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We had a busy week catching up with customers and partners at Microsoft Ignite in Chicago and online. We shared lots of exciting innovations to help customers build applications, keep their data architecture open and flexible and harness the power of AI in so many ways. Here’s a quick recap.

For years, companies have operated under the prevailing notion that AI is reserved only for the corporate giants — the ones with the resources to make it work for them. But as technology speeds forward, organizations of all sizes are realizing that generative AI isn’t just aspirational; it’s accessible and applicable now.

A revolution is underway as martech and adtech continue to converge around first-party data — and the revolution is happening on Snowflake. This seismic shift isn't a mere trend; it’s a game-changing transformation that will continue to shape the way that marketers and advertisers connect with consumers amid increasing privacy regulations, new identity frameworks and rising customer expectations.

Sports organizations have made major strides in recent years. Teams across the industry are transforming into data-driven organizations on the fan engagement, monetization and sports operations sides of the business. This trend is perfectly timed with the AI hype cycle. AI is proving that it’s here to stay. While 2023 brought panic and wonder, and 2024 saw widespread experimentation, 2025 will be the year sports teams get serious about AI's applications.

Snowflake leaders offer insight on AI, open source and cybersecurity development — and the fundamental leadership skills required — in the years ahead. As we come to the end of a calendar year, it’s natural to contemplate what the new year will hold for us. It’s an understatement to say that the future is very hard to predict, but it’s possible to both prepare for the likeliest outcomes and stay ready to adapt to the unexpected.

AI is proving that it’s here to stay. While 2023 brought panic and wonder, and 2024 saw widespread experimentation, 2025 will be the year that financial services enterprises get serious about AI's applications. But it’s complicated: AI proofs of concept are graduating from the sandbox to production, just as some of AI’s biggest cheerleaders are turning a bit dour.

The rise of generative AI models are spurring organizations to incorporate AI and large language models (LLMs) into their business strategy. After all, these models open up new opportunities to extract greater value from a company’s data and IP and make it accessible to a wider audience across the organization. One key to successfully leveraging gen AI models is the ability to share data.

As travelers increasingly expect personalized experiences, brands in the travel and hospitality industry must find innovative ways to leverage data in their marketing and product experiences. That said, managing vast, complex data sets across multiple brands, loyalty programs and guest touchpoints presents unique challenges for companies in this industry. Enter the Composable CDP on the Snowflake AI Data Cloud for Travel and Hospitality.

On a day-to-day basis, Snowflake teams identify opportunities and help customers implement recommended best practices that ease the migration process from on-premises to the cloud. They also monitor potential challenges and advise on proven patterns to help ensure a successful data migration. This article highlights nine key areas to watch out for and plan around in order to accelerate a smooth transition to the cloud.

Security has been an integral part of Snowflake’s platform since the company was founded. Through the security capabilities of Snowflake Horizon Catalog, we empower security admins and CISO’s to better protect their environments. As part of our continued efforts to help customers secure their accounts, and in line with our pledge to align with CISA’s Secure By Design principles, we are announcing the general availability of Snowflake Leaked Password Protection (LPP).