory is an inclusive platform that brings together resources and expertise from the OECD and its partners to facilitate dialogue and provide evidence-based policy analysis on the impact of AI. It is built upon the foundation of the OECD AI Principles, the first intergovernmental standard on AI adopted in 2019, endorsed by OECD countries and partner economies.

Implementing responsible AI in the financial sector is crucial for ethical practices, fairness, and transparency. Financial institutions must prioritize data privacy, address biases, ensure explainability, and practice ongoing monitoring. By doing so, they build trust, mitigate risks, and foster sustainable growth. 

Traditionally, responsible AI management practices are not just a matter of theoretical ethics debates but a practical matter of compliance. Financial sectors are highly regulated and monitored to ensure the safety and security of consumers and the overall economy. Many of those regulations are written so that responsible management practices are meant to avoid penalties. 

Critical to the definition of robotic process automation (RPA) is the notion that the tasks a 'robotic' software automates are repetitive by nature, with exceptions in rare instances. While RPA cannot independently learn from and adapt to new contexts and workflow problems, it can if the RPA system is imbued with the correct AI capabilities.