Updating Enterprise Technology to Scale to "AI Everywhere"
Companies can't scale their AI solutions without also reshaping their technology function to enable this massive shift. Taking an "AI everywhere" approach to re-architecting the tech stack is a critical, foundational step. Equally important will be upgrading current ways of working to make the best use of new AI solutions, which will require bringing the discipline of software development to the adoption of AI models. is ready to take this journey with you.
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How is generative AI changing enterprise technology?
CIOs are navigating substantial shifts in how work is accomplished due to the rapid adoption of generative AI. This includes re-architecting the technology stack to support an 'AI everywhere' approach and upgrading existing workflows to effectively integrate AI solutions across various functions.
What are the key processes for scaling AI solutions?
Companies should prioritize re-architecting their tech stack with an 'AI everywhere' mindset and upgrading their operational methods. This involves integrating machine learning and generative AI, upskilling engineering teams, and redefining tech spending to support AI investments.
What challenges do organizations face with generative AI?
Organizations face challenges such as the need for seamless integration of AI models into existing workflows, managing unstructured data, and ensuring collaboration and quality control as complexity increases. Additionally, they must adopt MLOps processes to treat AI models with the same rigor as software code.
Updating Enterprise Technology to Scale to "AI Everywhere"
published by USSFP
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