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Every day a new AI tool is born promising to revolutionize our habits. The software we use is filling up with intelligent features, social feeds are exploding with demos, and we, in all of this, need to understand what's really worth knowing and testing.
It's not easy to navigate a new world that's still evolving: between genuine hype and fleeting illusions, between tools that actually accelerate workflow and others that end up complicating it: a reasoned approach is needed.
That's why we thought of an overview that shines a light on what both the tech giants and the emerging names on everyone's lips are doing. To have a map that brings together all those tools that, in one way or another, will end up redefining how we think about and create design.
Why we're talking about AI revolution in the design world
This isn't the first time design has changed its skin, but this one has all the makings of a much deeper transformation. The arrival of Artificial Intelligence is revolutionizing the way we design. Not just for the speed at which we work, but for how we think about design, which phases of the process we can automate, and which still need human intuition, sensitivity, and experience.
This change is already reality and doesn't only concern experimental tools but the platforms we use every day, from Figma to Google, which integrate AI functionality directly into the workflow. And they're not just doing it to keep up, but because AI is really changing how we think, organize, and produce design.
We're in a totally open, exploratory phase, as if it were a big wild west. Some tools are in beta, others work in fits and starts, still others need to be trained, tested, adapted to your own context. But waiting isn't always the best strategy. Those who start exploring AI possibilities now can make more conscious choices, avoid the risk of chasing fleeting trends, and, above all, fine-tune a process that really works for their team.
Before moving forward, let's talk for a second about another topic that today more than ever is fundamental for a designer (and anyone working in the digital field) to know well: accessibility. We've created a white paper (in Italian) to help teams adapt and work with an accessible by design approach, save it for later!
AI for UX, or how to empower the designer and not replace them
If we had earned a cent every time someone asked us: "But will AI steal our jobs?", by now we could buy all of Silicon Valley.
Our short answer is: "No".
The designer's answer is: "It depends". It depends on how we choose to use it.
The truth though is that we're getting caught up in panic and if we thought more calmly the right question we should ask ourselves is: "How do we want AI to help us in our work?".
Because AI, if used critically, can really become our creative copilot. It should be the secret weapon to unblock us when we're stuck, to show us alternatives, to help us see more clearly in chaos, not to take our place.
Imagine it as a colleague always in a good mood and available for brainstorming, suggesting a structure or helping you order your thoughts. And yes, also for taking on the most boring activities like transcribing, summarizing interviews, extracting insights or generating a wireframe skeleton. But deciding the direction, giving meaning and coherence, making the choices that matter always remains with flesh-and-blood people.
This is exactly what's happening in the development world. The arrival of tools like GitHub Copilot hasn't replaced coders but has made their work faster and more productive. This is what's now called vibe coding**, whose mantra states: less repetitive code and more creative problem solving.** Similarly, in design, we're witnessing the birth of its natural parallel, vibe designing which could be translated as less pixel pushing and more strategy.
The goal isn't to automate everything, but to enhance human ingenuity, free up time, create space for reflection and experimentation. AI can do a lot, but it still can't, and perhaps never will, replace the ability to read between the lines (especially of project briefs), to intuit people's deep desires, to imagine solutions where there aren't any yet.
ALSO READ: UX Developer: chi è e cosa fa? (Italian)
10 UX/UI AI tools that every design team should knowAI che ogni team di design dovrebbe conoscere
To discover AI tools with the greatest impact, there's no need to go far. All the big players in the sector are already integrating intelligent features directly into their products, gradually transforming our daily work.
These are no longer isolated experiments or plugins for tech enthusiasts: it's a profound change, because it's happening within workflows we already know. Behind familiar interfaces, there are already radical innovations.
Alongside the giants, platforms born for digital design that make AI their main leverage are emerging, but also hybrid tools that experiment right on the border between design and development. Here we're not talking about additional features, but tools built around AI from the beginning.
The Big Players: How AI Enters Everyday Tools
1. Figma AI
Figma didn't just integrate an AI assistant, it rethought the role of artificial intelligence in collaborative design. Today its ecosystem moves in three directions: accelerating creative flows, expanding automatic generation, and simplifying publishing.
Main features:
- FigJam AI: useful for automatic clustering of ideas, workshop summaries, creating mind maps and auto-layout for collaborative boards.
- Figma Make: is one of the most promising innovations. It allows you to create UIs and complete flows starting from text prompts, using existing components and logic.
- Figma Sites (in rollout): born to generate responsive landing pages starting from content present in the file, optimizing layout and structure for web publishing. In its current state, the code underlying the generated design isn't exactly optimized and accessible, but improvements are constant.
Ideal for: UX/UI designers who want to move faster from wireframe to prototype, distributed product teams working iteratively on shared boards, and content designers or marketing managers who need to quickly validate layouts and landing pages.
In our talk dedicated to AI's role as the designer's copilot (in Italian), we illustrate the entire process in Figma to move from the wireframing phase, to defining the design system library, to generating a prototype. A realistic example of effective use of artificial intelligence's generative functionality, supervised and governed by the expert hand of a designer.
2. Adobe Firefly & Sensei
Adobe has chosen a systemic approach: AI becomes part of the creative flow, reducing the distance between the initial idea and the final output of assets. The integration is designed to enhance human work, not replace it, and is guided by the logic of helping designers and creatives realize complex ideas faster, without sacrificing quality or visual coherence.
Firefly works on generating images, effects, graphic elements and branded styles from text prompts. Sensei instead optimizes and speeds up with automatic selections, intelligent crops, assisted fills and colorings. Together they form a pair that covers the entire flow, from experimentation to execution.
Main features:
- Adobe Firefly: now an integral part of Photoshop and Illustrator, generates images, vector elements, effects and branded styles from text prompts. It was trained on Adobe Stock to ensure commercially safe outputs.
- Adobe Sensei: AI system that powers functions like intelligent object removal, automatic selections, composition and color suggestions. Includes Firefly-powered technologies like Generative Fill for image modifications via text prompts and Generative Recolor for rapid colorings of vector works.
Ideal for: visual designers and art directors creating original and branded assets, graphic designers managing color variants and revisions in rapid times, and creative teams that need to maintain visual coherence across campaigns, sites, and multiplatform materials.
3. Google Workspace AI
Google has transformed its productivity suite into an AI-powered ecosystem that supports every phase of the design process. Under the Gemini umbrella and with experimental projects from Google Labs, tools are multiplying to support research, analysis, writing, and prototyping.
Main features:
- NotebookLM: AI research notebook for synthesis and insights from documents and multimedia content (texts, PDFs, audio), ideal for summarizing and organizing large quantities of content, like user interviews, or doing competitive analysis.
- Gemini AI for Workspace: integrated assistant in Gmail, Docs, Sheets, Slides, Chat and Meet that helps with writing, brainstorming, summaries, visual generation and collaboration in daily workflow.
- ImageFX (currently not available in Italy): image generator for moodboards and visual prompt-driven. Let's not forget technologies like Nano Banana (image editing via prompt) and Veo3 (video generation), which complete Google's offering.
- Stitch (in beta): experimental tool for rapid prototyping, to go from prompt to UI in a flash.
- AI Studio: Google's free web platform that includes various technologies, models and AI tools and includes advanced features. It allows you to explore and develop prompts with Gemini models, test creative ideas and generate text, code or images starting from personalized prompts.
Ideal for: UX teams doing user-centric research, designers or product managers who need to prototype quickly, create visual assets, manage large quantities of content or documents, and make collaboration super fluid.
In our talk, we offer a concrete example of how AI supports the designer in the Discovery phase. With the support of NotebookLM, as well as a good dose of prompt engineering, it's actually possible to synthesize a large quantity of information (reviews, interviews, analytics, raw data), elaborate mindmaps that help exploration, generate complete reports to share with the team and client.
4. Microsoft Copilot
Microsoft has integrated Copilot natively into the Microsoft 365 suite, offering AI features that support business workflows, between content production, automation and design.
Main features:
- Copilot in PowerPoint and Word: helps generate presentations from prompts or reference documents, rewrite texts, create intelligent summaries and apply consistent layouts.
- Microsoft Designer: tool for creating graphics and marketing assets with AI assistance, using templates, styles and visual/textual inputs.
- Power Automate with AI: allows building automated flows starting from natural language, diagnosing and repairing errors in workflows or adding generative actions in business processes.
Ideal for: enterprise teams, product managers and project managers who need to prototype presentations and internal documentation quickly but above all improve internal automation of recurring processes.
Vibe designing AND vibe coding: THE FUTURE IS HYBRID
If there's one point where design and development are really merging, this is it. New hybrid platforms are transforming text prompts, sketches and flows into real digital products, navigable, functional. Here AI isn't just support, it's the main tool to create, iterate, validate and publish faster.
5. Lovable
Lovable is a low-code platform designed for those who want to create functional web applications starting from a text description. Just a simple prompt and in a few seconds you have a first navigable draft, with interface, flows and interactions already ready to test.
The logic is "design while you build": perfect for projects in exploratory phase or for small teams that want to immediately understand if an idea holds up. Great for gathering feedback on something already tangible, without starting from scratch every time.
6. Replit
Born for those who write code, Replit today is an AI-powered playground perfect also for designers, strategists and those working in discovery. With Ghostwriter (its AI assistant), you can test components, try micro-interactions and explore alternatives in real time.
It's a highly collaborative tool for working with multiple hands on the same prototype, seeing what happens when you change something and receiving suggestions from the model. It's a bridge between those who design and those who develop, perfect for making tests without blocking the sprint.
7. Visual Studio Code
Visual Studio Code, now an indispensable editor for those who develop (even design-driven projects), today integrates powerful AI features thanks to GitHub Copilot and dedicated extensions. It's possible to generate, correct and document code starting from natural language prompts and receive real-time suggestions while working on UI and front-end flows.
Various integrations, like Figma to Code extensions or the use of MCP servers, allow transforming layouts and interfaces created in Figma directly into ready-to-use code, reducing times and error risks between design and development.
Among emerging alternatives, it's worth mentioning editors like Cursor and Windsurf, which follow the same AI-driven approach. They're ideal tools for teams collaborating between design and dev, and for those who want to automate the writing of UI components or quickly test new ideas starting from prototypes.
AI-powered VISUAL CMS
In recent years, new visual CMS have raised the bar by integrating AI to simplify and accelerate design, development and publishing of sites and applications. Platforms like Framer, Webflow and builder allow even those who don't write code to create, iterate and put online professional digital products, combining an evolved visual editor with AI components for layouts, copy, images and automations.
8. Framer AI
Framer AI is a tool designed to shorten the distance between concept and publishable result. With AI features you can generate complete layouts starting from text prompts, set visual hierarchies, animations, content and interactive elements in a few steps. Ideal for designers and teams who want to test ideas fluidly, explore alternatives without touching the code again and validate prototypes directly in the field.
9. Webflow AI
Webflow is establishing itself as the king of no-code for designers, and AI now adds another level. With Webflow AI you can ask for suggestions on layouts, texts, page structure. It's possible to modify elements in natural language and see the result in real time. Its real strength is in precision: the result isn't just a draft, but a base already ready to be published or refined by hand. Perfect for those who want to maintain visual control but lighten the more technical part.
10. Builder.io
Builder.io isn't a simple visual editor: it's an AI-powered visual development platform that unites design, code and content. Its AI engine, called Visual Copilot, intervenes in the existing flow, supporting designers and developers in automating the most mechanical parts, leaving them creative control.
What if we told you that even Drupal is AI-Driven?
When talking about hybrid platforms that merge design and development (the so-called vibe designing), it's easy to think of tools born in recent years. But AI innovation is also involving the most robust enterprise CMS platforms.
This is the case with Drupal, historically known for enterprise stability and scalability, as well as for its open-source nature, which is taking giant steps in integrating AI directly into the workflow, including those involving UX/UI. In other words, Drupal today offers designers a modern playground as much as other emerging tools. Let's see the main aspects.
Experience Builder and Component Generation
If the future of design is composable, AI must operate within clear rules. This is where Drupal's new Experience Builder (XB) comes in, a drag-and-drop visual editor that allows building interfaces and layouts by composing sections and components, embracing modern frontend technologies.
This is where the AI Assistant comes into play (in active development), which allows the designer to create entire templates from text prompts ("Create a homepage template for a university", "Create a product page to launch this new product", "Add a section with two paragraphs and a vertical slider of five images").
The most important point: AI doesn't invent code from scratch, but reuses and orchestrates Single Directory Components (SDC) already approved by the design system. This way, the output is always consistent, accessible and adherent to company standards.
In Drupal, AI doesn't replace the designer, but multiplies governance effectiveness, freeing up time from "pixel pushing" to focus on strategy and creativity (the real added value of designers).
Design System and Visual Coherence
A design system is the backbone of any scalable project (regardless of the AI factor). Drupal integrates natively with Storybook, the de facto standard for developing and documenting UI components (we talked about it here). This allows:
- Developing UI components in an isolated environment
- Guaranteeing the visual contract between designer and developer.
- Speeding up QA and prototyping.
- Always keeping the component library updated
To push automation further, specific AI-based addons for Storybook can help automatically generate documentation (stories) and quality tests and controls, ensuring that the entire component catalog (those that XB's AI will use to compose pages) is always updated and precise. An integration that, when it reaches full maturity, will transform GenAI's operational speed into governed and coherent output.
Drupal MCP Server
A perhaps less visible but truly revolutionary aspect is Drupal's ability to become a source of strategic context for LLMs. Thanks to support for Model Context Protocol (MCP) in fact, Drupal can expose its own data (content nodes, taxonomies, information architecture) as Resources and its own functions as Tools directly usable by external LLM models.
Translated into practice: an LLM can query in real time the structure of Drupal's contents to analyze user paths, suggest microcopy or CTA optimizations, or propose UX modifications based on the live and updated context of the site.
But Drupal MCP's possibilities look truly unlimited, allowing connection of tools and resources to AI agents in the most diverse processes, to the advantage not only of designers, but of many other business functions.
Drupal's AI features are really in continuous evolution: many functions are already available, some aspects are still in development, others are experimental, still others are only sketched. But the future is rosier than ever, with really tight development by an extremely dedicated and fierce community (SparkFabrik actively contributes too!).
How LLMs Can Support UX Strategy
When we think of AI tools for design, visual tools often come to mind. But Large Language Models (LLM) like ChatGPT and Claude are becoming fundamental allies also for those working on research, strategy and information architecture.
They don't design interfaces, but they can help think them better.
These models are particularly useful in the initial phase of the process, when you need to gather, rework and connect a lot of information often in tight times. Here are some concrete use scenarios:
- Analysis of usability heuristics: you can ask an LLM to evaluate a page or interface according to Nielsen's 10 principles. It doesn't replace a real UX review, but can help you do a first quick and reasoned check.
- Analysis of key user paths: feed it the site map or a user flow and ask for an analysis of possible frictions or weaker calls to action.
- Synthesis of user interviews or tests: when you provide transcripts, the model can help you summarize pain points, recurring insights and suggestions (as we did with NotebookLM in our talk).
- Writing and testing microcopy: you can rapidly iterate on interface texts (titles, CTAs, error messages) and evaluate tone and clarity alternatives.
- Support for UX documentation: generation of personas, use scenarios, flow descriptions, even just as a first draft to then refine by hand.
Even those who build AI, like the Anthropic team, use it every day to simplify their work. Claude, their language model, isn't only used to write code or generate texts, but also to do research, think about products, organize ideas.
In an internal document, the Anthropic team tells of using it to write UX project plans, reformulate value propositions, reorganize insights gathered in interviews and improve product documentation. A concrete example of human-AI collaboration that improves efficiency and strategic depth.
ALSO READ: UX Strategy: l’usabilità è al servizio del tuo brand (Italian)
How to introduce these tools in your team, strategically
The way we see it, AI shouldn't be a sprint to keep up with the latest trend to embrace at all costs, but an opportunity to rethink the way we collaborate, create, test. And to do it effectively requires a clear, shared and scalable strategy.
The most classic advice is also the most effective: start with a pilot project, perhaps internal or low-risk. Experiment in a controlled context, measure what works (and what doesn't), then expand adoption. AI can accelerate processes, but without a solid upstream system it risks creating only confusion. If you already have a well-structured design system (more details in our design system deep dive), use it as a guide to select and configure tools: components, naming, tone of voice and accessibility must remain consistent.
And then create sharing moments: adoption works better if it's participatory. It's important to leave space for individual experimentation, but also to plan moments when the team can compare what they've tried and discovered. AI is a new tool and company culture is also built this way: experimenting and talking openly together.
ALSO READ: Design system: guida strategica per coerenza, UX e accessibilità (Italian)
How we integrate AI Tools in our projects
To understand what really works you need to get your hands dirty. At SparkFabrik we do it in the field: we experiment on internal activities, test tools and processes and bring to client projects only what generates real value.
An example is EAA, a site dedicated to the European Accessibility Act. Here we used Replit to accelerate the cycle between design and development: create, test, improve. The site was designed to be accessible, readable and sustainable, and AI helped us reduce times without losing coherence with our design system.
Another interesting case is DrupalCamp Italy, created with Lovable to prototype and iterate while always keeping our designers' vision alive. And we emphasize that it's not a matter of "doing faster" but of testing a new way of working, more fluid, more collaborative, closer to how we imagine the design of the future.
In both cases it wasn't about replacing our work, but making it more fluid, fast and connected. Designing with our method, with our style.
If you're thinking of introducing AI tools in your workflows, we can help you do it the right way: starting from your priorities, respecting your processes, and choosing together what can really improve your team's daily work. Ask our Design Unit how you can walk in balance between method, creativity and technology.
