Navigating the Promise and Pitfalls of AI | Figma blog | Figma Blog

AI’s promise is real, but useful AI products will emerge through experimentation rather than a race to ship features. Figma’s research suggests AI is already transforming individual workflows—especially for developers—while having a smaller effect on collaboration and foundational design work. To deliver lasting value, teams must focus on how AI reshapes products, industries, and group work, not just on model capabilities.

Research and Methodology

• Figma surveyed more than 1,800 designers, executives, and developers.
• Participants came from the US, Canada, Australia, the UK, Japan, France, and Germany.
• The survey ran from February 26 to March 3, 2024.
• The report combines survey findings with discussions involving AI and design experts.
• Its central premise is that AI’s impact depends heavily on product design and user experience—not only on the power of large language models.

AI’s Uneven Transformation of Workflows

• Developers were 60% more likely than designers to say AI had transformed the products they work on.
• Developers use AI for daily tasks such as generating starting points and translating between programming languages.
• AI-generated output is currently perceived as more reliable for developer workflows.
• Designers may use AI to turn mockups into code, but much of design’s foundational work still involves:
  • Understanding user needs
  • Exploring problems nonlinearly
  • Learning about the broader problem space
• AI initiatives increasingly originate outside design, with programmers, subject-matter experts, and stakeholders contributing ideas.

AI Must Improve Collaboration, Not Just Individual Productivity

• Eighty-five percent of respondents said AI had affected their personal productivity or workflows.
• Common uses include text and image generation, brainstorming, and using AI as a sounding board or thought partner.
• Respondents were three times more likely to report significant changes to individual workflows than to collaborative ones.
• AI has not substantially changed group activities such as alignment or meeting facilitation.
• Truly transformational AI products will need to support how teams work together, rather than focusing only on isolated tasks performed by individuals.

Long-Term Effects Across Industries

• Respondents in technology, professional and business services, and retail most often expected significant AI-driven changes to their products and services:
  • Technology: 41%
  • Professional and business services: 40%
  • Retail: 39%
• Healthcare, energy and utilities, and telecommunications respondents expected the least impact over the following 12 months.
• The report argues that realizing AI’s full potential requires considering how major institutions and essential services—not just software products—will evolve.

Experimentation Before the Product Race

• AI development is still characterized by experimentation, play, and research.
• Teams face pressure to release new AI features quickly as new products, applications, and research appear constantly.
• The recommended approach is to embrace uncertainty, iterate thoughtfully, and determine which ideas genuinely create value.
• As the technology matures, the most successful products will likely come from careful exploration rather than simply adding AI features because of market hype.