We recently published the first-ever report on agentic AI in credit unions. But the research also revealed insights into broader trends across the finance industry.

We’ve gathered them in one place to help you shape your strategy for 2026.

You’ll learn:

• Which type of AI has the highest adoption rate

• Which use case has the highest ROI

• How most institutions are approaching AI adoption, and so much more.

Get the insights you need now:

This Week: Zero to One in Enterprise AI With Ankur Patel

What does it actually take to ship an AI product that enterprises will buy, trust, and put into production?

Why do so many AI startups die before they even launch—and what separates the few that break through?

This week, our founder Ankur Patel joined the Zero to One podcast to share some of the most candid, practical advice we’ve heard on going from idea → product → adoption in enterprise AI.

We covered:

• Why speed is your only real moat in a world where foundation models improve weekly

• How picking a narrow wedge (not a platform) is the only path to early traction

• Why trust beats technology—traceability, validation, and ROI matter more than model size

• How being an outsider gives you an advantage incumbents can’t replicate

• Why failure is now career leverage, not a setback

Introducing Trust Center

In enterprise AI, trust isn’t a feature. It’s a requirement. That’s why we’re opening up how AgentFlow thinks, traces, and verifies every answer it generates.

Our new Trust Center breaks down the full chain of transparency behind Agentic AI: where information comes from, how it’s cited, and how every response can be audited down to its source file and JSON reference.

If your team needs AI you can verify, not just AI you can read, this is the place to start.