Spring 2026
·
Technology
AI Insights 2026
AI Insights 2026
Powered by AI, design's value is moving from production to direction and/from execution to judgment. AI 2026 Insights maps where this upstream motion is already underway, and what it demands from creatives next.
The gap between producing something and knowing why it works is where direction lives, in the act of design.
At this year’s SCAD AI Summit, one gap showed up consistently: the space between those who produce work and those who shape direction. Most classrooms and boardrooms still reward what gets produced, and how fast, but the real work happens earlier.
In 2026, SCADask surveyed 100+ leaders across design, tech, and enterprise to understand how AI impacts knowledge work, design workflows, and what barriers still exist with regard to adoption.
Where AI delivers the most efficiency gains
Emergence arrives at the edge of practice, in the friction of an outdated workflow, a word not yet invented, or the work-around that becomes the method.
Across all industries, research synthesis and content generation were identified as the highest-impact areas for AI adoption in 2026.
“You can’t apply AI to nothing. You need the disciplines themselves. Then you need to understand the frustrations they’re dealing with in order to apply AI to it.”
— Nye Warburton, Dean, School of Creative Technology, SCAD
AI Use in Creative Output
Generative AI pushes judgment upstream where decisions arrive before outputs.
Leading category
of practitioners use AI for concept visualization — the highest adoption across all tracked creative activities.
“Folks with the ability to leverage AI both in their day-to-day work and to build it into the products they work on — those skills come at a premium. We’re actually seeing the reverse of devaluation — having that capability actually increases their value.”
— Shaun Rance, Senior Design Director, Enterprise XD, Netflix
Where designers and industries adapt and restructure
Transformation appears in the gap between what designers assumed would stay and what has already given way, like a definition of craft that expanded or an ethical instinct that formed before the framework existed to name it.
of practitioners define their primary KPI for AI success as time saved.
“What AI is most helpful for is the very beginning — when you’re starting just to explore — or at the very end, a polish. But that middle part is actually where people’s voices and your own unique perspective come in.”
— CJ Jones (B.F.A., advertising, 2011), Head of Design for GenAI, Canva
Human skills growing in value
Generative AI strips away the production layer until what remains is unmistakably human.
Top human skill
Creative Direction
Identified as the human skill with the highest growing value as AI handles more production-layer tasks.
“What good design does is already changing — not what good design looks like. I think they’re two different things.”
— Karthik Narayan, Design Director, Amazon
Where design moves before the map exists
What surfaced consistently across the summit wasn’t prediction. It was direction — a shared recognition of where value is moving and what the field needs to claim before someone else does.
of respondents identify multi-agent orchestration as the emerging AI trend most likely to shape their industry, leading all categories.
“Unlike humans, who learn through embodied experience, exploration, and gradual growth, AI has no ‘childhood.’ [You] make AI practice, play, and improvise with humans by building AI that learns like a developing partner — not a perfect machine — and opens a huge, unexplored space for teaching, creativity, and skill-building.”
— SCADask survey respondent
The gap between producing something and knowing why it works is where direction lives, in the act of design.
At this year’s SCAD AI Summit, one gap showed up consistently: the space between those who produce work and those who shape direction. Most classrooms and boardrooms still reward what gets produced, and how fast, but the real work happens earlier.
In 2026, SCADask surveyed 100+ leaders across design, tech, and enterprise to understand how AI impacts knowledge work, design workflows, and what barriers still exist with regard to adoption.
Where AI delivers the most efficiency gains
Emergence arrives at the edge of practice, in the friction of an outdated workflow, a word not yet invented, or the work-around that becomes the method.
Across all industries, research synthesis and content generation were identified as the highest-impact areas for AI adoption in 2026.
“You can’t apply AI to nothing. You need the disciplines themselves. Then you need to understand the frustrations they’re dealing with in order to apply AI to it.”
— Nye Warburton, Dean, School of Creative Technology, SCAD
AI Use in Creative Output
Generative AI pushes judgment upstream where decisions arrive before outputs.
Leading category
of practitioners use AI for concept visualization — the highest adoption across all tracked creative activities.
“Folks with the ability to leverage AI both in their day-to-day work and to build it into the products they work on — those skills come at a premium. We’re actually seeing the reverse of devaluation — having that capability actually increases their value.”
— Shaun Rance, Senior Design Director, Enterprise XD, Netflix
Where designers and industries adapt and restructure
Transformation appears in the gap between what designers assumed would stay and what has already given way, like a definition of craft that expanded or an ethical instinct that formed before the framework existed to name it.
of practitioners define their primary KPI for AI success as time saved.
“What AI is most helpful for is the very beginning — when you’re starting just to explore — or at the very end, a polish. But that middle part is actually where people’s voices and your own unique perspective come in.”
— CJ Jones (B.F.A., advertising, 2011), Head of Design for GenAI, Canva
Human skills growing in value
Generative AI strips away the production layer until what remains is unmistakably human.
Top human skill
Creative Direction
Identified as the human skill with the highest growing value as AI handles more production-layer tasks.
“What good design does is already changing — not what good design looks like. I think they’re two different things.”
— Karthik Narayan, Design Director, Amazon
Where design moves before the map exists
What surfaced consistently across the summit wasn’t prediction. It was direction — a shared recognition of where value is moving and what the field needs to claim before someone else does.
of respondents identify multi-agent orchestration as the emerging AI trend most likely to shape their industry, leading all categories.
“Unlike humans, who learn through embodied experience, exploration, and gradual growth, AI has no ‘childhood.’ [You] make AI practice, play, and improvise with humans by building AI that learns like a developing partner — not a perfect machine — and opens a huge, unexplored space for teaching, creativity, and skill-building.”
— SCADask survey respondent
The gap between producing something and knowing why it works is where direction lives, in the act of design.
At this year’s SCAD AI Summit, one gap showed up consistently: the space between those who produce work and those who shape direction. Most classrooms and boardrooms still reward what gets produced, and how fast, but the real work happens earlier.
In 2026, SCADask surveyed 100+ leaders across design, tech, and enterprise to understand how AI impacts knowledge work, design workflows, and what barriers still exist with regard to adoption.
Where AI delivers the most efficiency gains
Emergence arrives at the edge of practice, in the friction of an outdated workflow, a word not yet invented, or the work-around that becomes the method.
Across all industries, research synthesis and content generation were identified as the highest-impact areas for AI adoption in 2026.
“You can’t apply AI to nothing. You need the disciplines themselves. Then you need to understand the frustrations they’re dealing with in order to apply AI to it.”
— Nye Warburton, Dean, School of Creative Technology, SCAD
AI Use in Creative Output
Generative AI pushes judgment upstream where decisions arrive before outputs.
Leading category
of practitioners use AI for concept visualization — the highest adoption across all tracked creative activities.
“Folks with the ability to leverage AI both in their day-to-day work and to build it into the products they work on — those skills come at a premium. We’re actually seeing the reverse of devaluation — having that capability actually increases their value.”
— Shaun Rance, Senior Design Director, Enterprise XD, Netflix
Where designers and industries adapt and restructure
Transformation appears in the gap between what designers assumed would stay and what has already given way, like a definition of craft that expanded or an ethical instinct that formed before the framework existed to name it.
of practitioners define their primary KPI for AI success as time saved.
“What AI is most helpful for is the very beginning — when you’re starting just to explore — or at the very end, a polish. But that middle part is actually where people’s voices and your own unique perspective come in.”
— CJ Jones (B.F.A., advertising, 2011), Head of Design for GenAI, Canva
Human skills growing in value
Generative AI strips away the production layer until what remains is unmistakably human.
Top human skill
Creative Direction
Identified as the human skill with the highest growing value as AI handles more production-layer tasks.
“What good design does is already changing — not what good design looks like. I think they’re two different things.”
— Karthik Narayan, Design Director, Amazon
Where design moves before the map exists
What surfaced consistently across the summit wasn’t prediction. It was direction — a shared recognition of where value is moving and what the field needs to claim before someone else does.
of respondents identify multi-agent orchestration as the emerging AI trend most likely to shape their industry, leading all categories.
“Unlike humans, who learn through embodied experience, exploration, and gradual growth, AI has no ‘childhood.’ [You] make AI practice, play, and improvise with humans by building AI that learns like a developing partner — not a perfect machine — and opens a huge, unexplored space for teaching, creativity, and skill-building.”
— SCADask survey respondent
