#a18-process

#a18-process

"Snowflake gives customers one place to bring their data together, connect the systems they rely on, and turn AI into something that actually helps teams get work done," says Baris Gultekin, VP of AI at Snowflake.

We're investing a lot in AI - we're doing a lot, but we're stopping at individual productivity. We're not taking the next step. You can't just screw AI on everything - it only makes you faster. It means you need to think about, 'how are our teams collaborating? How are people collaborating?' You probably need to change the way you work.

AI reveals a hidden, outdated assumption: that humans will continue to serve as the "digital glue," manually connecting disparate systems, teams, and decisions. For decades, enterprise software perpetuated a model of sequential handoffs, in which people managed data entry, reconciled conflicts, chased approvals via email, and updated spreadsheets. This structure was manageable when uncertainty was low and delayed decisions were affordable.

Agentic AI workflows sit at the intersection of automation and decision-making. Unlike a standard workflow, where data flows through pre-defined steps, an agentic workflow gives a language model discretion. The model can decide when to act, when to pause, and when to invoke tools like web search, databases, or internal APIs. That flexibility is powerful - but also costly, fragile, and easy to misuse.

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