The AI Reality Check
AI Brokers rebuilt trading around conversation
Ohad Ben Artzi is co-founder and CEO of AI Brokers, which builds chat-based trading platforms for brokers, exchanges, banks, and their retail clients. His company is trying to replace the old dashboard model with a system that lets users talk to the platform, and that shift is already changing how customers find and evaluate it.
The most useful lesson is that AI worked best when it was used behind the scenes for testing, edge cases, and compliance checks, not as a substitute for the first sales conversation. In a trust-heavy industry, the human relationship still has to start the deal.
What’s the quick origin story of your business, and what makes what you do genuinely different from the other options your customers are looking at?
AI Brokers came out of a frustration I experienced watching the trading industry operate with infrastructure that hadn’t fundamentally changed in decades – clunky interfaces, fragmented data, and retail clients who were essentially left to figure it out alone. We build AI-powered, chat-based trading platforms for brokers, exchanges, banks, and their retail clients. The idea is simple: instead of a dashboard full of charts and menus that require expertise to navigate, you talk to the platform. It understands what you want to do, surfaces the right information, and executes. What makes us different is that we’re not a feature bolt-on. We’re rebuilding the client-facing layer of trading from scratch around conversation – which is how people actually think and communicate, not how legacy fintech was designed.
Where does most of your new business come from today, and where do you wish it came from?
Right now most of our pipeline comes from direct relationships – introductions through the financial industry, conferences, regulatory networks. The sales cycle in this space is long and trust-driven, so warm introductions carry disproportionate weight. Where I wish more came from is product-led awareness: operators at brokers and exchanges who encounter what we’ve built, understand it immediately, and come in already educated. We’re working on making the platform speak for itself more loudly.
What’s one thing you’ve actually handed over to AI in the last year, and one thing you tried it on and went back to doing the human way?
We use AI heavily in our own development and QA cycles – generating test scenarios, edge cases, compliance checks across different regulatory environments. That’s off the team’s plate and it’s faster and more thorough than what we did before. What we tried on AI and walked back was automated client onboarding conversations – letting the AI handle the entire initial discovery call with a prospect. The information gathered was accurate but the relationship didn’t form. In enterprise fintech sales, the first conversation is where trust is built. We now use AI to prepare for that conversation, not replace it.
Have you noticed a change in how customers find you or what they already know before they reach out? Is anyone arriving through AI assistants like ChatGPT yet?
The sophistication of inbound has shifted noticeably. Decision-makers at banks and exchanges are arriving having already done a first pass of the competitive landscape – and increasingly that first pass was done through an AI assistant. We’ve had prospects say they started with a ChatGPT or Perplexity query about AI trading interfaces and traced their way to us from there. That’s a channel we’re taking seriously. It means the way we describe what we do – in articles, documentation, interviews – has to be precise enough to be cited correctly by models that have never spoken to us.
If you were advising someone in your industry on all of this for the next 12 months, what would you tell them to actually do, and what would you tell them to ignore?
Do: If you’re a broker or exchange, run a serious evaluation of your client-facing interface against what conversational AI makes possible today. Your retail clients are already using AI tools in their personal lives – the gap between that experience and your platform is becoming a churn risk. Start with a defined use case: onboarding, order flow, portfolio queries. Get one thing working well before expanding.
Ignore: The idea that compliance and regulation make AI adoption impossible in trading. The regulatory environment is moving, and the institutions that wait for perfect clarity will be lapped by those building responsibly now. Also ignore any vendor promising you a generic chatbot layer on top of your existing stack – the value is in a platform built for trading from the ground up, not a chat widget.
Thank you to Ohad Ben Artzi and the team at AI Brokers for sharing what actually worked with Leaders Perception readers.
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