|
8
min read

Top AI Designers Creating Intelligent User Experiences in 2026

Leading AI Designers Shaping the Future of Product Design
Looking to hire AI designers fit for a serious AI business project? These are practitioners who've shipped AI products, worked with AI companies at growth stage, and understand the specific design challenges that come with building credibility and adoption for intelligent systems.
Andriy Sambir
Andriy Sambir
Chief Executive Officer
OUTLINE

AI businesses have a design problem that general design agencies aren't built to solve. The product needs to feel credible to enterprise buyers before a single demo. The interface has to build trust with users who are skeptical of AI outputs by default. The onboarding has to work for people who've never used a tool like this before. And all of it has to connect to conversion, retention, and expansion — because in AI businesses, the product experience is the sales process. Finding an ai designer who gets this is harder than it should be. This directory focuses on designers with real AI business project experience.

Nataliya Sambir

LinkedIn profile

Years of experience: 12

Primary focus: UX, Conversion Optimization, Emotional Design

Key services: UI/UX Design, Product Design, UX Consulting

Location: Europe

AI businesses need design that converts skeptical buyers and builds trust with reluctant users simultaneously. That's the specific problem Nataliya's practice is built around. Her Emotional-Functional Framework runs two tracks: OKR-driven functional design where every decision connects to a metric, and emotional design that works across visceral, behavioral, and reflective experience layers. For an AI business, that reflective layer — does this product feel like it understands my problem, does it feel like something I'd trust with real decisions — is often what determines whether enterprise deals close.

Twelve years of practice. Work that's reached 70M+ users. 40+ global recognitions including Red Dot, Webby, and Apple. The kind of ai graphic designer who treats conversion as a design outcome, not a marketing afterthought.

Pavlo Savchenko

LinkedIn profile

Years of experience: 8

Primary focus: UI/UX

Key services: Conversion Optimization, UI/UX Design, Product Design, UI/UX Audit

Location: Ukraine

AI businesses rarely fail because the model is bad. They fail because users don't understand what the product is doing, don't trust the outputs, or can't figure out how to integrate it into their workflow. Pavlo's ai design services are specifically oriented toward finding and fixing those failure points — through structured audits, conversion optimization, and ongoing iteration tied to specific business metrics.

Eight years at Linkup ST. The performance model he operates within embeds him in client workflows on an ongoing basis, which matters for AI businesses where the product keeps evolving as the model does. Design as a continuous business function, not a one-time delivery.

Darya Ebadian

LinkedIn profile

Years of experience: 5+

Primary focus: UI/UX Design, Product Design

Key services: UI/UX Design, Product Design, Mobile App Design, UI/UX Audit

Location: Ukraine

Darya leads UI/UX at Linkup ST across web, mobile, and product design. For AI business projects specifically, her strength is in the translation layer — taking complex AI capabilities and making them feel approachable and credible to users who didn't ask for AI and aren't sure they want it.

Her background spans Lynksen, Dodotap, and Artman Studio before Linkup ST, building breadth across product types and user contexts. She works within the Emotional-Functional Framework, which means visual decisions get evaluated against measurable business outcomes rather than aesthetic judgment alone.

Ben Shih

LinkedIn profile

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

Ben is the kind of designer AI businesses need when the core challenge is adoption. His background in data science means he approaches AI product design as a systems problem — not just how does this look, but how does this behavior get communicated, how does trust get built through the interaction pattern, how does the product get users to a moment of genuine value before they give up.

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 — which is exactly the pattern most B2B AI businesses are trying to execute. Available for consulting.

Andrii Hadai

LinkedIn profile

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 practice, currently running the department at Lazarev.Agency — an agency that's been doing AI product design since 2018, before most agencies had a position on what that means. Andrii has directed work on AI compliance platforms, robotics control interfaces, smart farming dashboards, and industrial AI tools. The range covers the kinds of AI business projects where the interface has 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. The portfolio is worth looking at directly — the AI interface work is technically serious.

Roman Kaminechny

LinkedIn profile

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: Ukraine

Most AI business projects aren't building AI from scratch — they're adding AI capabilities to existing B2B products and figuring out how to get users to actually adopt them. As an ai designer who's worked through this specific problem repeatedly, Roman understands the constraints: users who've built workflows around the existing product, enterprise buyers who need to see clear value before they'll approve rollout, product teams who need to ship AI features without breaking what's already working.

Ten years of practice. Cieden has been publishing seriously on AI UX patterns — the thinking behind the work is visible publicly, which tells you something about how seriously they take the category.

Iryna Serednia

LinkedIn profile

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: Canada

AI businesses in regulated industries — healthcare, insurance, financial services, legal — face design problems that don't exist in other verticals. The AI output has real-world consequences. The interface has to support good professional judgment, not replace it. Compliance and explainability are design requirements, not afterthoughts.

Iryna co-founded Cieden and has spent a significant portion of her practice on exactly these contexts — EHR systems, clinical workflow tools, medical device interfaces. Her recent AI in Healthcare certification from Emeritus reflects active engagement with how AI changes design requirements specifically in regulated environments. Available remotely across North American and European time zones.

Ioana Teleanu

LinkedIn profile

Years of experience: 12+

Primary focus: AI Product Design, AI UX Strategy, Consulting

Key services: AI Product Design, AI UX Consulting, Design Leadership, Speaking & Education

Location: Romania 

For AI businesses where the design decisions are genuinely high-stakes — where the interface shapes how users relate to AI, how much they trust it, how they calibrate their own judgment against its outputs — Ioana is the most credentialed independent consultant on this list.

Clipboard AI at UiPath: Time Magazine 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.

She runs AI-R Design Studio now, taking on AI business projects where the design challenge is serious enough to warrant the most experienced person in the room.

Kirill Lazarev

LinkedIn profile

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

Kirill built Lazarev.Agency from a one-person operation into a 40+ person team with 120+ design awards and a track record of supporting clients in raising $500M. The agency has been doing AI product design since 2018. Based in San Francisco, Kirill is active in the AI startup and investor ecosystem — which means the agency understands what AI businesses need to show investors and enterprise buyers, not just users.

For AI businesses at the fundraising or go-to-market stage, that combination of design quality and commercial orientation is relevant. Five Webby Awards. Six Red Dot Awards. Work across fintech, healthcare, Web3, SaaS, and AI-native products.

Andrew Sapkowski

LinkedIn profile

Years of experience: 6+

Primary focus: Product Design, AI UX, B2B SaaS

Key services: UI/UX Design, Product Design, Design Systems

Location: Ukraine

Andrew works on B2B SaaS and AI-enabled products at Cieden. His focus is the execution layer — taking the strategy and research through to high-fidelity design and design systems that development teams can actually build from. Part of the team actively working through AI UX patterns for the specific challenge of integrating AI into enterprise products without breaking existing user workflows.

For AI businesses that need a strong execution-level designer embedded in a team with genuine AI UX depth, Cieden's model — and Andrew's role within it — is worth understanding.

How to Choose an AI Designer for Your Project

Define what kind of AI design problem you actually have

AI business design challenges are not all the same. Building trust for a brand-new AI-native product is a different problem from adding AI features to an existing enterprise SaaS tool. Designing for a regulated healthcare AI is different from a consumer generative AI product. Get specific before you start evaluating candidates — the right designer depends almost entirely on what the actual problem is.

Look for ai design services that understand the business context, not just the interface

The best ai design services for AI businesses treat the product experience as a business development function. The design isn't just for users — it's for buyers, procurement teams, and investors who evaluate AI products through the quality of the experience before they evaluate the underlying technology. Designers who understand this build differently than those who treat it as a pure UX problem.

Match domain experience to your industry context

A designer with serious B2B SaaS AI experience understands enterprise buyer dynamics, multi-role user environments, and the organizational change management dimension of AI adoption. A designer with healthcare AI experience has worked through regulated context constraints and high-stakes decision support design. Domain experience is not decorative — it changes the quality of design decisions in ways that only show up under real-world conditions.

Evaluate how they think about AI credibility as a design problem

For AI businesses, credibility is a design output. Not just usability, not just aesthetics — the interface either makes the AI feel trustworthy and capable to the relevant audience, or it doesn't. Ask designers how they approach this specifically. What signals communicate AI reliability? How do they handle error states without undermining confidence? How do they make AI outputs feel appropriately authoritative without overstepping?

Ask ai designers how they design for skeptical users

Most users of AI business products didn't request AI. They're using it because their company bought it, their industry is adopting it, or their workflow now includes it. Designing for adoption when users start from skepticism or indifference is a specific skill. How ai designers approach this — progressive trust building, appropriate AI visibility, user control that feels real rather than performative — separates those who've worked with AI businesses from those who've designed for willing early adopters.

Consider whether you need project-based or ongoing design engagement

AI businesses keep shipping. The model changes, the product evolves, user behavior surfaces new design problems. A one-time engagement produces a snapshot. An ongoing design partnership grows with the product. Several designers on this list operate in ongoing embedded models specifically because AI business projects don't end at launch — they're continuous. Match the engagement structure to the actual lifecycle of your product.

Right arrow

Frequently Asked Questions

No items found.
Andriy Sambir
Andriy Sambir
Chief Executive Officer
Share
Right arrow

Craft your idea into awesome digital experience

Let’s talk
Right arrow
No items found.