How the design team at Grab is redefining creativity with AI

Patrick Jean, Head of Design

. June 12, 2025 . Regional

Generative AI is reshaping the design industry faster than most teams can adapt. While many professionals feel unprepared in this time of uncertainty, Grab’s design team chose to embrace AI as an opportunity to elevate our craft, redefine our workflows, and scale our creative capabilities beyond traditional limits.

This journey has been one of discovery, learning, and innovation, and we’re proud to share how our team has leveraged AI in pursuit of more creativity and efficiency.

Our AI journey: experimentation and early adoption

Over a year ago, we developed the ambitious plan to integrate GenAI into our workflows. This wasn’t a passive exploration but a deliberate, hybrid approach, combining top-down vision setting with bottom-up experimentation. We tasked ourselves with solving specific design challenges using AI, discovering its capabilities.

The results were transformative. We developed tools like Mosaic, which generates illustrations aligned with Grab’s visual language. What once took an illustrator an entire day now takes just 15 seconds. Mosaic generates around 800 illustrations daily, scaling creative output across Grab’s teams while maintaining brand consistency. From icons to lifestyle photography, Mosaic continues to evolve, proving the scalability of AI-driven solution

Mosaic also redefined the role of illustrators within Grab. Instead of spending hours on manual tasks, our illustrators now focus on crafting detailed prompts and refining outputs; a shift that underscores the importance of adaptability and craft skills in the age of AI.

AI in prototype design

Beyond the tools we created in-house, we also explore the latest AI solutions in the market to keep up with innovation, for example, Agentic AI Coding tools with state-of-the-art models. These platforms are smart code editors that use AI to autonomously assist with various coding tasks.

We use them to build functional prototypes, one of which is our patent-pending Merchant Assistant, an AI-powered chatbot inside the Grab Merchant app. Merchants on Grab interact with this chatbot to get real-time advice related to their business performance.

For this use case, the agentic tools enabled rapid prototype development with LLM (Large Language Model) integration, allowing us to simulate realistic Merchant-Grab interactions within the prototype. In other words, designers can now quickly create interactive prototypes with authentic logic, navigation, form validation, and mock data—unlocking new efficiency in user experience design workflows.

AI in user research

Another area we found relevant use cases for GenAI is in user research. Our experiments yielded promising results. Early tools we developed specialised in tasks like usability testing (UT) script generation and prototype analysis, identifying usability issues with remarkable accuracy. More advanced tools now tackle foundational market research, producing insights comparable to traditional research agencies at a fractional cost.

However, these tools are not without limitations. AI models are trained on historical data, making them less effective at predicting future trends or understanding user sentiment toward emerging technologies. This underscores the importance of critical evaluation and human judgment in leveraging AI effectively.

Shifting roles in design

Which brings us to the next point: Adopting AI comes with its own challenges.

One critical skill we’ve learned to prioritise is prompt writing: the ability to craft precise and effective instructions for AI tools. Writing prompts is both a skill and an art, and its mastery can significantly impact the quality of AI-generated outputs. For example, illustrators using Mosaic often produce superior results compared to untrained users, highlighting the importance of domain expertise.

Fundamental design skills like problem-solving, strategic thinking, and aesthetic judgment remain essential, even with AI integration.

AI has shifted our roles as designers, emphasising adaptability and judgment over traditional “pixel pushing”. Designers must now focus on leveraging AI tools to achieve a faster feedback loop with high-quality results, a shift that has profound implications for how we hire and build teams.

We prioritise hiring adaptable individuals who embrace change and fluidity in their roles and are willing to acquire new skills. This mindset is essential in an AI-driven environment where tools and workflows evolve rapidly. For instance, many of the GenAI tools used within Grab’s design team were developed internally, requiring little in-house or external engineering resources. The ability to critically evaluate AI outputs for quality and relevance, and to refine the tools that generate them, is now a cornerstone of modern design.

Lessons for the industry

Being at the forefront of AI adoption is an advantage in today’s employment landscape. We’re hearing from new design hires that they’re intrigued and excited by the opportunity to make use of the state-of-the-art GenAI tools available and developed here at Grab. They see it as a way to upskill themselves, and to become part of a design organisation that’s setting a global benchmark.

As AI continues to reshape industries, our journey serves as a blueprint for how teams can thrive in an AI-driven environment. The future of design isn’t about resisting change: we can take an active role in shaping it. And at Grab, we’re proud to be leading the charge.

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