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.
How is generative AI changing enterprise technology?
CIOs are navigating substantial transformations in how work is conducted as generative AI becomes more prevalent. This includes re-architecting the technology stack with 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 to incorporate AI and upgrading their operational methods to facilitate AI solution development. This involves enhancing collaboration, quality control, and adopting MLOps processes to manage AI models throughout their lifecycle.
What challenges do companies face in adopting generative AI?
Organizations face challenges such as deciding whether to build or buy generative AI solutions, managing the integration of AI with existing systems, and ensuring data governance and risk management. Additionally, there are concerns regarding security and quality that need to be addressed as they scale AI initiatives.
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