May 10, 2025
How AI Is Disrupting Design Software, Not Designers
AI
UX Design
AI Tools
Shifting priorities
Is AI Making UX Design Better? A Look at How Design Tools Are Changing
In my recent experience, I've seen a clear divide between how younger creatives and seasoned designers approach design tools today. Younger users lean heavily on AI-powered, browser-based apps that are fast, cheap, and intuitive—tools that let them jump right in without a steep learning curve. Meanwhile, many experienced designers still swear by traditional software suites that come with a price tag, a download, and a hefty commitment to mastering complex features. The thing is, AI isn’t so much replacing designers as it is quietly disrupting the tools themselves, and that shift is changing how design work happens at its core.
AI models are faster to adopt, cheaper, and way easier to get started with compared to traditional design programs. And because AI development is so competitive and fast-moving, companies are constantly pushing new features at a pace we haven’t seen before.
Take Adobe Firefly, for example. When it was announced last year, many expected it to revolutionize design apps like Photoshop. But by the time Adobe rolled out Firefly in the official 2025 release, it already felt a step behind. Midjourney and other AI platforms had moved ahead with editing and retexturing features that Adobe hadn’t caught up to yet.
Then there’s pricing and accessibility. Adobe keeps raising prices, and their software still requires hefty downloads and installations. Meanwhile, a lot of AI-powered tools run right in your browser—no downloads, no huge files. This convenience can’t be underestimated, especially for casual creators or those who want to experiment quickly without a long setup.
On top of that, the learning curve for traditional design software is steep. It takes time to become proficient, which is a real barrier of entry for many. Instead, people are turning to AI tools like ChatGPT for the heavy lifting on ideation and reasoning, then jumping to AI image generators to quickly create visuals.
I jokingly started calling this phenomenon the 'the canva-ification' of creative platforms. Tools like Fable, Canva, Descript, and Runway offer canvas-style UIs that merge design, writing, and production into single workflows, all while offering users ways to start from the ideas and assets made by others. They don’t require switching between apps, exporting between tools or even looking for references elsewhere. Everything is built for flow—from idea to result.
The New Design Stack
The New Design Stack
How AI Platforms Are Setting New Interaction Standards
AI-native platforms are beginning to influence interface design in ways that challenge long-established paradigms. Tools like Notion AI, Perplexity, and Kling are not merely integrating AI—they are rethinking how users interact with complex systems. Their interfaces tend to favor clarity, immediacy, and guided control over dense menus or rigid workflows.
Rather than relying on traditional hierarchies of navigation, many of these platforms introduce non-linear interaction patterns. Context-sensitive panels, inline editing, and visual feedback loops help users explore AI capabilities with less friction and greater confidence. The result is a more intuitive interaction model that reduces cognitive load and increases trust in the tool.
Some mainstream apps have attempted similar integrations. Spotify’s DJ feature, for instance, uses generative AI to curate audio experiences. However, its reception has been mixed—highlighting the fact that simply embedding AI is not enough. The interface must still communicate clearly, remain responsive to user input, and avoid overstepping perceived user control.
In contrast, successful AI platforms expose just enough of the model’s behavior to let users understand and shape outcomes. This transparency isn’t just good UX—it’s a new kind of interaction grammar, one that invites exploration while preserving clarity.
These patterns suggest that AI’s most enduring contribution to design might not be in automation, but in the creation of novel, more responsive user experiences.
The Near Future
The Near Future
Will Legacy Tools Move Faster than AI?
One thing that’s hard not to notice is how quickly AI design platforms evolve. Tools like Runway, Leonardo, Uizard, and Krea are rolling out new features every few weeks. The velocity is part of their appeal: users give feedback, and the product actually changes. Contrast that with the release cycles of established design suites—where big updates often arrive annually and adoption takes even longer.
This new generation of tools emphasizes co-creation, quick iteration, and minimal setup. They’re built around the assumption that users don’t always want to “design” in the traditional sense—they want to explore, test, prompt, revise, and keep moving. And this is starting to blur the line between technical tools and creative interfaces.
That doesn’t mean traditional software is going away, but it may be recast as a kind of backend—something used for final polishing, complex workflows, or legacy compatibility. In many workflows, especially for those new to the field, the browser-based AI platforms are becoming the default frontend.
If the design ecosystem continues evolving at this pace, the biggest question for established players might not be “how do we add AI?” but “how do we rethink the entire model?” Because for a growing number of users, the most powerful design tool might just be the one that requires no setup or cost at all.
Latest Updates
(EC — 02)
©2024
Latest Updates
(EC — 02)
©2024
May 10, 2025
How AI Is Disrupting Design Software, Not Designers
AI
UX Design
AI Tools
Shifting priorities
Is AI Making UX Design Better? A Look at How Design Tools Are Changing
In my recent experience, I've seen a clear divide between how younger creatives and seasoned designers approach design tools today. Younger users lean heavily on AI-powered, browser-based apps that are fast, cheap, and intuitive—tools that let them jump right in without a steep learning curve. Meanwhile, many experienced designers still swear by traditional software suites that come with a price tag, a download, and a hefty commitment to mastering complex features. The thing is, AI isn’t so much replacing designers as it is quietly disrupting the tools themselves, and that shift is changing how design work happens at its core.
AI models are faster to adopt, cheaper, and way easier to get started with compared to traditional design programs. And because AI development is so competitive and fast-moving, companies are constantly pushing new features at a pace we haven’t seen before.
Take Adobe Firefly, for example. When it was announced last year, many expected it to revolutionize design apps like Photoshop. But by the time Adobe rolled out Firefly in the official 2025 release, it already felt a step behind. Midjourney and other AI platforms had moved ahead with editing and retexturing features that Adobe hadn’t caught up to yet.
Then there’s pricing and accessibility. Adobe keeps raising prices, and their software still requires hefty downloads and installations. Meanwhile, a lot of AI-powered tools run right in your browser—no downloads, no huge files. This convenience can’t be underestimated, especially for casual creators or those who want to experiment quickly without a long setup.
On top of that, the learning curve for traditional design software is steep. It takes time to become proficient, which is a real barrier of entry for many. Instead, people are turning to AI tools like ChatGPT for the heavy lifting on ideation and reasoning, then jumping to AI image generators to quickly create visuals.
I jokingly started calling this phenomenon the 'the canva-ification' of creative platforms. Tools like Fable, Canva, Descript, and Runway offer canvas-style UIs that merge design, writing, and production into single workflows, all while offering users ways to start from the ideas and assets made by others. They don’t require switching between apps, exporting between tools or even looking for references elsewhere. Everything is built for flow—from idea to result.
The New Design Stack
How AI Platforms Are Setting New Interaction Standards
AI-native platforms are beginning to influence interface design in ways that challenge long-established paradigms. Tools like Notion AI, Perplexity, and Kling are not merely integrating AI—they are rethinking how users interact with complex systems. Their interfaces tend to favor clarity, immediacy, and guided control over dense menus or rigid workflows.
Rather than relying on traditional hierarchies of navigation, many of these platforms introduce non-linear interaction patterns. Context-sensitive panels, inline editing, and visual feedback loops help users explore AI capabilities with less friction and greater confidence. The result is a more intuitive interaction model that reduces cognitive load and increases trust in the tool.
Some mainstream apps have attempted similar integrations. Spotify’s DJ feature, for instance, uses generative AI to curate audio experiences. However, its reception has been mixed—highlighting the fact that simply embedding AI is not enough. The interface must still communicate clearly, remain responsive to user input, and avoid overstepping perceived user control.
In contrast, successful AI platforms expose just enough of the model’s behavior to let users understand and shape outcomes. This transparency isn’t just good UX—it’s a new kind of interaction grammar, one that invites exploration while preserving clarity.
These patterns suggest that AI’s most enduring contribution to design might not be in automation, but in the creation of novel, more responsive user experiences.
The Near Future
Will Legacy Tools Move Faster than AI?
One thing that’s hard not to notice is how quickly AI design platforms evolve. Tools like Runway, Leonardo, Uizard, and Krea are rolling out new features every few weeks. The velocity is part of their appeal: users give feedback, and the product actually changes. Contrast that with the release cycles of established design suites—where big updates often arrive annually and adoption takes even longer.
This new generation of tools emphasizes co-creation, quick iteration, and minimal setup. They’re built around the assumption that users don’t always want to “design” in the traditional sense—they want to explore, test, prompt, revise, and keep moving. And this is starting to blur the line between technical tools and creative interfaces.
That doesn’t mean traditional software is going away, but it may be recast as a kind of backend—something used for final polishing, complex workflows, or legacy compatibility. In many workflows, especially for those new to the field, the browser-based AI platforms are becoming the default frontend.
If the design ecosystem continues evolving at this pace, the biggest question for established players might not be “how do we add AI?” but “how do we rethink the entire model?” Because for a growing number of users, the most powerful design tool might just be the one that requires no setup or cost at all.
May 10, 2025
How AI Is Disrupting Design Software, Not Designers
AI
UX Design
AI Tools
Shifting priorities
Is AI Making UX Design Better? A Look at How Design Tools Are Changing
In my recent experience, I've seen a clear divide between how younger creatives and seasoned designers approach design tools today. Younger users lean heavily on AI-powered, browser-based apps that are fast, cheap, and intuitive—tools that let them jump right in without a steep learning curve. Meanwhile, many experienced designers still swear by traditional software suites that come with a price tag, a download, and a hefty commitment to mastering complex features. The thing is, AI isn’t so much replacing designers as it is quietly disrupting the tools themselves, and that shift is changing how design work happens at its core.
AI models are faster to adopt, cheaper, and way easier to get started with compared to traditional design programs. And because AI development is so competitive and fast-moving, companies are constantly pushing new features at a pace we haven’t seen before.
Take Adobe Firefly, for example. When it was announced last year, many expected it to revolutionize design apps like Photoshop. But by the time Adobe rolled out Firefly in the official 2025 release, it already felt a step behind. Midjourney and other AI platforms had moved ahead with editing and retexturing features that Adobe hadn’t caught up to yet.
Then there’s pricing and accessibility. Adobe keeps raising prices, and their software still requires hefty downloads and installations. Meanwhile, a lot of AI-powered tools run right in your browser—no downloads, no huge files. This convenience can’t be underestimated, especially for casual creators or those who want to experiment quickly without a long setup.
On top of that, the learning curve for traditional design software is steep. It takes time to become proficient, which is a real barrier of entry for many. Instead, people are turning to AI tools like ChatGPT for the heavy lifting on ideation and reasoning, then jumping to AI image generators to quickly create visuals.
I jokingly started calling this phenomenon the 'the canva-ification' of creative platforms. Tools like Fable, Canva, Descript, and Runway offer canvas-style UIs that merge design, writing, and production into single workflows, all while offering users ways to start from the ideas and assets made by others. They don’t require switching between apps, exporting between tools or even looking for references elsewhere. Everything is built for flow—from idea to result.
The New Design Stack
How AI Platforms Are Setting New Interaction Standards
AI-native platforms are beginning to influence interface design in ways that challenge long-established paradigms. Tools like Notion AI, Perplexity, and Kling are not merely integrating AI—they are rethinking how users interact with complex systems. Their interfaces tend to favor clarity, immediacy, and guided control over dense menus or rigid workflows.
Rather than relying on traditional hierarchies of navigation, many of these platforms introduce non-linear interaction patterns. Context-sensitive panels, inline editing, and visual feedback loops help users explore AI capabilities with less friction and greater confidence. The result is a more intuitive interaction model that reduces cognitive load and increases trust in the tool.
Some mainstream apps have attempted similar integrations. Spotify’s DJ feature, for instance, uses generative AI to curate audio experiences. However, its reception has been mixed—highlighting the fact that simply embedding AI is not enough. The interface must still communicate clearly, remain responsive to user input, and avoid overstepping perceived user control.
In contrast, successful AI platforms expose just enough of the model’s behavior to let users understand and shape outcomes. This transparency isn’t just good UX—it’s a new kind of interaction grammar, one that invites exploration while preserving clarity.
These patterns suggest that AI’s most enduring contribution to design might not be in automation, but in the creation of novel, more responsive user experiences.
The Near Future
Will Legacy Tools Move Faster than AI?
One thing that’s hard not to notice is how quickly AI design platforms evolve. Tools like Runway, Leonardo, Uizard, and Krea are rolling out new features every few weeks. The velocity is part of their appeal: users give feedback, and the product actually changes. Contrast that with the release cycles of established design suites—where big updates often arrive annually and adoption takes even longer.
This new generation of tools emphasizes co-creation, quick iteration, and minimal setup. They’re built around the assumption that users don’t always want to “design” in the traditional sense—they want to explore, test, prompt, revise, and keep moving. And this is starting to blur the line between technical tools and creative interfaces.
That doesn’t mean traditional software is going away, but it may be recast as a kind of backend—something used for final polishing, complex workflows, or legacy compatibility. In many workflows, especially for those new to the field, the browser-based AI platforms are becoming the default frontend.
If the design ecosystem continues evolving at this pace, the biggest question for established players might not be “how do we add AI?” but “how do we rethink the entire model?” Because for a growing number of users, the most powerful design tool might just be the one that requires no setup or cost at all.