Modern finance teams need more than buzzwords.
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As the bar for productivity rises, so does the need for tools that don’t just promise intelligence, but actually deliver it. AI is everywhere in treasury tech marketing, but few platforms show what it really means for your day-to-day: less manual work, clearer visibility, smarter forecasting, and faster decisions.

If you’re exploring new treasury platforms, especially ones that claim to use AI, it’s easy to get overwhelmed by buzzwords. But asking the right questions can help you quickly spot which solutions are actually built to make your work easier, safer, and more efficient.

We’ve put together a downloadable guide with 25+ practical questions finance teams can use during demos, RFPs, or internal evaluations. They’ll help you get past the surface-level pitch and uncover which platforms truly support day-to-day needs, offer strong security, and include the core features that matter most.

The full AI Cash Management Buyer’s Guide also includes expert tips, simple explanations, and a clear way to compare responses, so your team can move faster and choose with confidence. Ready to dive in? Here’s a preview of the top 10 Questions or download the guide now.

1. Can you trace to the source data of where AI made the suggestion/prediction?

Why it matters: Pushes beyond black-box AI. Smart buyers want explainability and auditability, especially for financial decisions.

2. Can AI agents run operational workflows autonomously (e.g., tagging transactions, variance analysis, generating graphs)?

‍Why it matters: Moves the conversation beyond dashboards to agentic automation. Shows which platforms offer true productivity gains.

3. Are AI-generated forecasts editable with user assumptions?

Why it matters: Balances automation with user control, a must for finance teams who want AI supporting, not replacing, their judgment.

4. Are real-time APIs or webhooks available?

Why it matters: Exposes technical depth. Real-time sync drives true agility, critical in cash and liquidity management.

5. What is the manual setup or time-to-accuracy for AI features like transaction tagging or forecasting?

Why it matters: Gets real about AI implementation lag. Buyers want to know when they’ll see ROI, not just promises.

6. What historical data is needed to activate AI features?

Why it matters: Highlights AI readiness, and whether the buyer’s existing data will be usable without costly prep work.

7. What is your escalation process and resolution SLA?

Why it matters: Shows how serious the vendor is about support risk. Strong SLAs = stronger customer experience.

8. What percentage of clients actively use AI features?

Why it matters: Cuts through fluff. If AI is a real differentiator, it should be widely adopted, not just demo-only.

9. Can you connect to banks that don’t support major connectivity rails (API, SFTP, Host-to-Host)?

‍Why it matters: Tests the breadth of financial connectivity, especially for global, multi-bank or mid-market teams.

10. Are AI capabilities included or sold as add-ons?

Why it matters: Pricing transparency for buyers. AI shouldn’t feel like a hidden upcharge or patch-on feature.

Want the full list and a downloadable template to use for vendor selection? Download our full AI in cash management buyer’s guide with the form below and cut through all the noise. And, if you’re evaluating Nilus, click here to schedule a demo.