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With Generative AI Advances, The Time to Tackle Responsible AI Is Now

Unite.AI

Today, seven in 10 companies are experimenting with generative AI, meaning that the number of AI models in production will skyrocket over the coming years. As a result, industry discussions around responsible AI have taken on greater urgency.

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HR and Talent in the Era of AI

IBM Journey to AI blog

Critical considerations for responsible AI adoption While the possibilities are endless, the explosion of use cases that employ generative AI in HR also poses questions around misuse and the potential for bias. As such, HR leaders cannot simply rely on data and AI to make decisions. HR leaders set the tone.

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3 key reasons why your organization needs Responsible AI

IBM Journey to AI blog

Gartner predicts that the market for artificial intelligence (AI) software will reach almost $134.8 Achieving Responsible AI As building and scaling AI models for your organization becomes more business critical, achieving Responsible AI (RAI) should be considered a highly relevant topic. billion by 2025.

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How to become an AI+ enterprise

IBM Journey to AI blog

Generative AI (gen AI) introduces transformative innovation to all aspects of a business; from the front to the back office, through ongoing technology modernization, and into new product and service development. We refer to this transformation as becoming an AI+ enterprise. This requires a holistic enterprise transformation.

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Establishing an AI/ML center of excellence

AWS Machine Learning Blog

Additionally, pay special attention to the changing nature of the risk and cost that is associated with the development as well as the scaling of AI. To provide ethical integrity , an AI/ML CoE helps integrate robust guidelines and safeguards across the AI/ML lifecycle in collaboration with stakeholders.

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A Recipe For AI Strategy

ODSC - Open Data Science

This is a recipe for developing a strategy for incorporating AI into products. An AI strategy is a framework that will help the organization understand what data-driven projects and data sources are the most valuable to the organization, and how to prioritize them to build toward their product vision over time.

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How to improve your finance operation’s efficiency with generative AI

IBM Journey to AI blog

If poorly executed, these reports can limit our ability to explain the underlying drivers of performance. AI analyzes financial statements, notes, disclosures and other and applicable data, then translates and interprets the data to provide context-rich answers to your questions.