What Market Leaders Need to Know About AI and UX

By Brian Marr 

All brands today are facing the need to rethink how their digital products and experiences are designed, built—and importantly, evolve—over time. With the rapidly changing tech landscape comes changing user expectations. At Work & Co, we see the intersection of AI and user experience as one of the foremost challenges facing brands today.

AI isn’t just transforming workflows behind the scenes; it is fundamentally changing how people relate to digital products. The result is smarter, more responsive interfaces that adapt, anticipate, and feel deeply personal. Our most impactful work involves helping clients move beyond novelty, building AI-powered experiences that drive real outcomes at scale.

I want to share a set of key recommendations based on our hands-on experience—insights that can help any organization and leader navigate this new era with confidence.

1. Design Beyond the Interface and Build Intelligent Systems

Traditional UX has revolved around the interface: visuals, navigation, usability. Generative AI demands a shift—placing true intelligence at the core of every product. This means planning for natural language experiences (increasingly referred to as NLX) that allow users to interact with products through conversation as naturally as they would with another person. Today, leading brands expect more adaptive, predictive, and contextual experiences.

Take our work with Gatorade: the AI Bottle Builder is not simply a new feature; it’s a reimagined product journey. Athletes can now select interests, vibes, and colors, guiding generative AI to deliver unique, on-brand designs—all seamlessly integrated into Gatorade.com. The result is personalization that is both approachable and authentic, putting creative control directly in users’ hands.

Key considerations:

• Are you enabling your product to learn and improve continuously?
• Do users have clear, direct control over how AI influences their experience?
• Is the role of AI visible and understandable, not just hidden in the background?

Where to start: Prototype adaptive flows that respond to individual behavior. Map existing data to moments where personalization genuinely adds value—without undermining trust.

2. Deliver Personalization as a Service, Not a Gimmick

Many organizations treat personalization as window dressing: a welcome message, a product suggestion. True AI-powered personalization is ongoing, refining itself with every interaction to simplify decisions, reduce friction, and meet users across a spectrum of contexts.

With Pfizer, we launched Health Answers—a generative AI platform that provides trusted health information in real time. By allowing users to create personalized health profiles, the experience delivers tailored, science-based answers with transparency, user control, and clear explanations for every recommendation.

Key questions:

• Does your personalization tangibly improve the user experience?
• Are you clear and transparent about data usage, with user opt-in as a priority?
• Can users adjust or override personalization for control and trust?

Where to start: Audit current rules-based personalization. Evolve toward proactive, adaptive systems that anticipate needs and respect user boundaries.

3. Move from Consumption to Collaboration

Digital products have historically been passive: users browse, click, consume. AI enables a mode of co-creation and collaboration—particularly in domains like commerce, travel, and creative tools.

We’ve built AI-driven commerce and travel experiences, as well as interfaces for LLMs themselves, that make generative systems collaborative partners rather than invisible engines. The best results emerge when the AI’s “role” is explicit—enabling users to guide, correct, or collaborate as needed.

Key evaluations:

• Does your product allow users to actively shape what AI delivers?
• Is the value of AI surfaced in the user workflow, not hidden in back-end logic?
• Do users understand the boundaries and capabilities of the AI?

Where to start: Map key product journeys where AI could support, enhance, or automate tasks alongside the user. Prototype collaborative assistant features.

4. Prioritize Ethics and Trust in Every AI Decision

The rise of AI elevates longstanding questions of data, bias, and trust. Ethical AI is not an afterthought or compliance issue—it is intrinsic to product and brand strategy.

Our approach embeds ethics reviews, diverse perspectives, and transparency at every stage of the product lifecycle. We draw inspiration from broader industry standards, such as Google’s AI Principles, integrating practices like clear explanations, thoughtful defaults, and inclusive design into everything from copy to onboarding.

Assessment points:

• Is your AI system explainable, auditable, and inclusive of diverse users?
• Are default settings aligned with user empowerment, not just efficiency?
• Are you building processes to surface and address bias, exclusion, or unintended behavior?

Where to start: Integrate ethics checkpoints into design sprints. Solicit broad input throughout the process, especially early on.

5. Scale Purposefully by Experimenting and Iterating

Adopting AI at scale is a muscle that gets built through rapid, thoughtful experimentation. Not every pilot is a moonshot—small, focused prototypes lead to the kind of organizational knowledge required to adapt confidently.

We recommend standing up cross-functional teams, giving them specific, high-impact challenges, and building a culture that embraces learning from failure. This is how leaders stay ahead—not just tracking shifts but shaping them.

Critical questions:

• Are teams empowered with the right resources, frameworks, and space to experiment?
• Are you measuring real impact: time saved, engagement depth, or reduced cognitive load?
• Is the organization, end-to-end, ready to evolve alongside new AI capabilities?

Where to start: Select one high-friction user journey. Explore how AI can reduce user effort or deepen value—and iterate quickly.

Looking Forward: Smarter Experiences, Deeper Relationships

As AI becomes more ambient and emotionally intelligent, the most successful brands will not only meet these new technical standards, but deliver more intuitive, engaging, and human-centric experiences. The shift from passive interfaces to adaptive, collaborative systems is well underway—across mobile, web, retail, and beyond.

Work & Co will continue driving this shift with our partners, from Fortune 500s to emerging leaders defining the next era of digital product. For brands prepared to lead, the opportunity is not just smarter interfaces—it’s fundamentally deeper digital relationships.

It’s time to reimagine your digital products as intelligent, adaptive, and trusted systems. 

About the author

Brian Marr is a leader at Work & Co with a track record of transforming teams and driving sustainable impact. Known for building data-driven organizations and enhancing strategic outcomes, Brian shares his expertise as a Senior Affiliate Instructor at the University of Washington, where he teaches Advanced Marketing.