AI isn’t the future of work. It’s the present.
Everywhere I go, business leaders, engineers, and policymakers are talking about the potential of AI technology. But talk alone doesn’t move the needle. Leaders across industries are all asking the same questions: In a world where it seems like AI could solve anything and everything, how do we prioritize? How do we integrate this technology into our operations to drive real, measurable impact?
At Snowflake, we sit at the center of this AI revolution. We’re helping enterprises identify the right use cases, scale with confidence, and unlock tangible ROI from their data. With our recent release of our agentic AI platform, Snowflake Intelligence, we’ve taken a major step forward in making AI practical, governed, and value-generating.
Imagine having your favorite AI tool (ChatGPT, Claude, Llama….), but it’s all running on your enterprise data, with your company policies, privacy, and governance built in. You can talk to your data and get real-time insights, on knowledge content, sales metrics, service insights and more to drive impact for your business.
That’s what we’ve made a reality with Snowflake Intelligence. I know because I use it every day. For us, leadership means more than building powerful technology, it means being our own first customer, and challenging our teams to use AI across Snowflake to learn, adapt, and lead by example.
Leading by example in the age of AI
I’m a firm believer that to truly understand a technology, and help our customers embrace it, we must use it ourselves. And this goes all the way up to the C-suite. As leaders, we need to stay curious about this technology and understand what it can do to empower our teams to harness it effectively.
Putting this belief in practice, I have pushed our teams to reimagine how we sell, market, hire, code, and serve our customers in this AI era. This isn’t about replacing people. It’s about amplifying human potential and freeing up capacity for high value, strategic work. And even more, it’s also about discovering the new and magical ways you can apply this technology - things you only discover with the freedom and support to test and experiment.
Already, we’re seeing clear results across our business:
- Sales teams use Snowflake Intelligence to instantly surface account insights and turn prep into a matter of minutes not hours
- Marketers can generate, analyze, and optimize campaigns automatically
- Engineers are coding and debugging faster than ever
- Customer support is resolving issues faster and reducing escalations through intelligent triage
- People operations applies AI to streamline recruiting, analyze employee feedback, and improve the employee experience
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Why this mindset matters
Technology is only one part of the story. Enterprise AI requires a massive cultural change. And it’s no secret that change is hard work. The key lies in unleashing curiosity. When you empower super-users to explore, they uncover AI applications that make everyone’s work easier. They become evangelists for progress, accelerating adoption across the organization.
But cultural transformation also requires accountability at the top. Every leader must experiment with AI firsthand. After all, how can you empower teams to embrace AI’s potential without understanding the technology yourself?
This model of activating power-users, focusing on practical use cases, and driving accountability from leadership has fueled the results we’ve achieved so far. However, this approach is not without its challenges. Leading through this kind of technological change requires humility and experimentation. We have to be transparent about what works– and what doesn’t. That honesty builds trust, both within our teams and across the ecosystem we serve.
What’s next
We’re still early in this journey. As agentic AI systems evolve, the possibilities will expand exponentially. And in a world of pervasive change, the winners will be the ones that start now.
At Snowflake, we’re continuing to test, learn, and apply emerging tools, from our own Cortex AI to emerging coding agents and sales tools to stay ahead of the curve. We’re also placing a lot of thought and emphasis into what the “future-fit” version of our work looks like. We’re working hard to support AI literacy across teams and empower internal AI champions to keep pushing boundaries.
Over the next few weeks, you’ll hear directly from leaders across Snowflake as they share their playbooks on how they’re transforming their functions with AI. Each story highlights not just how AI can enhance a business, but also how it can transform how we lead.
We’re only at the beginning. But this much is clear: the organizations that experiment and learn fast now will define the next era of enterprise innovation.
I'm ready to crush it for Snowflake when you need me!
Well said. The real shift isn’t adopting AI tools—it’s redesigning workflows, incentives, and decision-making around them. Turning AI from “capability” into “performance” is where most organizations struggle. Leading by example matters.
AI becoming “the present” really shows up when leadership stops treating it like a side project and starts redesigning how work actually flows. What stands out here is the emphasis on using AI inside the business, not just selling it to customers. That’s how you move from pilots to real impact, when data, governance, and daily decision making all come together in one operating rhythm.
What resonated most is the focus on practical, role-specific impact - sales prep in minutes, smarter campaign optimization, faster customer resolution. That’s where AI earns adoption. From a marketing standpoint, this reinforces how critical clean data, governed access, and the right use-case framing are before expecting AI to “work.” When those foundations are in place, creativity and strategy actually expand rather than shrink.