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Powering the future: How Gen AI and AI illuminate utility companies

CIO Business Intelligence

AI can help by proactively monitoring operations and flagging when an organization is at risk for non-compliance. AI models can also help evaluate risks, and generative AI can offer suggestions for mitigating those risks. Read about unstructured data storage solutions and find out how they can enable AI technology.

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COVID-19 Effects on Financial Services & Managing Risk

bridgei2i

How much will the bank’s bottom line be impacted depends on a host of unknowns. The banking sector globally is definitely going to see impact, some more grave than the others and most of them are announcing short to mid term measure both from a customer and business risk mitigation standpoint. Understanding & Managing Risks.

Risk 52
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7 Enterprise Applications for Companies Using Cloud Technology

Smart Data Collective

Cloud technology results in lower costs, quicker service delivery, and faster network data streaming. It also allows companies to offload large amounts of data from their networks by hosting it on remote servers anywhere on the globe. Centralized data storage. Multi-cloud computing.

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Retailers can tap into generative AI to enhance support for customers and employees

IBM Big Data Hub

With the rise of highly personalized online shopping, direct-to-consumer models, and delivery services, generative AI can help retailers further unlock a host of benefits that can improve customer care, talent transformation and the performance of their applications.

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Governance and Fighting the Curse of Complexity

CIO Business Intelligence

Moreover, new sources of ever expanding data produced by generative AI and the unfettered growth of unstructured data introduce even more challenges. Data at rest. Data in motion. Risk considered in vendor contracts. Here we can look at monday.com, Asana, Trello, Hive, Zoho, and a host of others.

IoT 64
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Top Cloud Data Security Statistics for 2023

Laminar Security

With the mass adoption of the cloud, businesses of all sizes and industries gained access to the vast amounts of data generated by their own operations, their customers, and the market at large. The global datasphere is estimated to reach 221,000 exabytes by 2026 , 90% of which will be unstructured data.

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IBM and ESPN use AI models built with watsonx to transform fantasy football data into insight

IBM Big Data Hub

These applications are all hosted on the IBM Cloud to ensure uninterrupted availability. Managers can also use the AI models to analyze structured and unstructured data to compare players, estimate the potential upside and downside of starting a particular player and assess the impact of an injury.