The future of product design: How AI and data will change business

As the boundaries between design, data, and AI continue to dissolve, a new paradigm is taking shape, where human-centric design meets machine-native intelligence.

We interviewed Kirill Lazarev, founder and CEO of Lazarev.agency, to answer a simple question: “What’s the future of  product design?” Kirill shares his deep insights on how businesses must evolve to thrive in a future shaped by personalization, intelligent agents, and context-aware interfaces.

Key takeaways

• AI-powered UX must move beyond chatbots into hyper-contextual experiences.
• Vertical AI will emerge from data ecosystems, especially sensor-rich industries.
• The designer’s role will shift from creator to strategic architect.
• Personalization will be cultural, behavioral, and machine-generated.
• The businesses that win will be those who build and productize these new experiences.

Designing for intelligence

“Design is no longer about just what something looks like,” says Kirill Lazarev, reflecting on a decade of leading product design at Lazarev.agency. “It’s about understanding behavior, business goals, and the full lifecycle of user interaction from onboarding to pricing to emotional moments of conversion.”

He emphasizes that data should no longer be seen as something passively collected. The real value begins when data is treated as a product, a foundation for intelligent systems that fuel cross-sector collaboration and AI development.

Take electric vehicle (EV) charging infrastructure, for example. Sensor-rich environments like these produce enormous streams of data from battery stats and charging patterns to vehicle types and location behavior.

Companies that treat this data as internal-only are missing the opportunity to unlock broader value. When packaged properly, it can power entire vertical AI ecosystems, fueling insights for insurers, manufacturers, and even competitors.

Dynamic experiences

In 2017, Lazarev’s agency worked with a startup building market prediction models from sentiment analysis. At the time, it was an experimental AI. Today, it’s the baseline. What’s the difference now? Experience design has caught up.

“The real innovation,” Lazarev explains, “was in realizing that people didn’t want static dashboards. They needed interfaces that responded to them. So we started building products where the UI adapted to behavior in real time.”

With the rise of generative AI, he sees the next evolution: interfaces that design themselves instead of just displaying data.

“The front-end can now be generated per user, per use case, per goal. The whole concept of a ‘universal interface’ is outdated.”

Experience becomes infrastructure

Kirill Lazarev believes the next leap lies in transforming UX design into infrastructure.

“Design thinking has always been viewed as high-touch and exclusive. But AI can help make it scalable. If we can productize even 60–70% of what a top-tier designer does, especially for early-stage founders, that’s a game-changer.”

He envisions systems that generate experience flows, iterate based on real user feedback, and tie into the broader product journey, not just interface decisions, but emotional ones.

“Getting users to that aha moment? That’s not luck. It should be intentional, designed, and data-driven.”

Machine-to-machine UX

We’re moving into a space where machines interact with each other more than with people, raising a bold new question: how do you design experiences for agents?

“As AI agents begin making decisions, completing tasks, and interacting with other agents,” says Lazarev, “we need to design for machine-to-machine UX. What happens when your AI negotiates with 100 others to get you the best result?”

It’s not science fiction. AI-powered sales reps (SDRs), generative ecommerce assistants, and hyper-personalized recommendation engines that use real-time behavior, purchase history, and even emotional tone to drive interactions.

“When the human leaves the loop,” Lazarev notes, “timing, accuracy, and micro-decisions become everything. You don’t design for engagement, you engineer for it.”

Culture, context, and the Internet as a super-app

Kirill Lazarev also highlights the growing role of cultural and contextual personalization. Designing for a Western, low-context culture is fundamentally different from designing for high-context cultures like East Asia.

In a future where AI mirrors human language, culture, and thought, personalization needs to be deeper than traditional segmentation.

So what’s next? The internet may evolve into a single super-app, but the experience of that app will be unique for every user, every time.

Closing thoughts: What business leaders should do now?

Reflections and predictions are valuable, but the real question is: what should businesses act on today?

Kirill identifies three immediate opportunity areas:

1. LLM Optimization: Start optimizing ecommerce and informational content for ChatGPT, Claude, and other large language models. SEO for AI is coming fast.
   
   
2. Outreach Tactics: Rethink how you identify, qualify, and convert leads. AI agents can reshape this funnel, but only if experience design is built into the process.
   
   
3. Productizing Design: Don’t just offer design as a service. Turn it into a scalable, repeatable product. Build the systems now that will support the long tail of AI-driven startup growth.

Those who build intentionally, who understand how to merge data, insight, and design at scale, won’t just stay ahead. They’ll define the curve.