So, you’ve made the call. You’re ready to bring AI into your business. Maybe it’s an internal tool. Maybe it’s something customer-facing. Either way, you need help. You need an AI development company that knows what they’re doing—and doesn’t waste your time (or money).
Problem is, not all companies claiming to build AI solutions really get it. Some are great at buzzwords. Others rely too heavily on off-the-shelf models and give you a glorified prototype instead of a real product.
So how do you separate the good from the bad? Ask better questions. The right ones. Ones that dig deeper than “How long have you been in business?”
Here’s a list of 10 questions to ask before signing anything.
1. What specific AI projects have you completed in the past?
You’re not looking for a company that can build AI—you’re looking for one that has. Ask for examples. Real ones. Not just “we’ve worked in retail” but “we built a product recommendation engine that helped increase conversions by X%.”
You want details. What was the goal? What was the outcome? Were they involved from start to finish or did they only handle one part?
And yeah, check references if you can.
2. Do you build everything from scratch or use pre-built models?
There’s no right or wrong answer here. Sometimes, using a pre-built model makes sense. Other times, building from scratch is the better route.
The key is understanding what you’ll get. If they only know how to plug in someone else’s tools, they might not be the right AI app development company for a long-term partnership.
Ask how they approach custom development. Do they consider performance, scalability, and cost? Or do they jump to whatever’s trending?
3. How do you handle data?
This is where things usually fall apart. AI systems rely on data—lots of it. Clean, structured, relevant data.
So, how do they manage yours?
Will they help clean it? Will they help label it? Do they understand your industry enough to even know what data matters?
A solid AI partner should walk you through this like a pro. If they seem vague or dismissive, keep looking.
4. How do you test the accuracy and performance of your models?
This isn’t just about asking, “Does it work?”
You need to know how well it works. How they measure performance. What metrics they use. And more importantly—what happens when the model isn’t hitting the mark.
Do they retrain it? Adjust the inputs? Start over?
Good AI developers will talk openly about testing and tuning. It’s a huge part of the job, not just an afterthought.
5. What’s your process for understanding my business goals?
This might sound soft, but it’s actually a deal-breaker.
If the team doesn’t take time to understand your goals, your users, and how the tech fits into your workflow, the project will miss the mark.
Ask them how they get up to speed on a new business. What’s their discovery process like? How involved will you be?
If it sounds like they jump into development too soon, that’s a red flag.
6. Who’s actually working on my project?
Lots of companies show you their “dream team” during the pitch. Senior engineers, architects, all the shiny resumes.
Then after the contract is signed, your work gets handed off to junior developers or outsourced freelancers.
You need to know who’s doing the work. Not just names, but roles, experience, availability. If you’re working with an AI app development company, this is non-negotiable. You should have access to the people doing the actual coding, not just the sales reps.
7. How do you handle security and privacy?
AI isn’t just about getting results—it’s about handling data responsibly.
Ask what steps they take to secure your data. How they manage access. What protocols are in place for sensitive information. If you’re in a regulated industry (finance, healthcare, etc.), this becomes even more important.
Also, ask if they offer ongoing support to help you stay compliant as laws change.
8. What does your post-launch support look like?
Building the product is one thing. Keeping it running is another.
Do they provide maintenance? Model updates? Bug fixes? What’s the process for scaling as your data or user base grows?
A good AI product isn’t “done” when it launches. It needs updates and monitoring. If they disappear once you go live, you’re stuck with tech that might break six months later.
And if you’re using an AI Interview Platform, ongoing tweaks to improve candidate evaluation or bias mitigation might be needed. So ask about it early.
9. How flexible is your engagement model?
Not every business needs a full-time team. Maybe you just need a prototype. Or maybe you want someone on retainer. Or maybe you want to hire AI developers who can integrate with your in-house team.
Whatever your situation is, ask how flexible their setup is. Can they work in sprints? Do they offer dedicated resources? Are they open to hybrid models?
The right company will work with you, not force you into one approach.
10. What happens if the AI doesn’t deliver the results we expected?
This one separates the partners from the vendors.
AI isn’t magic. Sometimes it takes a few tries. Sometimes the data isn’t good enough. Sometimes the initial idea needs to be adjusted.
Ask how they handle those moments. Do they walk away? Charge you more? Or do they come up with a plan to fix it?
You want a company that’s honest about failure and ready to iterate—not one that disappears when things get tricky.
Final Thought: Don’t Settle for Shiny Proposals
Lots of companies can pitch well. They’ll throw in slick slides and flashy demos.
But at the end of the day, you’re not buying a presentation. You’re buying a product. A solution. A team.
So ask tough questions. Listen closely to the answers. Pay attention to how they talk, not just what they say.
Because once the contract is signed, it’s a whole lot harder to change your mind.