• Niv Liran, Chief Product and Technology Officer at Unzer


• 20.04.2026 08:21 am

AI is quickly becoming part of everyday work. But while many organizations focus on deploying tools, the bigger challenge often lies elsewhere: helping people understand how to use them confidently. For Niv, Chief Product and Technology Officer at Unzer, AI transformation is less about technology and more about AI fluency across the organization. In this conversation, he explains why curiosity alone isn’t enough, why training dramatically increases productivity, and why the real AI divide isn’t between companies, but between roles.

Many companies celebrate early AI adoption. But you’ve said experimentation alone isn’t enough. Why?

Niv: Early curiosity is a great sign. When new tools appear, the first step is always people trying them out and exploring what they can do. But curiosity alone doesn’t create lasting change. What we observed is something many organizations are experiencing right now: people might try an AI tool once or twice, but it doesn’t automatically become part of how they approach their work.

What changed when you realized that?

Niv: Initially, like many companies, we focused on giving people access to basic AI tools such as ChatGPT. But we soon learnt that you can’t simply hand people a tool and expect the way they work to change automatically. Real transformation happens when teams start asking themselves: Where does this actually create value in our daily work?

That requires learning, experimentation, and support. It’s about helping people understand where AI fits into their processes, and where it doesn’t. That’s why the real challenge isn’t rolling out tools. It’s building skills and competence.

Not every role uses AI today. Why should AI literacy matter across the entire workforce?

Niv: Because AI is increasingly shaping the tools we use, even if we don’t always notice it. AI literacy doesn’t mean everyone needs to build models or write code. It means understanding the basics: what these systems can realistically do, where their limits are, and how to critically evaluate their outputs.

Even if AI isn’t central to someone’s role today, it’s already influencing areas like reporting, compliance checks, internal workflows, or communication with customers, as well as employer hiring preferences. Being AI-literate simply means you can participate in these changes confidently rather than feeling like it’s something happening somewhere else.

You recently attended the AWS:Reinvent conference in the U.S. What stood out most?

Niv: I think it’s safe to say that the real differentiator isn’t who uses AI anymore. Most companies do. It’s how they use it. Another interesting observation was that AI adoption is function-led rather than industry-led. It’s less about which sector a company operates in and more about the type of work people do. Roles that involve writing, analysing information, coding, or creating content are moving much faster with AI than operational or frontline roles. We’re also seeing that AI is extremely strong at shorter, well-defined tasks, while longer, high-context work is still challenging. And another key insight from the conference was the impact of training: Employees who received structured AI training were roughly twice as productive with AI tools as those who didn’t.

AI can also create uncertainty or even fear in organizations. How should companies address that?

Niv: The worst thing organizations can do is avoid the conversation. If companies don’t talk openly about AI, people will fill the gaps themselves, usually with unexpected and more negative assumptions. That’s why transparency and learning opportunities are so important. People need spaces where they can ask honest questions: What will actually change? What won’t? Where are the risks? What’s in it for me? In most cases AI isn’t replacing roles. It’s removing repetitive or administrative work so people can focus more on judgment, collaboration, and creative problem-solving.

How do you encourage this open approach at Unzer?  

Niv: One important lesson is that transformation doesn’t scale through a central team sending instructions. It scales through peers. That’s why we introduced AI ambassadors across departments. These are colleagues within different teams who understand the day-to-day reality of their department’s work. They act as coaches and sounding boards, helping translate general AI capabilities into something practical for their teams. We also invest a lot in trainings, and this year, we organise an internal AI week. That’s week full of content completely dedicated to learning about and experimenting with AI. 

How have AI use cases evolved across the company?

Niv: I’d say quite significantly. At the beginning, adoption was concentrated among early adopters  typically people working heavily with text or code. Now we’re seeing much broader adoption across departments. Sales teams are automating reporting and preparing merchant briefings more efficiently. Compliance teams are experimenting with structured document analysis. Operations teams are building AI-supported workflows to help merchants faster.

The ambition is that every employee at Unzer becomes AI-enabled. What does that actually mean?

Niv: It means is that everyone reaches a shared baseline of understanding and AI usage skills. Knowing when AI can help, when it shouldn’t be used, and how to question its outputs critically. In the future, AI literacy will feel as normal as digital literacy does today. Not optional, not for a few people, but simply part of professional competence.

How do you balance innovation with responsible AI use, especially in a regulated fintech environment?

Niv: Responsible adoption is non-negotiable. That means clear governance, strong data protection standards, and human oversight. AI can support decisions, but accountability always stays with people.

How are you using AI so that it helps your merchants?

Niv: AI’s benefits don’t stop with Unzer employees: our ultimate goal is to create real advantages for our merchants. On one level, all the efficiency gains and workflow automation we’re achieving internally mean we respond faster, onboard merchants more smoothly, and deliver insights more quickly. For example, our AI solutions help prepare merchant periodical business reports, analyze transaction trends, spot opportunities and identify potential issues proactively.

Looking ahead, we’re working towards offering our merchants access to specialized AI tools, so they, too, can automate processes, get actionable analytics, and ultimately deliver a better experience to their own customers. It’s about making sure AI drives real, tangible benefits throughout the whole ecosystem, not just inside our own walls.

About Niv Liran

Niv Liran is the Chief Product and Technology Officer at Unzer, where he leads the company’s product and engineering teams and shapes its technology strategy. Under his leadership, Unzer has built a single platform that brings together online and in-store sales, giving businesses a complete, real-time view of their customers and operations. He also guides Unzer’s work in artificial intelligence, overseeing the company’s AI roadmap and initiatives.