AI systems are moving into the operational phase and starting to deliver business value through enhanced processes and decision-making. Central to keeping this momentum going is companies leveraging the technology for targeted workflows using models trained for specific use cases. Deploying, running and monitoring multiple models may sound like a complicated, arduous and costly exercise, but the secret to success lies in the fundamentals.
Companies, whether they’re banks, hospitals, telecoms or retailers, want to use AI to solve specific business challenges. AI systems need to reflect that specificity, and the best place to start is with the models that power them.
Please find attached full byline by Robbie Jerrom, Senior Principal Technologist AI at Red Hat, as he further unpacks why enterprises should move away from a “one-big-model” AI strategy and instead adopt a multi-model, use-case-driven approach, and how to do that practically in production.