Good read how clean data unlocks the power of AI in development! It leads to improved efficiency, accurate decision-making, and innovative solutions. What are your thoughts on the data-AI connection? #data #AI #development
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If your data isn't ready for #generativeAI, your business isn't ready for generative AI. 🔄 Data leaders have a huge opportunity to harness this new technology to improve their function. 👉 Link to McKinsey article https://lnkd.in/gqYj5Yz7
The data dividend: Fueling generative AI
mckinsey.com
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Passionate Sales Technologist skilled in connecting business and technology leaders to enhance communication, solve problems, and drive risk reduction and revenue growth.
With the rise of GenAI applications, prioritizing data integrity has never been more crucial. For AI initiatives that are high-performing, reliable, and produce quality outputs, your data must be: ✅ Complete ✅ Accurate ✅ Trusted ✅ Consistent ✅ Contextualized Data Quality paves the way for fostering trust and adoption within the Enterprise and accelerates AI development and innovation. Great article on the topic by Stephen Cantanzano: https://lnkd.in/djZt5Ywn #AI #GenerativeAI #DataEngineering #DataQuality #GraphDatabase #GraphDataFabric #AugmentedData #DataScience #DataAnalytics
Data quality fuels analytics, AI | TechTarget
techtarget.com
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As #GenAI reshapes industries, having a solid data strategy is essential for success. Iron Mountain’s blog highlights how crafting and implementing a comprehensive #datastrategy will better help organizations leverage the transformative powers of #AI: https://ow.ly/GzT150TNxrz Tyler Morris, Alex Sisserson
Is your data strategy ready for generative AI?
ironmountain.com
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Generative AI is poised to revolutionize how companies innovate and harness their full potential. A strong AI foundation starts with — and depends on — data quality. Data readiness for AI will be the differentiator between stagnation and competitiveness. Read our insights here #artificialintelligence #GenAI #datagovernance
Foundational data considerations for generative AI | Our Insights | Plante Moran
plantemoran.com
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Generative AI is poised to revolutionize how companies innovate and harness their full potential. A strong AI foundation starts with — and depends on — data quality. Data readiness for AI will be the differentiator between stagnation and competitiveness. Read our insights here #artificialintelligence #GenAI #datagovernance
Foundational data considerations for generative AI | Our Insights | Plante Moran
plantemoran.com
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Generative AI is poised to revolutionize how companies innovate and harness their full potential. A strong AI foundation starts with — and depends on — data quality. Data readiness for AI will be the differentiator between stagnation and competitiveness. Read our insights here #artificialintelligence #GenAI #datagovernance
Foundational data considerations for generative AI | Our Insights | Plante Moran
plantemoran.com
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Generative AI is poised to revolutionize how companies innovate and harness their full potential. A strong AI foundation starts with — and depends on — data quality. Data readiness for AI will be the differentiator between stagnation and competitiveness. Read our insights here #artificialintelligence #GenAI #datagovernance
Foundational data considerations for generative AI | Our Insights | Plante Moran
plantemoran.com
-
Generative AI is poised to revolutionize how companies innovate and harness their full potential. A strong AI foundation starts with — and depends on — data quality. Data readiness for AI will be the differentiator between stagnation and competitiveness. Read our insights here #artificialintelligence #GenAI #datagovernance
Foundational data considerations for generative AI | Our Insights | Plante Moran
plantemoran.com
GenAI Product Lead @ Dell Technologies | Shaping the future of human-AI collaboration at the intersection of conversational AI interfaces and prompt engineering research
9moThe connection is strong. You don’t have effective AI without good data. One non-obvious takeaway for me from the article is the importance of focusing on data engineering talent over data scientists, as the evolving landscape of generative AI requires more expertise in integrating data sets, managing large data volumes, and applying machine learning models. This shift underscores a changing priority in skill sets necessary for harnessing the potential of generative AI in business operations.