Infinum’s latest transformation embeds AI into every phase of digital product delivery, helping teams move faster, align earlier, and deliver higher-quality software without compromising control, compliance, or creativity.
Generative AI and code-aware machine learning tools are transforming the entire product development lifecycle, from the first whiteboard sketch to the final deployment.
According to McKinsey, 71% of companies now use generative AI in daily operations. At Infinum, adapting to this reality meant fundamentally reengineering our delivery playbook around AI.
Strategic AI at scale
AI isn’t new for us.
Our AI & Data Engineering team builds real-world applications powered by machine learning, computer vision, and large language models, from ML-powered recipe recommender and smart home energy management to medical imaging and automated privacy protection on the road.
But over the past two years, we’ve taken this expertise further by integrating AI into nearly every stage of the digital product lifecycle: research, planning, design, development, testing, and production monitoring. This rollout follows a structured framework that helps teams ensure quality without sacrificing human oversight.
We took a structured, ethical, and pragmatic approach to adopting AI that helps our teams ship faster, spend smarter, and sleep better knowing quality is climbing, not slipping.
IVAN ĐIKIĆ, VP OF ENGINEERING, INFINUM
Empowering people, not replacing them
While curiosity drove early exploration, responsible usage demanded more. What began as a grassroots, champion-led initiative, with AI leads in every team, regular Show & Tell sessions, and internal knowledge sharing, has since moved toward a structured framework.
Today, AI adoption at Infinum is governed by key company-wide standards: vetted tools, strict usage guidelines, and a commitment to continuous capability-building.
Our principle remains clear: AI is here to extend our people’s expertise, not replace it. Security and compliance, especially in client engagements, remain non-negotiable.
“With this initiative, Infinum’s culture evolves from cautious curiosity to confident integration of AI. Our teams are actively shaping AI workflows that enhance how we build software, driving greater efficiency and creativity. It’s all about amplifying our impact,” said Nikola Kapraljević, Infinum CEO.
We’re also clear-eyed about the risks. Without structure, AI adoption can become fragmented and insecure. With strategic intent, it becomes a long-term enabler of value for both our teams and our clients.
Where AI delivers the most impact
When it comes to implementing AI into our processes, we see the biggest gains in kickstarting our projects. Some of the most notable use cases include:
Strategic kickoffs
By pairing insights from strategy workshops with requirements-aware LLMs, we can auto-generate user stories, acceptance criteria, and architecture diagrams. This streamlines the handoff from alignment to execution, accelerating early momentum.
Faster prototyping and iteration
AI tools help teams rapidly turn concepts into clickable prototypes. Early pilots show a 40% reduction in prototyping time, a figure that improves as our component libraries grow. This speed enables earlier validation and more effective iteration, setting a clearer path for development.
Smarter development and alignment
In the development phase, AI plays a critical role in shaping robust, production-ready solutions. Engineers remain firmly in control, while AI acts as a capable co-pilot, taking on repetitive tasks such as code refactoring, identifying edge-case bugs, and generating unit tests. This enables teams to focus on architecturally sound, secure, and user-aligned solutions.
AI-powered code reviews
Code changes now pass through automated AI reviewers that flag logic errors, security vulnerabilities, and test gaps. Engineers retain full oversight, but with more time to focus on strategic technical work. The result: cleaner, safer code.
Looking ahead
While AI integration is often seen as a cost-saver, the reality is more complex, at least in the short term. “Investments in team licenses, enablement, and governance are significant. But for us, this is a strategic investment in long-term relevance.” – concluded Kapraljević.
This integration is our strategic investment in long-term relevance. Tomorrow’s clients won’t be asking if their partners use AI, they’ll expect it. They want future-ready partners, not outdated processes.
NIKOLA KAPRALJEVIĆ, CEO, INFINUM
By embedding AI across strategy, design, development, and delivery, we’ve created workflows that are faster, more focused, and easier to scale. At Infinum, it isn’t a side experiment or a future plan, it’s a practical tool we use today to build better software of tomorrow.