Top Gen AI Use Cases: How to Turn Unstructured Data into Insights and Shape the Future of Your Enterprise

Across all industries, generative AI is driving innovation and transforming how we work. Use cases range from getting immediate insights from unstructured data such as images, documents and videos, to automating routine tasks so you can focus on higher-value work. Gen AI makes this all easy and accessible because anyone in an enterprise can simply interact with data by using natural language.

While gen AI holds a lot of promise, it also comes with a long list of cautionary what-ifs when used in production: What if our sensitive data is exposed when using an LLM? What if our app doesn’t have access to the right data and generates inaccurate results for stakeholders? What if we don’t have the resources needed to build and maintain these tools and platforms?

More accurate and reliable AI requires a comprehensive data strategy that is rooted in a strong data foundation. Organizations have been turning to Snowflake for years to unlock the power of data. Now, they’re choosing Snowflake to accommodate a vast array of AI use cases and turn hype into ROI. 

“Conversational chatbots have captured the imagination of everyone, but the reality is that there is so much untapped potential taking unstructured data and transforming that into insights with AI in the middle,” says Chase Ginther, Principal Architect for AI/ML and Global Field CTO at Snowflake. “We see customers driving a lot of business value with these types of use cases.”

Snowflake’s Gen AI Day, held in collaboration with AWS, showcased the many ways in which enterprises are turning to Snowflake to leverage gen AI beyond chatbots to address mission-critical problems across industries. Experts from Snowflake and partners including Accenture, Braze, Kumo, LandingAI, Prodapt, Sigma and Twelve Labs participated in discussions and demos that illuminated how to:

• Develop high-quality, conversational apps faster for self-service analytics

• Optimize NLP pipeline performance with cost-effective LLM batch inference

• Serve open-source LLMs and custom embedding models for inference with managed GPUs

• Get started with gen AI through industry-specific demos that showcased solutions in action

To highlight just a few, here are five key use cases for leveraging gen AI to address mission-critical problems across industries:

• While there are many gen AI use cases across financial services, the most prominent examples at Snowflake showcase the technology’s ability to process and generate text and to democratize access to insights and analytics through natural language. Snowflake partner Accenture, for example, demonstrated how insurance claims professionals can leverage AI to process unstructured data — including government IDs and reports — to make document gathering, data validation, claims validation and claims letter generation more streamlined and efficient. 
• Personalized recommendations are one of the most intuitive uses for gen AI in advertising, media and entertainment. By providing tailored recommendations, streamers and media publishers can keep audiences engaged, leading to better retention rates and financial benefits. Snowflake partner Twelve Labs is taking personalization to the next level by using multimodal AI to understand video. By analyzing all of a video’s modalities, including visual, audio, text and sound effects, they can provide contextual insights and customized recommendations. 

• Personalization is also a game changer in healthcare and life sciences, leading to improved patient outcomes and cost savings for healthcare systems. Healthcare professionals can use AI to create customized treatment plans, automate documentation and perform predictive health analytics. For example, Snowflake partner Kumo uses Snowflake’s AI capabilities to predict whether patients might need to be readmitted to the hospital. Kumo’s native app provides this intelligence by combining graph learning over structured data and gen AI models trained on unstructured data, all within the Snowflake environment. 
• In the public sector, gen AI has enhanced efficiency, service delivery and decision-making from citizen services to education and defense. Snowflake Cortex AI, for example, is helping governmental agencies simplify tracking legislative bills by creating AI-generated bill summaries and chatbots that allow individuals to search within and ask questions about bill documents. Agencies can quickly uncover trends, identify risks and optimize resource allocation based on AI-generated analysis. Traditionally, this would have entailed hours of manual work and the creation and maintenance of extensive, cumbersome spreadsheets. 
• Marketing and sales are particularly well positioned to take advantage of gen AI assistants that can accelerate access to insights. Sales teams are usually boxed into dashboards to get insights. These dashboards often grow unusable or lack dynamic filters to answer sales questions. With Snowflake Cortex AI, sales teams can build an AI assistant and ask questions about customers, territories or performance metrics — no dashboards needed. This solution can save time, enhance data-driven decisions and empower sales teams to focus on closing deals with near real-time, trusted data. 

Gen AI Day featured many more insights and demos for a wide array of industries and departments, including financial services; retail and consumer goods; advertising, media and entertainment; manufacturing; healthcare and life sciences; the public sector; telecommunications; marketing and sales; and IT, human resources and engineering. 

But don’t worry if you missed it — now you can watch the event on demand.

To learn about the top use cases for leveraging AI to drive success, download the Ultimate Guide to Data + AI for Industries.