Key Insights for 2025 on AI Adoption, Agentic AI, and Design Trends from Figma's Report

Last year, Figma's inaugural AI report suggested a "pivotal" moment as AI hype peaked. Now, a year later, the industry still grapples with similar questions. With cheaper, accessible foundational models, competition is fierce, pushing product teams to rapidly adopt AI and ship AI-powered features. Let's see what Figma's 2025 AI report revealed.

Key Takeaways

• AI product adoption is rapidly increasing, especially Agentic AI.

• Agentic AI automates complex multi-step tasks, making it highly valuable. Learn about AI adoption strategies.

• Design and iteration are critical for successful AI products.

• Smaller companies lead in AI adoption due to agility. Smaller companies are going all in.

• There is a perception gap between developers and designers on AI quality.

• Trust in AI output is still low, but AI is seen as essential for future success.

AI Product Development and Design: Key Insights from Figma's 2025 AI Report

This year, a survey of 2,500 Figma users revealed that one in three are launching AI-powered products—a 50% increase. These products range from predictive maintenance analytics to medical document interpretation.

Here are five key takeaways from the report, highlighting the current state of design and development in the age of AI.

The Rise of Agentic AI

Agentic AI is the fastest-growing product category. While text generation is common, agentic AI is booming: twice as many Figma users are building agentic products compared to last year. Unlike simple text or image generators, agentic AI tools handle multi-step processes. Their appeal lies in automating monotonous tasks, cutting costs, and accelerating business operations. Learn about AI adoption strategies to stay ahead.

What is Agentic AI you ask, and why is it becoming such a pivotal topic in the realm of artificial intelligence and technology? Agentic AI refers to AI systems designed to autonomously perform multi-step tasks by understanding, reasoning, and acting upon user input. This capability makes them significantly more powerful than simple content generators. The ability of Agentic AI to automate complex workflows and substantially reduce human effort is the primary reason for its rapid growth and increasing importance in AI product development.

The Challenges of Agentic AI

However, agentic AI tools pose unique challenges. Unlike content-generating tools, agents digest, reason, and act on user input. Developers must decide when an agent should consult a user, how much to share, and the best interface format—chat or button commands. These decisions demand critical thinking, testing, and prototyping expertise from both designers and developers.

Success in AI product development requires a flexible approach to best practices. Human knowledge and analytical reasoning are crucial. 52% of AI builders consider design more critical for AI-powered products than traditional ones, with 95% agreeing it's at least as important. Company leadership concurs.

Iteration and Collaboration are Key

The data confirms the value of iteration, rapid prototyping, and tight collaboration. Successful teams understand that iteration is key—60% explored multiple design or technical approaches, compared to only 39% of unsuccessful teams. Those who viewed generative AI product creation differently from non-AI products were more likely to succeed. As one respondent noted, it's like running a restaurant with a daily-changing menu. This dynamic requires skilled human input and industry knowledge.

As companies invest in intuitive AI tools, thoughtful design becomes a key differentiator in a crowded market.

We are often thinking about how much we explain about what is happening behind the scenes, and how we design for AI assisted actions with a human in the loop.

UK-based designer at a mid-market professional services company.

Small Companies Lead the Way in AI Adoption

While companies of all sizes see generative AI as vital for revenue and market share, smaller companies are more eager to fully embrace AI products. The proportion of Figma users at small companies who see AI as essential has doubled since last year. Companies with fewer than ten employees are building and integrating AI more readily, possibly due to their agility and the belief that AI can rapidly accelerate growth, justifying deeper investment.

The Perception Gap Between Developers and Designers

AI adoption is deepening across workflows, but there’s a quality perception gap between developers and designers. While both groups recognize the importance of AI, developers report higher satisfaction (82%) and perceive greater quality improvement (68%) compared to designers (69% satisfaction, 54% quality improvement).

67% of developers say that AI improves the quality of their work, while only 54% of designers say the same.

This divide stems from how AI supports existing work: 59% of developers use AI for core tasks like code generation, while only 31% of designers use it for core design work like asset generation. AI's code generation capabilities are a factor—68% of developers use prompts to generate code, with 82% satisfied with the output. Developers find AI more useful in their daily work, while designers are still exploring its best applications.

The future is AI—but how do we get there? 78% of those surveyed agree that “AI significantly enhances the efficiency of my work,” but only 32% say they can rely on the output of AI in their work.

Looking Ahead: The Future of AI in Product Development and Design

Looking ahead, AI's expected impact remains moderate, with AI projects still accounting for a minority of work: only 20% of designers and developers say that the majority of their projects are powered by AI. Quality perception is also a concern: only 32% trust AI's output.

AI builders report a lack of clarity in project goals, with only 9% citing revenue growth as the top priority and 76% focusing on vague aims like “experimenting with AI” or “improving customer experience,” making it difficult to measure impact.

More than 80% of both designers and developers say learning to work with AI will be essential to success in their role in the future.

Despite these challenges, there's a consensus that AI will be essential in the future of product development. While uncertainties exist, this shared vision points to a future where AI integration is inherent and natural. The specifics of this future depend on leaders' ability to leverage AI's potential while valuing human skills and expertise.

Despite AI's growing usage and capabilities, uncertainties and contradictions persist. To navigate this evolving landscape, explore our full report for insights into the promises and open questions. Seven purple mangos is busy with seeing how AI can be incorporated in the design flow, not for final designs, but to make the briefing and feedback flows more efficient for us and our clients. Want to read the complete Figma article? Check it out here.

If you're interested in how branding and marketing intersect in the digital age, check out our post on branding vs marketing.

FAQ

What are the key benefits of adopting AI in product development?

AI adoption can lead to increased efficiency, automation of repetitive tasks, improved decision-making through data analysis, and enhanced customer experiences through personalized features.

What is Agentic AI, and why is it important?

Agentic AI refers to AI systems that can autonomously perform multi-step tasks by understanding, reasoning, and acting upon user input. It's important because it can automate complex workflows and significantly reduce human effort.

What are some effective AI adoption strategies for businesses?

Effective strategies include starting with clear goals, prioritizing projects with measurable impact, fostering collaboration between designers and developers, and continuously iterating based on user feedback and performance data.

What are the main challenges in developing AI-powered products?

Challenges include ensuring data quality, addressing ethical concerns, managing user expectations, and bridging the perception gap between developers and designers regarding AI's impact on product quality.

How can companies measure the success of their AI initiatives?

Success can be measured by tracking key performance indicators (KPIs) such as revenue growth, customer satisfaction, efficiency gains, and cost reductions. It's also important to monitor user engagement and gather feedback to assess the overall impact of AI-powered features.

Looking for expert design work for your AI-powered products? Seven Purple Mangos specializes in creating intuitive and engaging user experiences for AI applications. Contact us today to learn how we can help you bring your AI vision to life with professional design services.