AI Articles and Analysis about Data management

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. 

As nearly every American household has realized over the last year, large language models combined with generative AI abilities pose tremendous challenges and opportunities for enterprises of every shape and size. Just ask anyone who has heard of ChatGPT.

AI initiatives that cannot find ROI have no use in modern business. However, the path to ROI from enterprise-wide digital transformations is never a straight and narrow road. A pre-pandemic survey from MIT Sloan Management Review and Boston Consulting Group found that 70% of companies among those surveyed reported no value from their AI investments. 

While accounting as a discipline has roots going back to the 13th century, current-day accounting software is still based on manual record-keeping just as it was in the 1990s, only with digital checks in a digital checkbook register, allowing users to keep track of their finances on a computer.

This article is sponsored by Riskified, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines.
The advent of the COVID-19 pandemic is leaving retail and eCommerce enterprises awash in numerous, often chaotic trends, many of which are proving critical for driving AI adoption throughout the industry. Perhaps most prominent among these market dynamics is an enormous shift to online retail.

In the era of big data, companies need help navigating through an overwhelming volume of unstructured data to uncover meaningful insights. The topic search process presents unique challenges in deciphering data signals and identifying critical information before problems escalate.

AI adoption poses several challenges for organizations, including the need for specialized skills and expertise, integration with legacy systems, data quality and accessibility, and the ethical implications of AI.