5 powerful ways to supercharge your AI team for creative success in 2025 | Inspired by Figma’s fresh report

A New Era of Digital Creativity

In 2025, the world of design is entering a new era. Just a few years ago, AI in animation and design seemed like a futuristic concept with uncertain potential. Today, it’s becoming a full-fledged partner in the workflows of designers, illustrators, and UX professionals. According to the newly released Figma’s 2025 AI Report, artificial intelligence in the creative industry is no longer an experiment – it’s a widespread strategy for many companies aiming to stay competitive and grow their market share.

AI is being integrated particularly actively into digital art – from generative AI for visual storytelling to advanced user behavior analytics. Artists are no longer just crafting compositions by hand; they’re now also crafting prompts for generative models, refining outputs to match a brand’s identity, and automating tasks that once took hours using AI-powered design tools.

A striking example of AI’s growing role in the creative industry comes from Toys “R” Us. In a historic move, the brand became the first third-party company to produce a full commercial using OpenAI’s Sora. This advanced generative video model enabled Toys “R” Us to vividly reimagine a young Charles Lazarus, the company’s founder, interacting with the beloved mascot Geoffrey the Giraffe in a beautifully rendered 1930s setting.

The video, generated entirely from text-based instructions, showcases Sora’s ability to create complex, realistic scenes with multiple characters – pushing the boundaries of what’s possible in AI-driven storytelling and brand communication.

This bold experiment highlights how AI can deepen a brand’s narrative potential, delivering emotionally resonant, immersive content that bridges historical legacy with modern technology. By leveraging Sora, Toys “R” Us not only embraced innovation but positioned itself as a pioneer at the crossroads of creativity and AI.

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But how exactly is the creative workflow changing? Which practices remain effective, and what needs to be reimagined? And why do smaller teams often lead the way in adopting AI-powered tools?

In this article, we’ll explore the latest insights from Figma’s report, analyzing key trends, statistics, and practical advice for designers who aim not just to “keep up,” but to help shape the future of animation and design.

AI in Design: A Breakthrough in One Year

The year 2025 marks a sharp acceleration in the adoption of artificial intelligence in design workflows. According to Figma’s data, the share of users who have already launched products with AI-generated content rose from 22% in 2024 to 34% in 2025. That’s nearly a third of all respondents – a strong indicator of how quickly new technologies are being embraced across creative industries.

AI adoption in design workflows rose from 22% in 2024 to 34% in 2025, according to Figma.

An even more striking fact: 56% of surveyed companies reported that they have integrated AI animation software into their existing products. This goes beyond R&D experiments – it’s a large-scale adaptation aimed at real, day-to-day business needs. Companies are beginning to view AI not as a future innovation, but as a powerful tool for addressing current challenges: automating routine tasks, personalizing experiences, and accelerating time-to-market.

In the design context, this means that interfaces, prototypes, and visual content are increasingly crafted not entirely from scratch, but with the help of AI tools tailored for designers and animators. While creativity firmly remains in human hands – it’s the designer who formulates the prompts, curates the outcomes, and makes final decisions – overall team productivity grows substantially.

A compelling example of this hybrid approach comes from Adidas. To promote its new “Floral” collection, the brand leveraged several advanced AI technologies to streamline production and enhance visual impact.

• RunwayML was used for dynamic animation effects,
• Midjourney generated intricate floral visual motifs, and
• Topaz AI Upscaler ensured high-resolution output suitable for various digital platforms.

By combining these tools, Adidas was able to rapidly create and adapt campaign visuals across channels while maintaining both aesthetic quality and strong audience engagement. This reflects a broader trend: AI is not replacing creativity – it’s amplifying it.

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Such use of AI not only saves time and resources in content creation but also enables brands to produce original and personalized content that effectively attracts new customers. Adidas, like many other brands, demonstrates how AI can be a strategic tool for achieving marketing goals, allowing the brand to retain creativity while rapidly generating and adapting video content for different audience segments.

Design Becomes a Strategic Discipline

In the new design reality, the role of the artist or UX specialist has shifted dramatically. According to 52% of respondents in Figma’s report, design in AI-powered products is even more important than in traditional digital solutions. This is due to the nature of AI: instead of clear-cut user flows, people interact with systems that make decisions autonomously. Such interactions must be intuitive, ethically transparent, and controllable – and design becomes the bridge that connects algorithms with user expectations.

New interfaces are often built around chat interactions, recommendations, or agent-based logic – meaning the product “acts” either on behalf of the user or alongside them. In this context, design is no longer a decorative layer – it becomes the architecture of behavior, something that must be anticipated, structured, and explained.

Traditional practices such as UX research, fast iteration, and deep collaboration with dev teams remain relevant. But they are no longer enough. Emerging technologies demand adaptability: designers must be ready to restructure products on the fly in response to changes in the tech platform or user expectations.

The success of today’s AI-powered creative workflows depends not so much on how “smart” the model is, but on how well design frames its capabilities and conceals its flaws. This is the new strategic role of design in product development.

Agentic AI: The New Favorite Among Digital Teams

One of the key technology trends of 2025 is the rapid rise of agentic AI – autonomous systems capable of acting independently without constant user oversight. According to Figma, the share of designers working with agentic AI rose from 21% in 2024 to 51% in 2025. This is the fastest growth among all types of AI solutions.

The share of designers using agentic AI jumped from 21% in 2024 to 51% in 2025 – the fastest-growing AI trend, according to Figma.

Agentic AI is not just about tools that generate content – it’s about virtual agents capable of completing multi-step tasks: organizing information, making decisions, and communicating with users. For designers, this is a new paradigm. It’s no longer enough to design a button or a form – they must now design agent behavior, define boundaries of autonomy, ensure transparency, and create interfaces for explanation and trust.

This raises essential questions: How much control should the user retain? When should the agent ask for confirmation, and when should it act independently? Should users see the agent’s decision-making logic, and in what form? These are not just technical questions – they are AI-assisted design questions.

That’s why agentic AI opens a vast field for UX researchers, interface designers, and product strategists. These systems add complexity – but also dramatically expand the product’s potential. And those who learn to work with them today will gain a significant advantage tomorrow.

Why Small Teams Lead the AI Race

One of the most intriguing findings of the report is that small companies with fewer than 10 employees are the most active AI adopters. 61% of respondents from such teams believe AI is critically important for expanding market share. That’s nearly three times more than mid-sized companies and almost twice as much as large organizations.

The reason lies in their agility and lack of bureaucracy. Small teams can launch an experimental product within weeks, test a hypothesis, gather feedback, and quickly adapt the process. The growth in AI-related investments confirms this dynamic: AI research increased from 29% to 41%, staff training from 30% to 40%, and AI specialist hiring from 18% to 20%.

AI-related investments grew sharply: research rose from 29% to 41%, staff training from 30% to 40%, and AI specialist hiring from 18% to 20%.

The Design–Development Tandem: A Key to Success in AI Projects

One of the most crucial factors in successfully launching AI products is close collaboration between designers and developers. According to the report, 75% of high-performing teams confirmed that they worked closely together at every stage of product development. This collaboration includes not only exchanging ideas but also joint work on prototypes, validating hypotheses, and aligning interface architecture.

Creative workflow automation plays a particularly important role. AI for motion graphics, UI logic, and interactive behavior requires continuous iteration. Teams that skipped deep iteration phases often faced low user engagement or non-functional user experiences.

AI as an Analytical Tool: Rethinking the Creative Process

Although AI is commonly associated with automatic image or text generation, the data reveals a shift in how it’s being used. 43% of developers and 38% of designers now use AI for desk research – conducting background studies, competitor analysis, and collecting statistics. Additionally, 40% of designers turn to AI for analyzing user data, helping them better understand audience behavior.

This highlights that AI in the creative industry is no longer just a matter of intuition – it’s driven by insights. Designers are becoming researchers, analysts, and strategists. While text (67%) and image generation remain core use cases, analytical applications are becoming the foundation for deeper AI impact within teams.

Vague Goals: The Main Obstacle to Scaling AI

Despite the active adoption of AI, many teams struggle to clearly define the problem they are solving. In the study, 40% of respondents cited “improving user experience” as their main goal, 35% said “AI experimentation,” and only 9% focused on “increasing revenue.” This ambiguity complicates the setting of KPIs, measuring performance, and justifying investments.

This partly explains why only 15% of respondents consider AI to be transformational for business in the near term. While expectations are high, actual results often remain at the “let’s see if it works” stage. The absence of a systemic strategy limits the technology’s potential, reduces team engagement, and slows product development.

Most teams use AI to improve user experience (40%) or experiment (35%), while only 9% aim to increase revenue – which may explain why just 15% see AI as transformational.

Recommendations: How Teams Can Adapt to an AI-Driven Future

Integrating AI into workflows is not just a matter of technology – it’s about culture, mindset, and organizational structure. Figma’s 2025 report makes it clear: successful teams don’t simply use AI, they build a new operational logic around it. Below are key recommendations that can help transform not only your tools, but your entire approach to product design in the era of AI.

1. Think Like a Startup: Small Iterations, Big Results

In today’s fast-moving AI landscape, rigid long-term plans are becoming obsolete. Instead, teams should adopt a startup mindset: move fast, stay flexible, and validate ideas quickly. Launch minimum viable products (MVPs) using AI-powered tools, gather feedback, and only scale what proves to be effective.
This lean approach is especially effective when experimenting with AI in animation or AI-powered design tools, where early results provide real insights and help guide product evolution. Embracing fast iterations allows teams to avoid waste and stay ahead in a competitive, ever-changing environment.

2. Prototype Realistically: Iteration Takes on New Meaning

With AI-generated content, unpredictability is part of the process. That’s why realistic prototyping is essential: it helps identify edge cases, system weaknesses, and user confusion before launch.

Don’t rely on static visuals – prototype full AI flows, including varied user prompts, multiple AI responses, recovery scenarios, and potential failures. Especially in AI for motion graphics and interactive systems, such realism helps teams build trustable and adaptable experiences. Remember: a polished-looking prototype isn’t enough – functionality under pressure is key.

This emphasis on realism and practical application is already visible in real-world use cases.

In January 2025, for example, Google released a commercial for its new Pixel 9 smartphone titled “Dream Job”. Created entirely with artificial intelligence, the ad highlights how AI can assist with learning, task planning, and execution – perfectly aligning with the phone’s core promise of enhancing productivity.

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The production itself showcased two major applications of AI:

• AI-generated content: Realistic scenes and characters were created from simple text prompts, portraying everyday situations where the Pixel 9 helps users manage their tasks more efficiently.
• AI-driven scriptwriting: The storyline was also shaped by AI, which generated relevant and relatable scenarios for both work and personal life.

This innovative approach brought Google several key advantages:

• It reinforced the company’s position as a tech leader, seamlessly blending cutting-edge AI with creative storytelling.
• It enabled the creation of tailored, audience-specific content, enhancing the campaign’s resonance and reach.
• It successfully captured the attention of younger, tech-savvy audiences, positioning Pixel 9 as a forward-thinking device for modern life.

3. Learn Agentic AI: It’s Not the Future – It’s the Present

Agentic AI, which enables autonomous systems to take actions independently, is gaining massive momentum. According to Figma’s 2025 report, it shows the fastest growth among AI technologies. These agents aren’t just tools – they behave like intelligent collaborators.
For design teams, this means learning how to structure decision-making flows, transparency models, and user override options. It’s not only about UX anymore – it’s about shaping ethical, explainable systems. Mastering AI-assisted character design and interactive logic will become a superpower in your team’s creative arsenal.

4. Invest in Your Team: AI Is a Skill You Can Build

Adopting artificial intelligence in the creative industry isn’t just a technical shift – it’s cultural. To succeed, teams must build AI fluency the same way they once learned design tools like Figma or Sketch.

Organize monthly “AI knowledge sessions,” share real examples, and test emerging AI animation software together. This creates a shared vocabulary and helps eliminate fear around automation. Internal discussions about creative workflow automation make it easier to integrate AI tools for designers and animators into real processes.

5. Embrace Imperfection: Prioritize Speed Over Perfection

Perfect AI output is a myth – especially early on. The most successful teams accept this and use AI-generated content as a starting point, not a final product. Even rough drafts can save dozens of hours each week.

The goal is not to let AI replace creativity, but to enhance animation with AI, free up time, and focus on what humans do best: refinement, judgment, and emotional intelligence. Speed, iteration, and learning-by-doing are far more powerful than chasing perfection.

AI Design Is the Intersection of Creativity, Technology, and Strategy

The year 2025 marks a turning point in digital design. The designer’s role is shifting from visual creator to architect of interaction systems between humans and intelligent machines. AI doesn’t replace designers – it unlocks new opportunities to better understand users, work faster, and think more systematically.

While large companies often hesitate due to complexity and scale, it’s small teams that are setting the pace. They test new formats, create breakthrough solutions, and show how to enhance animation with AI and integrate machine learning in animation into the creative process – without losing identity.