· UX Meridian research team

Best AI UI/UX Design Agencies (2026)

a hand holding a laptop

The short answer

Isadora Agency, Teague and MetaLab lead this list. Isadora pairs UX research with web and product development, and built AI-powered search for a technical college that interprets plain-language questions and surfaces matching programs across 50+ offerings. Teague designs interfaces for AI and autonomy where operators act on machine output, as for a startup's off-road autonomous vehicles. MetaLab designs brands and products for AI companies, including a prompt-to-song platform.

AI UX covers two kinds of work: adding AI to a product people already use, such as search, recommendations or a support assistant, and designing a new AI product, where the interface has to show what the system did and let people correct it. Some agencies below come from websites and digital products, some from industrial design, and some from consulting firms that build AI platforms for large clients. Each of the eight names client work with an AI component on its own website.

The ranking weighs shipped AI features over AI messaging, research with the people who rely on the output, interfaces that make machine decisions readable and correctable, and how each team is staffed and sold.

Quick picks

For mid-market and enterprise teams adding AI features to a website or product, with UX research and development from one team

Isadora Agency

For AI and autonomy in defense, industrial or robotics systems

Teague

For an AI company that needs brand and product design for launch

MetaLab

For an AI platform built inside a large consulting program

BCG X

Rank

Agency

Specialty

Team size

Founded

1

Isadora Agency

UI/UX design, UX research and web development for AI-powered products

11 to 50

2009

2

Teague

Interfaces and human factors for AI-enabled and autonomous systems

1926

3

MetaLab

Brand and product design for AI tools such as Suno and Otter

160

2006

4

Designit

Service and workplace design with AI built into support

1991

5

AKQA

Brand experiences and AI-generated commerce interfaces within WPP

6,500+ in 50+ countries

1994

6

BCG X

AI platforms and new ventures built within BCG engagements

3,000+

7

Huge

Conversational AI and digital platforms for consumer brands

1999

8

IDEO

Field research and design for new AI products and brands

1991

Methodology

We started from each agency's own website and kept only firms that name a client project with an AI component: an AI feature inside a product, an interface for an AI system, or a product built for an AI company. Pages about AI without a named client didn't count. We then compared how close each firm's AI work sits to the people using it, whether research with users or operators shaped the design, and whether the interface explains what the system did and lets people step in. We also weighed the wider UX practice behind the AI work, because search, content structure and design systems decide how well an AI feature performs. Fit came last: team size, ownership and how a buyer would engage each firm. Facts we couldn't confirm on a firm's own site are left blank.

UI/UX design, UX research and web development for AI-powered products

Isadora Agency works with mid-market and enterprise organizations, designing and developing their websites and digital products. Its UX team relies on competitive benchmarking, analytics, user interviews and testing with real audiences. The AI work comes from five years of partnership with Texas State Technical College, which grew from a redesign into a WordPress multisite platform for 10 campuses and more than 50 programs. The platform's AI-powered search, implemented through Element 451, reads plain-language questions and surfaces matching programs, services and next steps. Workshops with marketing, admissions and program leaders set its direction, and it links to the college's Element 451 CRM and to Workday for enrollment. The case study reports application starts up 453% and completed submissions up 217% over the partnership, and ongoing work covers journey mapping, CRO and further AI integration. For Kelley Blue Book, Isadora built a UX design system spanning typography, icons, illustration and components, and put full pages through user experience testing.

Covers

UI/UX design, UX research and strategy, product design, AI integration, design systems, web development

Ideal client

Mid-market and enterprise products adding AI features for easier discovery, paired with UX research and web development

Notable clients

Texas State Technical College, Kelley Blue Book, Autotrader, Sunbit, Upli, NCCER

Recognition: MUSE Creative Awards Silver 2026 (APS Payroll website); AVA Digital Awards Platinum 2022 (News Corp benefits video)

Interfaces and human factors for AI-enabled and autonomous systems

Teague, founded in 1926 and owned entirely by its employees, designs products and systems for companies in defense, mobility, aviation, robotics and technology. Its services page frames AI design around accountability: what data is appropriate, how people understand outputs, when they step in and who stays responsible. The main example is the startup Overland AI, which builds off-road autonomy for military vehicles. Teague opened with a two-week design definition sprint, compared military, professional and commercial interfaces, then coded the frontend alongside Overland AI's backend developers. Within months the delivered software handled vehicle mapping and live video, plus robot telemetry and tasking and the management of several vehicles at once. The interface borrows patterns from consumer navigation tools to cut training time for operators. Teague's client list also includes Shield AI and Noble Machines, which builds humanoid robots.

Covers

AI and autonomy interface design, user research and human factors, product design, prototyping, futures and strategy

Ideal client

Companies putting AI and autonomy into products where operators must trust and act on the output

Notable clients

Overland AI, Shield AI, Noble Machines

Not the right fit when: The AI feature sits in a consumer app; Teague's AI work centers on defense, industrial and robotics systems.

Brand and product design for AI tools such as Suno and Otter

MetaLab, part of Andrew Wilkinson's holding company Tiny, has designed software products since 2006 and lists 160 people on its About page. Its AI practice helps teams judge AI readiness, find real use cases and decide whether to buy a tool or build one. Work in the category includes Suno's prompt-to-song platform, where a brand engagement grew into a partnership across brand, product design and engineering, with component libraries for Suno's team. The AI clients on its site also include Otter, Together.ai, Modular and Crusoe. Windsurf, an AI coding assistant, received a full rebrand from the studio, and its AI page describes taking teams from a first build through to global launch.

Covers

AI product strategy, product and interface design, brand identity, design systems, engineering support

Ideal client

AI startups and product companies that need brand, product design and engineering support for launch

Notable clients

Suno, Otter, Modular

Not the right fit when: The AI work is a back-end model or data platform; MetaLab focuses on the product and brand people see.

Recognition: Fast Company Most Innovative Design Companies 2026

Service and workplace design with AI built into support

Founded in 1991 and part of Wipro since 2015, Designit calls itself an experience innovation company and works from studios that include Copenhagen, Oslo and Seattle. At a telecom company, staff found the internal IT support used by 80,000 employees overly technical and hard to navigate. Working with Wipro, Designit ran user research across roles and regions, mapped journeys with leadership and support teams, and redesigned the service so that AI became the first line of support and pointed people toward quick resolutions. Communication and change design were part of the scope, to turn the new tools into habits. The firm's work index also lists a project on reimagining work with generative AI, and its studios design service journeys for banking and investing clients such as DNB.

Covers

Service design, UX research, product design, change and communication design, design systems

Ideal client

Large organizations adding AI to employee support, service operations and internal workflows

Notable clients

DNB, Sandvik, Moove

Not the right fit when: The AI product is a consumer startup app; Designit's AI cases sit inside large organizations' operations.

Recognition: Red Dot Award 2023 (Moove brand identity)

Brand experiences and AI-generated commerce interfaces within WPP

AKQA, founded in 1994, works across brand, product and experience design and operates within WPP. An AKQA news page puts its staff at 6,500 people in more than 50 countries. Generative Store, built with Google Gemini as part of the WPP and Google partnership, is the agency's main AI example: an ecommerce experience that assembles each page in real time from a brand's design system, assets and heritage, so copy, imagery and storytelling shift with each visitor's intent. Visitors see interactive, image-led layouts in place of a chat window. Through AKQA Leap, the agency also handled product discovery and UI for Neurable's Enten headphones, and it designed a city data dashboard for A2A.

Covers

Brand and identity, product and UI design, AI commerce experiences, design systems, campaigns

Ideal client

Consumer brands testing AI-generated shopping and brand experiences as part of larger creative programs

Notable clients

A2A, Neurable, GripAble

Not the right fit when: The project is internal software for staff; AKQA's AI examples are consumer commerce and brand experiences.

AI platforms and new ventures built within BCG engagements

BCG X, the unit inside Boston Consulting Group that handles tech build and design, has more than 3,000 technologists, engineers, designers and entrepreneurs. It builds AI and GenAI products, customer journeys, large platforms and new ventures. For an iron ore producer's operation in Western Australia, BCG X built the Future Scheduling Platform, a user interface where a team of 50 schedulers reviews algorithm recommendations and makes rail and port decisions, backed by machine learning, optimization and simulation. The producer also recruited and trained an internal digital team to keep improving the platform. The insurer Signal Iduna, working with BCG, BCG X and Google Cloud, built Co SI, a GenAI assistant for its frontline service staff.

Covers

AI and GenAI product build, customer experience design, platform engineering, venture building

Ideal client

Large enterprises building AI platforms where decision-support interfaces and change management ship together

Notable clients

Signal Iduna, Konecta, Mandai Wildlife Group

Not the right fit when: You want design work without a consulting engagement; BCG X builds within BCG's strategy and change programs.

Conversational AI and digital platforms for consumer brands

Huge dates from 1999 and runs its design and technology work from 14 hubs. For a media company, it developed a natural-language chat guide that let viewers search thousands of hours of sports coverage and find where to watch each event. Huge covered product vision, experience design, conversational branding and front-end development. The guide ran on Google Cloud's Vertex platform with Gemini, and Huge describes it as its first intelligent experience. For CoinTracker, a crypto tax platform, Huge repositioned the brand and produced its campaign through a hybrid human and AI production system. For Candescent, a digital banking software provider, it set out an experience vision covering the Intelligent Banking platform.

Covers

AI experiences, product and app design, brand, design systems, commerce

Ideal client

Consumer brands launching conversational AI experiences as part of a wider digital product program

Notable clients

CoinTracker, Candescent, UNC Health

Not the right fit when: The AI need is internal tooling or data infrastructure; Huge's AI cases are audience-facing experiences.

Field research and design for new AI products and brands

IDEO has run human-centered design projects since 1991, covering strategy, products, services and new brands. IDEO's AI case centers on Aitu, a sub-brand Jack Technology created for AI-powered industrial sewing machines. Its team visited more than a dozen garment factories in China, Vietnam and Bangladesh, interviewing factory managers, industrial engineers, pattern-making leaders and frontline workers, then set the brand direction for Aitu. It helped build the brand system and designed the machines' interaction logic, with icon-based visuals for operators of varying skill, as well as the industrial and interaction design of AI10, a humanoid sewing robot. The work ran through several rounds of co-creation with Jack's team and apparel-sector stakeholders, and Aitu launched in Shanghai in September 2025. IDEO's design services also include helping companies read signals from emerging technologies such as AI and build a human-centered strategy around them.

Covers

Design research, product and interaction design, industrial design, brand creation, strategy

Ideal client

Companies defining a new AI product and brand, from field research through industrial and interaction design

Notable clients

Jack Technology, Straight Arrow News, Taylor's Education Group

Not the right fit when: The task is adding an AI feature to an existing app; IDEO's AI case builds a new product brand.

AI features depend on the structure underneath them

An AI search box or assistant answers from whatever the site or product already holds. When programs, products or help articles are scattered across departments under inconsistent names, the AI layer serves up the same confusion faster. A useful case study shows the structural work done alongside the AI feature: a cleaned-up taxonomy, consolidated content and the integrations the feature reads from.

Testing an AI interface includes testing its wrong answers

Usability testing for AI adds one question that ordinary testing doesn't need to ask, which is what people do when the system gets something wrong. Good test plans include prompts that produce weak or uncertain results, so the team sees whether people notice, how they correct the output and when they give up. Operational settings raise the stakes. BCG X's scheduling platform for an iron ore operation in Western Australia puts algorithm recommendations in front of human schedulers, who make the final call. Testing only the happy path leaves the riskiest moments unexamined.

What an AI UX engagement includes and costs

Most AI UX engagements begin with discovery about which tasks the AI should take on, what data it can draw from and where people need to stay in control. Research with the users or operators who will rely on the output follows, then flows and prototypes that show sources, confidence and ways to correct a result, then usability sessions that include wrong answers. Delivery adds visual design, a component library and work alongside engineers on the integration. Larger programs bring model development, data platforms and change management, which is where consultancy units come in. Of the eight, only Isadora Agency publishes pricing: its website and product design engagements begin in a $95K to $165K band and reach $401K and above for the largest scopes. The other seven price per project or within a broader contract.

Frequently asked questions

How much does AI UX design cost?

Isadora Agency is the one agency here with a public price: website and product design opens at a $95K to $165K band on its inquiry form, with higher bands for larger scopes. The spread across the market is wide because AI UX can mean one search feature on an existing site or a new product with its own brand, interface and data platform. Comparing quotes is simpler when discovery, user research, prototyping and integration support each carry their own price.

How long does it take to design an AI feature?

A contained feature on an existing site can fit inside a single project phase, while a new AI product takes longer because brand, interface and engineering are designed together. Teague moved from a two-week definition sprint to working frontend software for Overland AI in a matter of months. AI features also tend to arrive inside longer relationships: at Texas State Technical College, AI-powered search came as part of a five-year partnership with Isadora Agency.

How does AI improve user experience in web design?

Mainly by shortening the distance between a question and an answer. AI search can read a plain-language query and return matching pages, products or programs, and generated layouts can change what each visitor sees. AKQA's Generative Store, for example, rebuilds ecommerce pages around each visitor's intent. The gains depend on the content underneath, so clean information architecture and consistent product or program data come before the AI layer.

What makes AI UX design effective?

Effective AI UX shows people what the system did and lets them step in. Users should be able to see why a result appeared, how confident the system is and how to correct or override it. Familiar patterns help too: Teague's interface for Overland AI borrowed from consumer navigation tools to reduce training time.

Should a company build its own AI feature or buy one off the shelf?

It's mostly a question of whether the feature sets the product apart. Search, support chat and content tagging are widely available from existing platforms, and the design work lies in fitting them into the product's flows and data. A feature that defines the product, such as Suno's prompt-to-song creation, is more likely to justify a custom build. MetaLab's AI practice offers this assessment as a service, covering readiness, use cases and the buy-or-build decision.

Which UX research methods work for AI products?

Contextual research carries extra weight, because AI often changes how a job gets done. Designit's work on a telecom company's internal IT support began with user research across roles and regions before AI became the first line of support. Interviews and observation show which tasks people are happy to hand to AI and which they want to keep. Prototype tests with realistic, imperfect outputs then show whether people trust the results enough to act on them.