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.
How is generative AI changing enterprise technology?
CIOs are managing substantial shifts in work processes as generative AI is adopted. This includes re-architecting the technology stack with an 'AI everywhere' approach and upgrading existing workflows to effectively integrate AI solutions. Companies are moving beyond initial experimentation and are now focused on scaling generative AI across their organizations.
What are the key processes for integrating AI in enterprises?
Companies should prioritize re-architecting their tech stack to support an 'AI everywhere' approach and upgrading their ways of working to incorporate AI solution development. This includes enhancing collaboration, quality control, and scalability while treating AI models with the same discipline as software code through MLOps processes.
How should companies approach AI solution development?
Organizations should establish a federated AI development model that defines roles for teams producing and consuming AI services. They should also create AI-first software development processes that allow for rapid iteration and incorporate generative AI tools into software development and service management, ensuring clear guidelines for deployment and monitoring.
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