Systems | Development | Analytics | API | Testing

Unstructured text is everywhere in business: customer reviews, support tickets, call transcripts, documents. Large language models (LLMs) are transforming how we extract value from this data by running tasks from categorization to summarization and more. While AI has proved that real-time conversations in natural language are possible with LLMs, extracting insights from millions of unstructured data records using these LLMs can be a game changer. This is where batch LLM inference becomes essential.

Some 70% of organizations are actively exploring or implementing large language model (LLM) use cases, but fewer than a third of generative AI experiments have made it into production. A common hurdle? The inability to access and leverage the data crucial for running AI applications effectively. Snowflake’s Accelerate 2025 virtual events dive into the challenges and myriad opportunities offered by AI.

Throughout my career, I’ve had the privilege of working across the full spectrum of enablement: internal enablement, partner enablement and customer enablement. Each of these domains brings unique challenges, audiences and approaches, but a common thread unites them all: the goal of fostering growth. At its core, training and enablement are not just about imparting knowledge or improving skills. While these are vital components, the true purpose transcends the transactional.

Sales reps dedicate just two hours each day to active selling, according to HubSpot research. At Snowflake, our sales team found they were wasting 10 to 15 minutes searching for the right content every time they needed to answer a single question, like “Can you explain how Snowflake handles data integration from various sources?” Valuable content was scattered across different platforms, forcing employees to hop between various tools to assemble the right information.

If you ask any advertiser about the most disruptive factor in recent years, they’ll probably hesitate between two contenders: privacy and AI. While AI is poised to have a transformative impact far beyond advertising in the future, one thing is certain: No organization today can address use cases involving consumer data without prioritizing privacy. Before we dive into the world of data clean rooms, let’s take a quick trip back in time to set the stage.