Generative AI is poised to transform many facets of data and analytics, but it won’t provide the value organizations expect if their data management practices are lacking. They must solve current advanced analytics challenges first before incorporating the latest AI tools.
Large language models (LLMs), such as GPT-4, are good at understanding ideas and coming up with readable text. They’re not well suited to tasks that legacy systems and advanced analytics tools are already good at, such as managing transactional or structured data or doing high-speed data processing.
As a result, some organizations are considering a hybrid approach. They might use generative AI to automate some tasks and continue to use traditional analytics and data tools for others, said Traci Gusher, data and analytics leader at EY Americas. Consider a common use case for LLMs: customer service chatbots.
