There’s a version of AI product design that’s mostly about making screens look futuristic. Dark mode, glowing gradients, animated data visualizations. It photographs well and communicates almost nothing about whether the product actually works for the people using it.
The ai designers on this list are the other kind. They’ve worked through the actual hard problems – how do you build trust with users who didn’t ask for AI, how do you communicate uncertainty without undermining confidence, how do you design for adoption when the product does something users have never seen before.
1. Nataliya Sambir – Linkup ST
Years of experience: 12
Primary focus: UX, Conversion Optimization, Emotional Design
Key services: UI/UX Design, Product Design, UX Consulting
Location: Europe
Twelve years of practice, built around a framework that treats AI product design as a two-track problem. The functional track: every design decision tied to a specific metric and business objective. The emotional track: how users feel at each interaction across visceral, behavioral, and reflective experience levels. For AI businesses, the emotional track is often what determines whether users actually adopt the product or quietly avoid it while technically using it.
Work at Linkup ST has reached 70M+ users worldwide. 40+ global recognitions including Red Dot, Webby, and Apple. The ai graphic designer who approaches conversion as a design outcome, not a separate marketing problem.
4. Ben Shih – Miro
Years of experience: 7+
Primary focus: AI Product Design, Growth Design
Key services: AI Feature Design, Onboarding Design, Product Growth, Conversion Optimization
Location: Amsterdam, Netherlands
Portfolio: benshih design
Data science background first, design second – which changes how Ben approaches AI products in ways that matter practically. At Miro he redesigned how AI surfaces to new users across the product. At Lokalise he built an AI-first translation review system that replaced a spreadsheet-heavy manual process – the exact pattern most B2B AI businesses are trying to execute. Twenty-plus indie apps shipped over a decade. Available for consulting alongside his staff role.
5. Andrii Hadai – Lazarev Agency
Years of experience: 15
Primary focus: AI Product Design, Creative Direction
Key services: UI/UX Design, Creative Direction, AI Product Interfaces, Design Systems
Location: United States
Fifteen years of design, currently heading the department at Lazarev Agency. The portfolio covers AI compliance dashboards, robotics control interfaces, smart farming platforms, and industrial AI tools – the kinds of projects where interfaces have to make complex automated decisions legible to professional users who need to trust and override the system. European Design Award Gold as Creative Director on Lazarev’s own site.
6. Roman Kaminechny – Cieden
Years of experience: 10+
Primary focus: B2B SaaS, AI UX, Design Systems
Key services: UI/UX Design, Design Systems, UX Audits, AI Feature Design
Location: Lviv, Ukraine
As an ai designer working specifically in B2B SaaS, Roman deals with the problem that doesn’t get enough attention: how do you introduce AI capabilities into a product users already have established workflows around, without those workflows becoming the obstacle to adoption? Ten years of practice across design systems, UX analytics, and application design spanning healthcare, fintech, edtech, and AI verticals.
7. Iryna Serednia – Cieden
Years of experience: 10+
Primary focus: UX Strategy, Healthcare & AI Product Design
Key services: UX/UI Design, UX Strategy, Product Design, AI Healthcare Interfaces
Location: Cochrane, Canada (remote)
Co-founded Cieden. Deep background in healthcare product design – EHR systems, clinical workflow tools, medical device interfaces – which develops specific instincts around designing for high-stakes decisions with incomplete information. That rigor transfers directly to AI products where probabilistic outputs meet real-world consequences. Recent AI in Healthcare certification from Emeritus. Available remotely across North American and European time zones.
8. Ioana Teleanu – AI-R Design Studio
Years of experience: 12+
Primary focus: AI Product Design, AI UX Strategy, Consulting
Key services: AI Product Design, AI UX Consulting, Design Leadership
Location: Bucharest, Romania (remote)
Clipboard AI at UiPath won Time Magazine’s Best Invention of 2023. First designer on Miro’s AI team. US Design Patents for AI product work. Consulting clients include Anthropic, Framer, Adobe, Notion, ElevenLabs. Speaker at SXSW, TED AI, GitNation. Creator of the most-enrolled AI for Designers course on Interaction Design Foundation. 250K+ design community followers. Runs AI-R Design Studio taking AI business projects where the design challenge is serious enough to warrant the most experienced person in the room.
9. Kirill Lazarev – Lazarev Agency
Years of experience: 10+
Primary focus: AI Digital Product Design, Startup Design
Key services: AI Product Design, UX Strategy, MVP Design, SaaS Design
Location: San Francisco, CA
Built Lazarev Agency from a one-person operation to 40+ people, 120+ design awards, $500M raised for clients. AI practice active since 2018. San Francisco base keeps the agency close to how the AI investor and enterprise buyer market is actually developing. Five Webby Awards. Six Red Dot Awards. Work across fintech, healthcare, Web3, SaaS, and AI-native products.
10. Andrew Sapkowski – Cieden
Years of experience: 6+
Primary focus: Product Design, AI UX, B2B SaaS
Key services: UI/UX Design, Product Design, Design Systems
Location: Ukraine
Product designer at Cieden working on B2B SaaS and AI-enabled products across healthcare, fintech, and enterprise software. Full product design lifecycle from discovery through high-fidelity design and design systems. Part of the team actively developing AI UX patterns for integrating AI into enterprise products without breaking existing user workflows – one of the more common and underestimated challenges in AI product work right now.
How to Find the Right AI Designer for Your Project
Start with the specific AI design problem, not a general brief
The relationship between ai and designers is still being defined – which means the gap between someone who genuinely understands AI product design and someone who’s added it to their service list is larger than in most design categories. A specific brief surfaces that gap quickly. Vague briefs let everyone look equally capable until you’re three months into an engagement.
Ask for evidence of shipped AI products
Every designer working today has used AI tools. That’s not the signal. The signal is whether they’ve designed for AI products – interfaces where outputs are probabilistic, where trust needs to be built through interaction design, where the feedback loop between AI behavior and user understanding is a core design problem. Ask for specific examples with specific outcomes.
Look for ai design services that understand business context
The best ai design services for AI businesses don’t treat design as a separate function from business development. They understand that the product experience affects enterprise deals, investor perception, and user adoption simultaneously – and they design with all three audiences in mind. Ask how they’ve thought about the business context of AI design work, not just the user experience.
Evaluate how they think about trust as a design material
For AI products, trust isn’t a nice-to-have – it’s the product. The interface either builds it through the quality of every interaction or erodes it through ambiguity, inconsistency, and poor error handling. Ask designers specifically how they approach trust as a design problem. The answer reveals whether they’ve worked through it or are just aware of it as a concept.
Check their approach to AI failure states
How ai designers handle failure states – wrong outputs, miscalibrated confidence, unexpected behavior – tells you more about their AI product design maturity than any portfolio piece. Ask specifically: walk me through how you’ve designed for a situation where the AI was wrong and the user needed to know that without losing confidence in the product overall.
Match engagement model to product lifecycle
AI products keep evolving. The right engagement model evolves with them. Some of the top AI design companies on this list offer ongoing embedded models specifically for this reason – design as a continuous function rather than a periodic project. Match the engagement structure to where your product actually is in its lifecycle.
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