Snowflake World Tour 2026: Key takeaways 

Snowflake World Tour 2026 London brought together around 5,000 people at Excel London, with more than 70 breakout sessions and 30 plus Snowflake customers sharing how they are using data and AI. 

In the special episode of Clektive Thinking, Chris Harling, and Elliott Fairhall share their key takeaways from the event, from the keynote and customer stories to the growing role of agentic AI across the business.

Alongside their reflections, Thomas Maud Director of Solutions at Clekt, has shared some additional observations from the event. Together, they highlight four themes that businesses should be paying attention to.

1. AI starts with a data strategy 

The message was clear from the keynote and throughout the day: businesses cannot build an effective AI strategy without getting their data foundations right. 

“There isn’t an AI strategy without a data strategy.” 

For Thomas, this was one of the defining themes of the event. Moving from AI experimentation to genuine business value requires trusted, well managed data, with the right governance and context around it. 

The giffgaff customer keynote brought this to life. Its CEO, Kate Dohaney, talked about putting the customer at the centre of the business, using customer data to become more data driven and focusing AI on automating manual processes while keeping people in the loop. 

The message was simple: AI should not be an experiment happening separately from the rest of the business. It needs to be connected to the data, processes and outcomes that matter. 

2. The enterprise context gap is becoming critical 

One of the sessions Thomas found particularly interesting was The Enterprise Context Gap, which explored why AI can struggle to work effectively with enterprise data. 

The problem is that context is often scattered across databases, files, code, cloud platforms, BI tools and people. Even when metadata exists, it does not necessarily capture the business definitions, rules and ownership that AI needs to understand what the data actually means. 

This is where Snowflake’s developments around Horizon Context, Horizon Catalog and the semantic layer become particularly important. 

The challenge is not simply having more data. It is making sure AI has the right context to use that data accurately. 

That matters because the more businesses rely on AI to generate analysis, write code or support operational decisions, the more important it becomes to know that the output is based on the right information and definitions. 

3. AI is moving into the core of the business 

Elliott’s breakout sessions showed how quickly the opportunity is moving beyond traditional analytics and technical teams. 

In The Agentic Enterprise, he saw examples of how organisations are looking at agents to support processes across retail and ecommerce, including areas such as fulfilment and procurement. 

Elliott states “It’s not just a data platform. It’s not just for the tech team. It can be for the operations and the operational processes that are needed.”

Clekt’s CEO, Andy Tudor discussed this on recent Clektive Thinking episode with Paul Winsor, Head of Retail EMEA at Snowflake, which can be watched here.

The same theme came through in the keynote: Snowflake is positioning its platform as a way to empower and accelerate the wider business, not simply as somewhere to store and analyse data. 

Chris believes that shift is significant. 

“AI is no longer the competitive advantage. It’s actually the competitive disadvantage if you’re not using it.”  

The question for business leaders is therefore changing. It is no longer simply what could AI do? It is where can AI make a measurable difference to how we operate? 

4. Speed needs to be balanced with trust 

The Raw Data to AI Readiness breakout looked at the foundations needed to make data AI ready, including the role of data pipelines, semantic layers and the context needed to support AI development. 

Across the event, there was a clear focus on using tools such as CoCo to accelerate development and enable teams to work at greater pace. But speed cannot come at the expense of trust. 

One of the demonstrations raised an important question: how do you know the AI generated output is right? That brings the conversation back to trusted data, governance, semantic context and human oversight. 

As Elliott put it: “You can’t do it without real deep clarity and understanding of this is what we mean.” 

The opportunity is huge. The foundations still matter. 

The biggest takeaway from Snowflake World Tour was not one particular product or announcement. It was how quickly data and AI are moving from experimentation into the core of business operations. 

The organisations that benefit most will be those that combine the technology with strong data foundations, clear business priorities and the right context to make AI useful and trustworthy. 

As Thomas, Elliott and Chris’s observations from the event show, the opportunity is not simply to do existing things faster. It is to rethink what is possible when data, AI and business processes are brought together. 

Want to explore what your data and AI opportunities could look like?