Here are a few questions that helped us figure out whether building an AI-driven chatbot was the right move, and when it wasn’t.
1. Do your users need personalized, actionable guidance?
In complex domains like personal finance, users don’t just need information, they need help making sense of the information and therefore, their options. AI-powered personalized guidance becomes essential in difficult situations that require specific context of the user, like managing variable income or choosing which debt to pay down. This financial assistant chatbot started to gain traction once it could interpret user inputs and offer next steps that actually made sense for their specific case.
If your users need contextual support—something more than static advice—AI chatbots can help them connect the dots faster.
2. Could users feel safer talking to a chatbot than a human?
In interviews, some users told us they actually preferred sharing details about their finances with a chatbot. They felt less judged and more comfortable opening up about debt, income struggles, or financial mistakes. That psychological safety can be a real advantage—if the chatbot experience handles it with care.
In certain contexts, AI chatbots can lower emotional barriers. If shame or fear is part of the user journey, a chatbot might help people open up.
3. Is there a real, repetitive user need?
If users are constantly asking the same thing: FAQs, onboarding steps, how-tos; a chatbot might make sense. In our case, we saw patterns like “How do I start saving?” or “What’s the best way to boost my credit?” Automating those answers and/or re-directing them to existing resources helped reduce friction fast.
Don’t build a chatbot to have a chatbot. Build one if it's solving something that keeps coming up—especially if you're aiming to scale support automation or AI-driven guidance.
4. Can your domain handle automation?
We’ve worked in personal finance and other sensitive domains like legal where stakes are high. At first we restricted the chatbot to safe, pre-approved content early on to avoid misinformation. That kept things clean but made the chatbot frustratingly limited in some situations. We’re now working on a middle ground—one where the chatbot can still respond dynamically, but within compliance boundaries we trust.
If the cost of getting something wrong is high, be honest about what your AI chatbot can and can’t do.
5. Do users actually need help at the moment?
An AI chatbot shines when users are stuck or overwhelmed and can’t wait. Many people manage their finances outside of traditional hours, often late at night, when questions about bills or income gaps can feel most urgent. A 24/7 financial assistant that’s available anytime could offer real-time support when users need it most, helping them take action in the moment instead of waiting or feeling stuck.
If people need just-in-time assistance, an AI chatbot can act as an always-on support layer. If they don’t, maybe a static resource is enough.
Final thoughts…
Building an AI chatbot can absolutely improve UX, reduce support load, and scale human-like interactions—but only if you're solving something real, and you're ready to keep showing up for it. Our financial assistant chatbot wasn’t magic out of the gate. But it’s starting to work—because we’re listening, adapting, and designing for real human needs, not just AI capability.
If you're considering building a chatbot, ask yourself:
Is it solving a pain point? Can it grow over time? Are we designing it to support how users want to engage?
